What is the impact of disruptive industry forces like digital transformation and sustainability on long-term business success, and how are companies responding? Companies are facing pressure from all angles, threatening their long-term survival and success. Business is digitalizing and customers are demanding more. The workforce is aging. Natural resources are increasingly constrained as populations grow…
- Disruptive Forces Threaten Business Sustainability
- Business Risk and Disruption are on the Rise
- What Drives Long-term Company Success?
- What’s Driving Company Strategy?
- Innovation Basics and Beyond Lead to Success
- Workforce Development is Critical to Success
- Economic, Environmental, and Social Sustainability
- Executives Must Lead Their Companies to Succeed
- Execution Faces a Variety of Barriers
- Sustainability has Unique Challenges
- Managing Change is a Multi-Faceted Issue
- Conclusions and Next Steps
- About the Research
- Acknowledgments
Business Risk and Disruption are on the Rise
Market Reinvention is Increasing Surveyed executives share that their markets have experienced increased business risk and disruption over the last five years. About three-quarters of companies say this turmoil has increased, with almost one-quarter saying it has increased “significantly.”
Larger Companies Face Greater Risk
Larger companies are experiencing greater challenges. A full one-half of companies with over 10,000 employees say that risk and disruption have increased “significantly.” The status quo is changing, and market leaders are at risk of disruption while challengers have great opportunities.
Few are Exempt from the Impact
Today’s industrial revolution is extremely broad. Out of all of the companies surveyed, only 4% said that this market upheaval has decreased. No participants indicate it has decreased “significantly.”
It’s Time to Act
Executives have to sustain business performance despite these conditions – or better yet find a way to capitalize on the disruption. Let’s take a deeper look at the business sustainability challenges companies face and what they’re doing about it.
What’s Driving Company Strategy?
Executives are Looking to the Future
With disruption and competing needs, what do companies take into consideration when developing and executing their business strategies? The most commonly reported corporate strategy and initiatives drivers are new market opportunities and long-term growth objectives. In fact, only 13% of respondents indicate that short-term profits influence their direction, reflecting a longer-term horizon for these decisions.
Companies Respond to Outside Pressure
Executives also report that consumer pressure and non-governmental organization (NGO) reporting influence their strategy decisions, as do financial market perception and regulation.
Although the overall results show only about one one-third of respondents say regulation impacts strategy, C-Level execs are 40% more likely to view governmental regulations as a driver than VPs and Directors. In addition, companies with over 5,000 employees are almost twice as likely to drive strategy based on government regulation.
Regulation and Oversight Drive Sustainability
Corporate responsibility and environmental issues do not directly make the list of top strategic influences, but other driving forces such as consumer pressure, NGO reporting, and regulation influence these important issues indirectly.
The influences vary by regions. For example, North America is more focused on consumer pressure and regulation than the average across regions, while Europe is more focused on NGO reporting. These factors likely drive these markets toward sustainability.
Conclusions and Next Steps
Industry Risk and Disruption Demand Change
Global markets are undergoing major disruption. Companies have to adapt to survive and prosper into the future. Current shifts in business models, technology, the environment, and socio-economic factors can challenge leaders and provide challengers the opportunity to become a disruptor. One thing is certain, the status quo is changing rapidly.
Companies are Choosing their Sustainability Initiatives
Executives are identifying and prioritizing the actions they believe will take their businesses into the future. Today, companies are focused most commonly on economic sustainability, with a strong emphasis on product and service innovation. They are keenly focused on making the transition to digital business models in order to stand the test of time.
At the same time, they recognize the need for greater environmental and social responsibility, particularly reacting to regulatory demands. In addition, customer perceptions and NGO reporting are likely encouraging sustainable approaches.
Finally, executives recognize they need to invest in the workforce of the future. This includes getting the most out of existing resources as well as attracting and retaining new talent. In order to gain value from their human resources, they are also focused on the ability to capture company knowledge and know-how.
Putting Initiatives into Action
There are numerous initiatives underway, each with their own level of executive sponsorship, funding, enterprise change management, and technology support. Companies have to take on the challenge of prioritizing and supporting each of these initiatives in order to create long-term, sustainable business success. In particular, surveyed companies would benefit from more attention to enabling enterprise technology.
*This summary is an abbreviated version of the research and does not contain the full content. A link to download the full report is available above.
If you have difficulty obtaining a copy of the report, please contact us using the "Contact" link below.
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What should you look for in a simulation solution for design engineers in your organization? How do a design engineer’s needs differ from those of an analyst? Why should a company even invest in simulation for design engineers in the first place?
Tech-Clarity’s Simulation Buyer’s Guide for Design Engineers helps answer these questions. Based on a survey of 195 companies, this report reveals what Top Performing companies value most in a CAE solution for design engineers. While this report is not an exhaustive list of requirements, it serves as a guide to help you focus on the selection criteria that matter most to design engineers.
Please enjoy the summary* below.
For the full Buyer’s Guide, please visit our sponsor PTC (registration required).
THE ROLE OF SIMULATION DURING DESIGN
How Simulation Helps
What if you could improve your design efficiency by 7% or lower your lower your prototype costs by 10%? Our survey results found that Top Performing companies have experienced these benefits and more since their design engineers started using simulation. So what’s the best way to see similar results? Let’s explore that question.
How Design Engineers Use Simulation
Products have gotten so complex; it is hard to know how a design decision will impact the rest of the design. Simulation can provide insight, enabling you to evaluate different options, design with greater confidence, and ultimately engineer better products. It also helps you catch potential problems early on. As a result, there are fewer delays and less excess cost caused by problems discovered during test or production.
In fact, design engineers get so much value from simulation, 65% would like to conduct more simulations than they currently do. Results from Tech-Clarity's Revolutionizing Simulation for Design Engineers show that it is mostly the tools that hold them back, as many solutions are not particularly well suited for the needs of a design engineer. This buyer's guide reveals what to look for in a simulation solution to meet those needs.
WHY INVEST IN SIMULATION FOR DESIGN ENGINEERS?
Design Better Products Companies invest in simulation for design engineers for a variety of reasons (see graph). Comparing responses from 2018 to 2016 reveals a trend that simulation is becoming more intertwined with the design process. Better insight for design engineers remains a top reason to invest in simulation, with even more companies citing it in 2018 than 2016. Unfortunately, "quality issues" was not an option choice in 2016, but in 2018, over 1/3 of respondents are investing in simulation to find problems during the design process rather than at the end.
SELECT THE RIGHT SIMULATION FOR YOUR NEEDS
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations to select the right simulation solution for your design engineers:- Empower design engineers with simulation tools to help guide their decisions.
- Understand your needs for a simulation solution.
- Consider how the needs of a design engineer are different from those of an analyst.
- Focus on how simulation can best integrate with the design process to improve design decisions.
- Select a simulation solution that will be easy for your design engineers, integrates with your existing CAD tool, and supports existing workflows.
- Consider a solution that makes it easy to set up an analysis and includes features that minimize preprocessing steps and provides quick results.
- Ensure the solution supports design optimization.
- Select a vendor who can provide the required support resources when needed.
What should manufacturers look for when they’ve outgrown PDM and need to “level up” to PLM? Product Data Management (PDM) is a critical capability for a manufacturer of any size. As our research shows, PDM helps companies achieve business benefits including increased efficiency, improved quality, reduced cost, and the ability to bring products to market much faster. At some point, however, most manufacturers find that their PDM system falls short of their growing needs. They face a decision to either upgrade to a more capable PDM system or “level up” to a broader PLM solution. How can they tell which direction is right for their business? What should they look for in a replacement PDM or a PLM solution?
This eBook explains how to recognize that you've outgrown PDM and offers several options to find the data and process management capabilities your company needs, whether it's time to find a more capable PDM or upgrade to PLM. It also provides practical advice on what to look for in a PLM solution, to ensure a successful implementation, and in a software partner.
Please enjoy the summary below. For the full Buyer's Guide, please visit our sponsor PTC (registration required).
Please also see our related Expanding Beyond Your Outgrown PDM Systems Buyer's Guide which shares the top ten signs you've outgrown your PDM system and what to look for in a more capable data management solution.
Table of Contents
- What to do When Your PDM is No Longer Enough
- A Guide for Upgrading from PDM to PLM
- Recognizing When the Time has Come for PLM
- When You’ve Outgrown Your PDM
- Path 1: A More Capable PDM
- Path 2: Upgrading to PLM
- What to Look for to go Beyond PDM to PLM
- 1) Manage the Whole Product
- 2) Support Product Development Processes
- 3) Expand Support of the Lifecycle
- 4) Extend to more People, Departments, and Roles
- 5) Integrate PLM into the Systems Ecosystem
- New Service and Vendor Considerations
- Special Considerations
- Next Steps
- Acknowledgments
A Guide for Upgrading from PDM to PLM
The Purpose of this Guide Like all of our buyer’s guides, this eBook is intended to help manufacturers make the right decision when they select a new solution. When companies need to move beyond their current PDM, the information in this guide will help them choose the right course of action. It complements our Expanding Beyond Your Outgrown PDM System guide that explains how to move from a basic PDM system to a more capable PDM solution. Understanding the Structure of the Guide The guide focuses on how to know it’s time for PLM, where to find PLM requirements, and some key things to look for in order to achieve the most value from the transition. The guide covers functional requirements, but also highlights what’s needed for successful implementation, adoption, and support. It also puts forward criteria to identify the right vendor partner.
References to Other Buyer’s Guides
This guide doesn’t repeat requirements covered in our existing PDM and PLM guides, including guides for selecting basic or Extended PDM systems. Those guides already share the key requirements that we’ve found make a difference in achieving desired value. In order to prevent duplication, this guide references the others to help companies gather requirements to help manufacturers quickly identify the solutions to evaluate more closely.
Recognizing When the Time has Come for PLM
When PDM Capabilities Aren’t Enough The PDM Buyer’s Guide encourages manufacturers to “consider future needs” and “build a foundation to grown on” when they select a PDM system. Sometimes that advice wasn’t followed. Other times, business circumstances dictated implementing a less capable solution.
But more often, a solution that fulfilled company needs at a certain point in time just isn’t enough anymore due to:
- Product complexity
- Product development complexity
- Growth
- Globalization
- Outdated software
- Increased product innovation maturity
- The need to achieve value beyond product development
- The need to support digital transformation
Next Steps
Leverage PDM Investments to Increase Value
Companies that have outgrown PDM can leverage their existing investment to take advantage of broader PLM benefits. The value is proven. Top Performing companies are more likely to have structured, collaborative systems like a more mature PDM or a PLM system. While PDM is often a productivity tool, PLM can drive new business value by helping to drive top-line growth.
Create a Foundation for Further Growth
As companies adopt a PLM system, it’s important to leave room to expand to more mature capabilities over time. Mature PLM systems support a variety of business processes and initiatives that translate to both top-line and bottom-line benefits. In addition, PLM scope continues to grow and expand to provide even more capabilities.
Consider a Platform for the Greatest Potential Value
We recommend that companies evaluate an integrated Product Innovation Platform (PIP) when moving to PLM. A PIP offers manufacturers the ability to expand from PDM today and create room to grow as they are ready to adopt more, or more mature, processes. A PIP with a modular approach will allow them to scale and add capabilities as they need them.
Final Words: Don’t Forget the Future
Finally, no company should select a solution without considering the cloud or digital transformation. PLM plays a vital role as the backbone of the digital manufacturing enterprise. In addition, cloud PLM solution adoption continues to increase. To ignore the realities of these two trends would be shortsighted.
*This summary is an abbreviated version of the report and does not contain the full content. A link to download the full report is available above.
If you have difficulty obtaining a copy of the report, please contact us using the "Contact" link below.
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How can CPG companies drive higher innovation performance and profitability by embracing the digital thread? Consumer Packaged Goods (CPG) companies live and die by product innovation. Delivering products that anticipate and meet market needs creates consumer loyalty and brand affinity. Developing a profitable product requires the combined knowledge of countless individuals, each contributing their expert input and domain expertise. Too often, though, their efforts are disjointed.
The Driving Innovation with the CPG Digital Thread ebook shares how consumer packaged goods (CPG) companies can streamline their product innovation and commercialization practices by innovating along the digital thread. It shares how companies can simultaneously enable R&D to innovate more efficiently while capturing the resulting IP as a reusable corporate asset by leveraging an integrated product innovation platform to create the digital thread.
Please enjoy the summary below or download the full eBook (registration required) from our sponsor by Dassault Systems.
Create Digital Continuity in Product Development
Focus on Consumer Needs Bringing successful products to the consumer is challenging. It starts by targeting the right customer needs, which should permeate the innovation process and become the central theme throughout. It then demands an orchestrated effort drawing contributions from an array of people inside and outside of the enterprise. The program has to harness their input efficiently and effectively in order to compete in today’s crowded global markets. Target Product Performance and Quality At the heart of the innovation process and the consumer experience is the product itself. The product must deliver the value the consumer seeks in a pleasing and effective way. It must deliver on the customer promise with quality, while complying with a wide variety of local requirements. Develop the Full Offering But there’s a lot more to developing a winning product than a great formulation or product specification. A successful commercial product has to deliver the right marketing messages and brand perception. It has to be offered in packaging that pleases consumers, and provides the details they need to make an informed buying decision. All of this together builds the experience that will keep consumers buying again and again.
Connect Manufacturing and the Supply Chain
The product must also be manufacturable, with ingredients that can be globally sourced. Production processes and materials must comply with a host of regulatory demands to avoid recalls and brand damage.
Tie it All Together for Digital Continuity
Each of these elements is dependent on the others, and all are critical to product success. Decisions need to take this into account, yet be made rapidly to meet aggressive time to market goals. Every aspect is crucial to developing a profitable product offering, and each has its own challenges.
Perhaps the biggest challenge, however, is that these facets are typically developed in relative isolation. Most CPG companies lack a continuous process and data flow that connects each of these activities in an overall product innovation context. Digital continuity, creating a seamless digital thread through product innovation, promises to revolutionize the way CPG companies develop – and profit from – innovation.
Table of Contents *
- The CPG Innovation Imperative
- Create Digital Continuity in Product Development
- Innovating Along an Integrated Digital Thread
- The Enterprise – Innovation Conundrum
- Help R&D Create Value
- Allow R&D to Design in Context of the Whole Product
- PLM Creates The Digital Thread for Enterprise Value
- An Innovation Platform Streamlines Digital Thread Creation
- Collaborate Along the Digital Thread
- Simplify and Accelerate Publishing Product Documentation
- Start Improving Value with the Value Digital Thread
- Acknowledgments
Start Improving Value with the Digital Thread
Recommendations CPG companies have the opportunity to step up their product innovation processes and productivity to compete in crowded, competitive markets. In order to do that, they can leverage the digital thread to:- Enable individual contributors with the right tools
- Integrate design tools within a product innovation platform that serves as the digital thread backbone
- Keep resulting information in context from early ideas through production and commercialization
- Make product information readily searchable to leverage product IP company wide
- Enable easier, more social collaboration
- Automate and streamline product documentation
How can food and beverage companies use the digital twin and industrial IoT to dramatically improve production performance? This eBook shares the value of the digital twin and IIoT for companies that produce food and consumer packaged goods. Then, it shares some practical examples and advice to get started down the path to streamline R&D and new product development, optimize production plans, increase performance, gain production intelligence, improve quality, and compete as an integrated supply chain.
Please enjoy the eBook content below or download a PDF of the eBook here (no registration required) courtesy of our sponsor, Siemens Industry Software.
You can also learn more from Siemens about the Industrial Internet of Things on their website or view our complementary report Revolutionizing Plant Performance with the Digital Twin and Industrial IoT targeted for a broader range of industries.
The Digitalization Imperative in Food & Beverage
Competition is Heating Up
Competing in the Food & Beverage market is getting increasingly challenging. New competitors are changing the rules of the game with digital processes that allow them to drastically improve speed, agility, quality, and the ability to tailor products to customer and market needs.
In the digital age, it’s no longer enough to be big. The barriers to entry have dropped as markets have transformed. Today’s markets are omni-channel, allowing even the smallest startups to gain access to consumers. Buyers’ preferences have also changed. They are more excited to try a new microbrew than consume the brand from their favorite, traditional mega-brewery. At the same time, customers are expecting food to meet their specific social, dietary, and regional preferences.
Competitive Disruption Puts Pressure on the Plant
The plant has to respond to these disruptions. Production and Operations Managers need to embrace digital, Industry 4.0 capabilities including the Internet of Things (IoT), the Industrial Internet of Things (IIoT), the digital twin, the cloud, big data, and analytics. These digital capabilities can help them increase capacity, optimize asset and resource utilization, and drive productivity gains. At the same time digitalization provides them speed and flexibility to quickly ramp up production to bring product innovations to market and shift more fluidly across different plants, lines, and regions to react to consumer demand.
Leverage Digital Enablers to Compete
Digitalization is the key to Remaining Competitive Companies are responding. A recent Tech-Clarity survey shows that more than one-half of companies say that digitalization / digital transformation initiatives are “important” if not “critical” to their business strategy. The study also finds that over 90% of manufacturers believe the IoT is likely to contribute to their business strategy, with over one-half saying the same for the Digital Twin. These initiatives, enabled by analytics, can provide significant business benefits to manufacturers. They aren’t new concepts, but they are coming of age and are now within reach of manufacturers large and small. Model and Simulate Performance with the Digital Twin The first capability we’ll discuss is the digital twin. As the name implies, it is a virtual model that represents a physical asset like a product or plant. The digital twin is a complete model that allows companies to accurately simulate performance. It can be used to help predict and optimize product and production behavior virtually to get designs right.
Significantly Expand Digital Twin Benefits with the IIoT
The power of the twin increases dramatically by connecting physical twins with their digital, virtual models via the IIoT. This digital association allows real-time performance monitoring and feeds the digital thread for traceability. Connecting twins allows companies to actively monitor the physical world in real-time, in the context of the product or plant, so they can identify or predict issues ranging from equipment breakdowns to product quality exceptions. It also allows companies to compare actual with expected performance to validate and improve simulations.
Bring External Perspectives to the Plant with IoT
The IoT expands internal information with data from outside the “four walls” of the plant. It can aggregate data from other plants, the market, retailers, suppliers, and many other sources to help make decisions in a broader context. This connectivity reduces data lag between producers and the outside world and allows them to compete as an integrated, synchronized supply chain.
Add Market and Supply Chain Intelligence with Analytics
The complete digital toolkit also includes analytical tools. These solutions help companies gain market insight and identify trends early to get more advanced notice about market shifts. This information allows plants to react in a more optimal way because time affords them more options. In addition, predictive analytics in the plant can leverage IIoT equipment data to quickly diagnose and resolve equipment or production issues before they escalate and provide data to support continuous improvement programs.
Gain Greater Benefits with Digitalization
These digital enablers are all powerful tools on their own. The benefits, however, are much greater when they are leveraged together. A completely digital enterprise has fully connected product and production digital twins that enable automated commissioning and changeovers. They use the IoT and analytics to identify and capitalize on consumer trends ahead of the competition. Finally, they leverage the IIoT to continually improve performance to gain the highest levels of productivity and quality.
Apply the Digital Twin in the Food & Beverage Industry
Leverage the Digital Twin Concept Digital enablers are providing value across many industries. Food and beverage companies have found many creative ways to gain value from the digital twin concept. Although most food and beverage companies already have mass amounts of data, they have trouble unlocking the value from it. They are now using analytics and the digital twin to gain intelligence from the data instead of simply storing it away in historians. Develop a Digital Twin of the Product One powerful way to apply the digital twin in food and beverage is to develop digital product models. These digital definitions represent formulas and recipes with all of their variations and can be used to predict product characteristics like nutritional values, adherence to marketing claims, and regulatory compliance. A full model includes production requirements to allow rapid recipe transformation to shift production between plants and adapt to site-specific production equipment.
Create a Digital Twin of the Plant
Another highly valuable application of the digital twin is establishing virtual models of equipment, production lines, or plants. These models may include different levels of granularity for different purposes, from high level models for production flow to detailed machine models that can accurately simulate production performance. The models include a fully detailed representation of manufacturing capabilities so processes can be simulated, optimized, and validated virtually. The models help manufacturing engineers and planners improve production planning and plant design.
Connect the Physical and Digital Twins
Connect Digital and Physical Twins with the IIoT Digital twins are much more valuable than static models. Modeling and simulating plant performance is not new to food and beverage companies. Production control and monitoring systems are also familiar technologies. While each are valuable, real transformative change comes from tying the digital twin together with actual physical twin performance data collected from the IIoT. Give Meaning to IIoT Data The value of the digital twin comes from connecting the virtual and the physical environments. This provides visibility to real-world performance data from sensors on production and packaging equipment collected via the IIoT and provides the context to interpret the information. For example, time series data is meaningless without an understanding of intended performance. This connectivity helps companies monitor actual performance to optimize the health and condition of a piece of equipment or the plant, and gain insights into how the physical assets actually perform. It also helps companies gain perspective from the market and the supply chain. Identify and Address Anomalies and Issues Manufacturers can learn a lot from discrepancies between simulated performance predicted using the digital twin and actual performance measured on the physical twin. Identifying these variances can identify issues in the plant that can be diagnosed and remedied to bring performance back into plan.
Improve Models, Plans, and Simulations by Replacing Assumptions with Facts
Connecting the physical and digital twins with the IIoT helps companies learn and continuously improve by interpreting real-world behavior. They can improve planning and optimize production based on observed behavior in the plant as opposed to calculated values. This lets planners use real-world results and scenarios to improve their simulations.
Streamline R&D and NPDI with the Digital Twin of the Product
Develop a Holistic Product Model First, let’s look at R&D and NPDI. Developing a fully digital product specification helps streamline R&D and product development. Digital R&D organizations can start with requirements and add ingredients, labels, and packaging to develop a fully digital specification. Developing the formula digitally allows downstream departments like Marketing or QA to get started in parallel and add their own information to the model. Working in parallel enhances speed, but more importantly provides visibility so decisions impacting others are recognized and evaluated early while there is still time to change. For example, Compliance can see a change to the formulation to determine if packaging or labeling must be updated to reflect the impact on ingredient listings, nutritional facts, certifications, or claims.
Extend Product Models to Production
Formulas can be extended with process steps and related production data to create a fully digital recipe. Digital recipes can then be transformed to meet local regulations and equipment availability. Maintaining an integrated model of materials and processes allows companies to readily adapt them to changing demands.
Optimize Plant Assets and Production Plans
Leverage Plant Models to Plan and Optimize Production How do these models improve performance? A digital twin of the plant lets food producers get the most out of their plant investments. Digital twins of the plant model production capabilities with enough fidelity to predict behavior and performance. For example, a beverage company could simulate sequencing, changeovers, tanks, pipes, batch sizes, filling, and packaging. They can also incorporate business factors such as seasonal or geographic variability of products and ingredients. These twins can be used to simulate, iterate, and optimize everything from material flows to equipment. This allows planners to optimize processes digitally before committing to a production plant, changing a line, or commissioning a new product. Twins eliminate bottlenecks, avoid quality issues, reduce cost, and reduce changeover times before committing to physical assets. This get things right the first time and build in the flexibility to react more quickly to changing consumer demands.
Get More from Production Equipment with IIoT (and Analytics)
Keeping a Virtual Eye on Production Equipment Let’s explore how to apply the connected digital twin. Although food and beverage producers likely have a control system and/or a data historian that captures large volumes of data, they typically have little understanding of how equipment is performing or when it may have an issue. The IIoT lets food and beverage companies monitor the performance and health of their critical production assets in real-time so they can receive alerts and rapidly identify, diagnose, and correct issues before the problem escalates. Gaining Equipment Intelligence An IIoT platform with analytics goes beyond simple alerts. It allows plant personnel to connect, aggregate, filter, and analyze information from sensors and existing control systems to drastically improve uptime and performance. One proven way to gain value is moving away from preventative maintenance to a more predictive model. For example, companies can replace scheduled preventative maintenance based on operating hours or a reactive break-fix approach by using the IIoT and analytical algorithms to identify equipment behavior that precedes a failure.
Enhance Quality and Productivity
Gaining Insight and Intelligence on Production Beyond monitoring a piece of equipment, food and beverage companies can monitor production as a whole. For example, IIoT data can be shared in a dashboard to make key production KPIs like cycle times or yield visible so operators can quickly identify issues. The IIoT platform can detect anomalies and provide alarms so plant operators can correct issues as they occur, if not earlier. IIoT data can also provide intelligence to help managers benchmark lines, plants, and geographies for continuous improvement. And, it can help close the loop between R&D and the plant by comparing actual versus predicted batch specifications. Associating Production Parameters with Quality Outcomes Combining information from production equipment with lab results can help provide insights into potential quality drifts that leads to scrap or rework. By correlating actual batch results with equipment settings, ingredients, suppliers, personnel, or environmental factors that may be impacting quality or throughput manufacturers can find and alleviate root causes.
Compete as an Optimized Supply Chain
Benchmark Your Manufacturing Network Digital twin value goes beyond the enterprise. Companies can learn a lot by comparing production across multiple facilities. Plants can share IIoT data with corporate headquarters or a center of excellence through the cloud. Analyzing product data across the network, whether it consists of their own plants or contract manufacturers, can help identify regional variances. Further analysis may uncover additional insights that can be used to identify issues or share best practices to ensure high productivity and product consistency across the globe. Close Information Gaps in the Supply Chain Digital companies compete as a supply chain. For example, they can work closely with ingredient suppliers on R&D or collaborate with retailers on promotional packaging. Or, suppliers can proactively share specifications for natural ingredient shipments so that formulators can begin to modify recipes based on data like actual moisture or sugar content. Digitalization allows companies to better share information to improve agility, productivity, and quality.
Next Steps
Getting Started The value of the digital twin to Food and Beverage companies is significant. To get started, food and beverage companies can choose between a number of valuable initiatives that leverage the digital twin, IoT, IIoT, and analytics. For example, they can:- Apply the digital twin of the plant to optimize production planning
- Simulate production on the digital twin to optimize plants in the virtual world before committing to physical assets
- Monitor equipment to gain equipment intelligence and improve uptime
- Use IIoT and analytics to shift from preventative to predictive maintenance
- Monitor production to rapidly identify and correct quality or productivity issues
- Connect with the market and the supply chain via the IoT to gain advanced insights into market trends and consumer preferences
- Leverage measured results from the physical twin to improve simulations by providing the digital twin with observed production scenarios and parameters
Recommendations
It’s time to leverage the IIoT to connect the digital and physical twins to improve availability and production performance. The most important recommendation is to get started, learn, and grow benefits over time. Food and beverage companies can start small and expand value by building on the foundation of their first initiatives.
It’s important, though, to consider needs like equipment connectivity, security, and analytics. Leveraging an integrated platform of digital solutions designed for the food and beverage industries can help. A platform approach also helps ensure that early investments are repeatable and can be used as a foundation for further value.
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Effective Tech Transfer is crucial to delivering innovative products to market. Can companies improve Tech Transfer through the use of digital data, processes, and technology? We surveyed over 200 companies to find out.
Please enjoy the summary below.
For the full report, please visit our sponsor BIOVIA Dassault Systems (registration required).
Improve Tech Transfer, Improve Profitability
Tech Transfer is the Bridge Between Innovation and Profits Process manufacturers must continuously innovate to differentiate and remain viable in competitive, global markets. They have to be agile, delivering customer-driven and market-centric solutions quickly across their global production network. At the same time, they have to continuously improve quality and cost to drive customer satisfaction and profitability. Tech Transfer is an inherently data-driven process that translates R&D innovation to the plants. It is also the vehicle that supplies real-world production feedback to R&D for continuous improvement. This makes Tech Transfer a critical competence to achieve and maintain product profitability. Identify Digitalization Improvement Opportunities This research identifies the significant challenges companies face in Tech Transfer and analyzes how best practices and increased digitalization improve Tech Transfer performance. At the highest level, the results indicate that Top Performing companies have more digital data and processes. Let’s take a look at the details.
Table of Contents*
- The Impact on Business Performance
- Tech Transfer Complexity on the Rise…
- Complexity Adds Up…
- Contract Organizations Lead to Complexity
- Identifying Tech Transfer Performance Leaders
- Tech Transfer Fundamentals Lead to Success
- Differentiating Practices of the Top Performers
- Adopt Higher Levels of Process Digitalization
- Digitalize Data and Automate Data Collection
- Integrate Systems More Completely
- Leverage PM and Specialty Scientific Solutions
- Leverage Analytics
- Digitalize to Improve Business Results
- Get Started – Digitalize Tech Transfer Now
- About the Research
- Acknowledgments
Digitalize to Improve Business Results
Tech Transfer is Strategic Tech Transfer is a challenging process that companies have to master to deliver innovation to market. Companies must transfer products with quality despite the need to control cost and the demand for speed. Companies that don’t master Tech Transfer will suffer from the inability to successfully innovate. Challenges are Increasing Unfortunately, there is little relief in sight. The data shows that Tech Transfer complexity is on the rise.
Digitalization is the Solution
Digital transformation is a proven approach for companies in the process industries. Our research shows direct benefits of digitalization in the laboratory and beyond. The research finds a clear correlation between developing better products and greater data and process digitalization in the lab. The research also found that the companies surveyed are much less digital BEYOND the lab, providing significant promise to improve Tech Transfer.
Get Started – Digitalize Tech Transfer Now
Digitalization Differentiates Top Performing Companies in Tech Transfer This survey extends prior findings to show that companies can improve Tech Transfer performance through digitalization. Digitalization shows clear value in Tech Transfer. Specifically Top Performers:- Are more likely to use cohesive, integrated, digital product models
- Have more digital, standardized processes
- Have more digital data
- Have more automated data collection
- Have more integrated lab / manufacturing systems
- Take a more global systems approach
- Use project management software
- Use more specialty lab systems including SDMS, QMS, and LIMS
- Use more analytics capabilities, and use them better
What do designers, engineers, and product developers need to know about managing product data to stop wasting so much time managing CAD files and start hitting their new product development targets?
Join this interactive webcast, The Facts about Managing Product Data, to learn how Top Performers spend less time managing product data and more time designing. Get a sneak peek at new survey data to learn how leading companies use extended PDM systems to develop and launch high quality products.
Register for the Autodesk sponsored webcast now (registration required).
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How can Automotive and Transportation companies leverage the cloud to improve innovation, engineering, and manufacturing across the product lifecycle? We conducted a survey to find out how Automotive manufacturers are approaching the cloud PIP opportunity. We gathered over 250 survey responses from manufacturing and engineering services firms, and took a closer look at approximately 100 of them in the Automotive industry. The research analyzes both challenges faced and benefits achieved by Auto companies using cloud-based applications. The eBook shares implementation, adoption, operational, and business benefits of cloud systems and how they impact today's digital auto manufacturer. The report also touches on some specific topics including the use of cloud standards and audits to help mitigate security risk and how cloud platforms enable value-added services in the context of innovation tasks.
Please enjoy the full eBook below for no charge or download a PDF free of charge, thanks to our sponsor Dassault Systèmes. Or, learn more on the Dassault Systèmes website.
You can also read our Aerospace and Defense Industries Adopting Cloud Platform eBook or watch our Tech-Clarity TV episode sharing the A&D research highlights.
Cloud Opportunities for Automotive
The Automotive Industry is Facing Disruption The Automotive industry is undergoing a major transformation with the evolution to electric, connected, autonomous vehicles (ECAV). This shift has introduced a significant influx of innovative startups including many from outside of the traditional automaker community. Product innovation, engineering, and manufacturing software are the tools of the trade needed to help Automotive companies innovate in these dynamic times. They can help today’s OEMs and suppliers remain competitive so they can take advantage of this market disruption instead of becoming a victim of it. Auto Industry Adopting Cloud Solutions Another significant trend across industries is the adoption of cloud solutions. The cloud offers significant business, implementation, and operational benefits. Unfortunately, Automotive companies have historically been forced to make tradeoffs between the highly capable, integrated solutions – the Product Innovation Platform (PIP) – and the cloud. Now, PIPs are available with cloud deployments, offering the best of both worlds. Product Innovation PlatformsEvolution of Product Innovation Platforms
Before we explore the evolution to the cloud, it’s important to understand how PIP solutions have evolved. Engineering solutions have enabled companies to design products with unprecedented levels of innovation. They’ve advanced to model and simulate new materials, advanced manufacturing methods, systems, and other characteristics to more accurately predict product behavior.
These engineering tools are integrated with data and process management solutions that support products, processes, and programs. These PLM tools have expanded to support a broader view of the product and support a wider range of processes ranging from ideation to launch.
Needs Expand for the Digital Enterprise
The digital transformation demands more. Solutions must support a more integrated approach, enable data-driven design, and support model-based systems engineering. They need to support digital continuity where each engineering discipline contributes their design into a comprehensive, cohesive model. They must enable real-time, secure collaboration across domains and the supply chain whenever and wherever needed.
The PIP creates a comprehensive digital thread, supports a cohesive digital twin, and breaks the paradigm of disparate, file-based systems. And it’s now available on the cloud.
Automotive Companies Open to Cloud
Cloud Adoption is Growing
Manufacturers and suppliers across industries have begun to adopt cloud solutions. Our research finds that an increasing number of companies are transitioning to the cloud in order to take advantage of significant benefits, including:
- Cost reduction
- Reduced IT resource needs
- Agility
- Scalability
- Flexibility
- Ability to work anytime, anywhere
- Rapid deployment and time to benefit / ROI
- Lower implementation risk
- Shifting capital investments to expenses
Succeeding in the Automotive Industry
The Industry Demands Product Excellence Ask people in the Automotive industry what leads to success and you’ll hear that product quality has a major impact. As you might expect, survey respondents report product quality as a profitability and success driver more frequently than any other factor. But innovation, reported as a profitability driver more frequently by Automotive companies than any other industry in our survey, isn’t far behind. Perhaps this isn’t surprising given the major changes facing the industry. The top success factors – quality, innovation, reliability, performance, and cost – are all related to product excellence. But today’s dynamic market also demands agility. In fact, OEMs were almost twice as likely as suppliers to report time-to-market as a critical success driver.
The PIP Delivers Product Excellence and Agility
Our research shows that an effective PIP can help improve all of these factors. These platforms, incorporating engineering tools and PLM capabilities, are proven to drive better product development results. The cloud is reducing the barriers to these PIP solutions and provides benefits in multiple dimensions, including affordability, flexibility, and agility. We explore these further in the survey.
Business Benefits of the Cloud
Cloud Software Provides Multi-Dimensional Benefits Why are other companies using the cloud? Cloud software provides benefits in three dimensions:- Business
- Implementation
- Operational
Cloud Enables to Working Anytime, Anywhere
The most commonly reported business benefit is the flexibility to work anytime / anywhere, reported by two-thirds of participants. This is followed by ease of collaboration. This capability, along with the ability to have more integrated workflows as reported by about one-half of companies, allows OEMs and the supply chain to work together more efficiently and effectively. This is particularly important for Automotive companies given the global nature of their business, the need to be agile, and the integrated nature of the automotive value chain.
Automotive companies also pointed out the value of faster access to new capabilities, helping them get more value from their applications. The cloud gives companies flexibility in the capabilities they adopt and accelerates time to value.
Implementation Benefits of the Cloud
Automotive Values Faster Time to Value The implementation and adoption experience for cloud solutions is typically very different from with traditional solutions, offering some significant advantages. The Automotive industry has already enjoyed these benefits in other types of solutions. Many companies initially consider cloud solutions in order to save money. Affordability is an important factor in any industry. But cost is actually slightly less commonly mentioned as a benefit than faster time to implement. The cloud can save money, but it also helps companies be more agile, getting their solutions up and running faster. Faster implementations helps them achieve the intended business impacts of the applications – improving quality, innovation, reliability, performance, and product cost to drive company success – more rapidly.
Other Benefits
Other benefits mentioned include lower hardware costs and reduced IT needs. Each of these can provide additional savings. It’s also interesting to note that reduced IT needs gives companies the flexibility to implement solutions faster because they don’t have to wait for internal resource availability.
Operational Benefits of the Cloud
Cloud Solutions offer Ongoing Benefits Beyond implementation benefits, there are ongoing operational benefits available from cloud deployments. The flexibility to scale user counts is the most frequently reported benefit, and one-half report computing scalability as an advantage. This kind of agility is particularly valuable for program-oriented companies and shifting demands for designing today’s vehicles, including ECAV. In addition, companies across industries report cost- and resource-related operational benefits. Over one-half cite reduced IT needs and well over one-third cite reduced software / hardware operational costs, making PIP more accessible and affordable.
Cloud Benefits Improve the Business, not Just IT
Ease of supporting multiple locations is reported by over one-half of participants. This can be a significant benefit for companies with global footprints that must support multiple sites. In addition, about one-third mention ease of supporting mobile devices. These results highlight the fact that the cloud makes accessing solutions easier, helping companies take advantage of their applications to improve the business. These factors also enable easier collaboration that can help drive the quality, innovation, reliability, performance, and cost improvements that automotive companies seek.
Lastly, it's an interesting note that about one-third observe that the cloud helps them get faster access to new capabilities - again helping companies be more nimble and get greater value from their applications.
Value-Added Services in the Context of Innovation Tasks
Transitioning to the Cloud Opens Opportunities One of the unique benefits of cloud solutions is the ability for the software vendor to provide links to services beyond the capabilities of the software. For example, an engineer working on a program could be offered help with their design task, sources to find capacity for an advanced manufacturing process, or a service to gather data from the supply chain on their behalf.
Automotive Companies Value New Services
Automotive companies have a very positive view on the value of services that could help them with their current task. The vast majority say these services might be useful or a big benefit, while very few share indifference or a belief that it would be distracting.
The Cloud Provides Targeted Services
Cloud software can provide targeted help because it’s aware of the function that users are performing and can provide tailored offers. It can also dynamically link to the right sources of assistance in a marketplace format, to help bring people together.
Finding help where it’s easy for people to connect via the Internet when they need something can be much more expedient than a typical search and procurement process. This is another area that can help companies deliver the quality, innovation, reliability, performance, and cost improvements they need to succeed.
PIP Capabilities and Cloud no longer Require a Major Tradeoff
Mature PIP is now Available on the Cloud As seen earlier, the cloud offers benefits along multiple dimensions that help companies reduce cost and risk, while providing the tools they need to succeed. Despite the advantages of a cloud deployment, companies have traditionally had to choose between full-featured systems and cloud solutions. Fortunately, Automotive companies no longer have to sacrifice the capabilities they need to innovate and drive quality because they are available in cloud PIP solutions. Automotive Demands Capabilities and Cloud The majority of Automotive companies say software capabilities are more important than taking advantage of cloud-specific benefits. Over one-half of Automotive companies say they’re willing to give up “very little” or no software capability to use cloud software. A significant number say they won’t compromise software capabilities at all in order to gain the benefits available from the cloud. Although about one-third are willing to give up “some” features, less than 10% said they would give up “quite a bit” of functionality for the cloud.
Mature Cloud PIP is now Available for Automotive
We believe taking this “software first” approach is the right priority for Automotive companies, because software capabilities provide the benefits of the Product Innovation Platform, including the highest success and profitability factors – quality, innovation, reliability, performance, and product cost. Now, Automotive companies can leverage robust PIP capabilities on the cloud.
Challenges Faced with Cloud Solutions
Cloud Solutions Address Security Concerns There are clearly challenges that have to be addressed with cloud computing, but there has been significant progress. For example, just less than one-half of Automotive companies still perceive security as a "significant risk.” Security is an important issue, of course, and one that requires attention regardless of whether a solution is deployed on the cloud or in a more traditional setting. Ironically, many companies including innovative startups are moving to the cloud to reduce security risk. They believe cloud solutions are more secure because cloud providers can leverage more dedicated security personnel and processes due to economies of scale.
Other Concerns
There are other concerns as well, but none that were reported as a significant risk by more than 15% of respondents. Companies should still pay attention to these needs and consider including key performance criteria in Service Level Agreements (SLAs) that incent providers to perform in these areas.
Automotive companies adopting the cloud will likely have to adjust their approach to upgrades, integration, and customization to work with their deployment option. But these solutions are well known as cloud experience across multiple domains has become commonplace.
An Opportunity for Improvement – Standards and Audits
Standards and Audits Reduce Security Risk One of the ways that companies can mitigate cloud-oriented risks in the previous chart is through the use of standards and formal audit processes. In fact, manufacturers across industries who currently use cloud standards and audit processes are over 50% less likely to consider security a "significant risk,” although the majority still say it's at least a "concern.” Perhaps not surprisingly, the largest challenge Automotive companies face with the cloud, or expect to face, is security. But when asked about cloud standards and audit processes to ensure application performance and security, it appears that most Automotive companies aren’t adopting them.
Lack of Awareness of Standards and Audits
About one-quarter of respondents say their company is unaware of cloud standards and audits. About another one-quarter are aware but not adopting them. Over another one-quarter say they don’t know if their company is aware of them. Implementing standards and audits is a clear opportunity for education and improvement that can help mitigate security risk.
Conclusions
The Cloud Opportunity is Compelling Cloud solutions offer benefits along implementation, operational, and business dimensions. They provide companies the flexibility and agility they need to compete in today’s changing Automotive market as old and new players alike try to capitalize on the transition to electric, autonomous vehicles. Cloud Computing without Tradeoffs With the right cloud solution Automotive companies don’t have to choose between capabilities and the cloud. They can leverage the functionality they need to compete and gain value from them faster than previously possible. Automotive companies face a number of challenges in order to leverage the benefits of the cloud, including security, which should be addressed through SLAs, standards, and audit procedures. It’s important to understand, though, that in many ways cloud deployments actually help with these challenges by offering shared services with dedicated specialists. Cloud Adoption in Automotive will Accelerate We see cloud PIP adoption accelerating in the Automotive industry, providing compelling benefits. We expect to see cloud solutions become a primary option as manufacturers seek to compete with innovative, new companies in new categories like ECAV. Companies are not willing to trade off the PIP features that directly impact their success drivers – quality, innovation, reliability, performance, and product cost.Recommendations
Recommendations and Next Steps Today’s highly capable solutions offer the power of mature PIP capabilities along with cloud benefits, providing the flexibility and affordability that makes advanced features available to Automotive companies of all sizes.
Based on this research and our experience, we recommend that Automotive companies:
- Focus on quality and innovation to drive success and profitability
- Leverage a Product Innovation Platform (PIP) to help them develop innovative, high quality products with high performance, great reliability, and lower cost
- Adopt cloud solutions to enable anytime, anywhere access to capabilities
- Reduce implementation cost and risk while increasing flexibility and agility with the cloud
- Achieve faster time to benefit and adoption of new capabilities through cloud deployments
- Adopt cloud standards and audit procedures to mitigate security risk
- Implement Service Level Agreements (SLAs) to further reduce risk
About the Research
Data Gathering Tech-Clarity gathered and analyzed over 300 responses to a web-based survey on the use of cloud software. Survey responses were gathered by direct e-mail, social media, and online postings by Tech-Clarity and Dassault Systèmes. Of those, 254 were manufacturers or engineering firms (primarily excluding consultants, software vendors, and academia) of which 100 serve the Automotive Industry. Demographics The respondents represented a mix of company sizes, including 19% from smaller companies (less than $250 million), 13% between $250 million and $1 billion, 13% between $1 billion and $5 billion, and 26% greater than $5billion. 29% did not disclose their company size. Company sizes were reported in US dollar equivalent. The respondents were comprised of over about two-thirds (63%) individual contributors, more than one-quarter (30%) manager or director level, 3% who indicate they are VP or executive levels, and 4% other roles. Of the respondents, 52% were in engineering or design roles (including industrial / manufacturing engineering), 15% were in Information Technology (IT), 13% were analysts / simulation experts, and the remainder were from a variety of organizations including Program Management, Service, Manufacturing, Sales, Quality, and General Management. The companies were primarily OEMs (51%), with 30% component/subsystem suppliers, 7% part suppliers, 4% contract designers, 4% contract manufacturers, and 4% others. The respondents reported doing business globally, with the about two-thirds of companies doing business in the North America (66%), about the same amount doing business in Western Europe (62%), 34% doing business in the Asia-Pacific regions, 22% in Eastern Europe, 14% in Latin America, 5% in Australia, 3% in the Middle East, and 2% in Africa. Note that the numbers total greater than 100% because companies reported doing business in multiple geographies.
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[post_content] => What unique value does the cloud offer to companies using product innovation and engineering software? Our research identifies five categories of cloud benefits and finds some areas where the cloud really stands out for product innovation platforms.
Read the guest post in full in the Digital Transformation section of the Siemens PLM Community blog.
Jim Brown followed his recent guest post The Subtle Shift to "Why Not Cloud?" with a new post sharing more details on the value cloud software offers to PLM and other engineering software solutions. The post shares how cloud engineering software offers benefits beyond the basics related to:
- Collaboration
- Infinite Computing
- IoT and Analytics
- Scalability
Read the post on the Siemens website for more information (no registration required), or access some of our prior research on using cloud for PLM.
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[post_content] => How can manufacturers use the digital twin and industrial IoT to dramatically improve manufacturing and product performance? This eBook shares the value of the digital twin and IIoT for products and in the plant. Then, it shares some practical examples and advice to get started down the path to improved performance, availability, and product quality.
Please enjoy the eBook content below or download a PDF of the eBook here (no registration required) courtesy of our sponsor, Siemens Industry Software (formerly known as Siemens PLM Software).
You can also learn more from Siemens about the Industrial Internet of Things on their website.
Disruption Demands Digitalization and the Digital Twin
Manufacturing is Undergoing a Revolution
The manufacturing industries are getting more challenging. Manufacturers must evolve as new technologies remove barriers to entry and enable new, digital players to challenge market share. Operational efficiency is no longer enough to compete in today’s era of digitalization and Industry 4.0.
To remain competitive, companies have to maintain high productivity while offering unprecedented levels of flexibility and responsiveness. We believe this is a fundamental disruption that will change the status quo. To survive, manufacturers need to digitalize operations in order to improve speed, agility, quality, costs, customer satisfaction, and the ability to tailor to customer and market needs.
Raising the Bar with Digitalization: The Digital Twin
One of the most compelling digitalization opportunities is adopting the digital twin. This approach combines a number of digital technologies to significantly improve quality and productivity. It starts with comprehensive, virtual models of physical assets – products and production lines – to help optimize designs. But the value is much greater because the physical and virtual twins are connected and kept in sync with real data from the Internet of Things (IoT) and Industrial IoT (IIoT). Further, companies can use analytics to analyze digital twin data to develop deep insights and intelligence that allow for real-time intervention and long-term, continuous improvement.
The Digital Twin’s Impact on the Plant
The digital twin holds significant productivity and quality opportunities for the plant. It can be used to understand when the plant isn’t operating as intended. It can identify or predict equipment issues that can result in unplanned downtime or correct process deviations before they result in quality slippage, scrap, and rework. In addition, it can significantly further benefits already achieved by six sigma programs and support greater continuous improvement. Let’s learn how manufacturers can leverage the digital twin to improve plant performance and product quality.
How the Digital Twin Drives Value
Develop Comprehensive Virtual Models (the Virtual Twin)
First, let’s step back to discuss what a digital twin is and, more importantly, how it creates business value. Digital twins consist of a virtual model and a physical item that are identical. At the core, the virtual component of the twin is a model that is rich enough to simulate and predict the physical item’s behavior. These representations can be used to optimize and validate designs early in the product or asset lifecycle and are subsequently kept in sync with the physical item throughout its life.
The digital twin concept can be applied to a number of different physical items:
- Products (equipment, devices, etc.)
- Production (machines, lines, plants)
- Infrastructure (cities, etc.)
- Something wrong with the physical asset that can be corrected
- Something wrong with the virtual model or simulation that leads to new understanding and provides knowledge for future modeling and simulation efforts
Applying Virtual Twins in the Manufacturing Industry
Target the Right Virtual Twins for Manufacturing There are many ways to gain value by applying the digital twin approach in the manufacturing industries. In the plant, the typical ways to create value are from creating twins for products and for production assets. Let’s discuss how to create and drive value from each of these.
Develop Virtual Twins of Products
The first way many people think of the digital twin is as a digital model of a product. This typically starts with a 3D CAD model, but also captures much of the information captured in model-based design approaches. For today’s smart products, the model typically incorporates electronic, software, and systems designs.
The virtual product twin can be used to simulate and communicate planned product behavior and predict product characteristics like throughput, torque, energy consumption, or other performance characteristics. To do this, the virtual twin must accurately represent a specific configuration or unit of the product and be kept up to date with changes. The product model should also include production requirements to support a design anywhere / produce anywhere strategy.
Create Virtual Twins of the Plant
One manufacturer’s product may be the equipment in another’s plant. The virtual model concept extends to equipment, work stations, lines, and entire plants. These twins should completely model production at the appropriate level of granularity for their intended purpose.
The twin can also include the virtual twin of products being produced and the operators running the plant.
These models can be used to simulate and optimize production plans, plant layouts, materials flows, and equipment. Manufacturers can use the models to virtually operate the plant all the way down to control code in order to detect collisions, bottlenecks, and analyze throughput. This allows them to optimize production behavior virtually to get designs right before making physical investments.
Finally, virtual twins can be used to develop code for CNC equipment that can be run and validated on virtual PLCs using an approach known as “software in the loop.” This code can then be used for virtual commissioning to speed ramp up and changeovers.
Creating the Complete Digital Twin in Manufacturing
Gain Greater Value from Connected Digital Twins
The value of digital twins specific to manufacturing is greatly enhanced when the virtual and physical twins are connected via the IIoT. Manufacturer operations can produce a lot of data. For example, companies may already have MES and other control data, but they traditionally have trouble unlocking the value from it. The value of this data is made tangible when it’s put into the context of the digital model. Connecting the virtual and physical twins allows companies to compare actual to expected results and behavior of plants, product lines, work cells, machines, and even the products produced. The digital twin helps them gain intelligence from the data instead of simply storing it away.
Connect and Analyze Plant and Product Virtual Twins
Manufacturers can learn a lot from discrepancies between expected performance predicted using the virtual twin and measured performance of the physical twin. The twin defines what “good” looks like in production and what “right” looks like with the products. Variances from simulated values may identify issues in the plant that can be diagnosed and remedied to bring performance back into plan.
A more complete digital approach leverages analytics and the cloud. Analytics creates deeper insights to gain product and process intelligence. Let’s take a look at how the intelligence derived from the digital twin drives tangible business value for manufacturers.
Improve Equipment Performance and Availability
Monitor and Optimize Equipment Performance The first way we’ll examine the business value of the digital twin in the plant is by improving equipment performance. Today’s manufacturers need to get the most out of available production assets. Manufacturers can use the digital twin to monitor equipment and production via the IIoT. They can aggregate, filter, and analyze sensor and control data in the context of the virtual twin to find issues. The resultant information can be shared in dashboards and put into action with alerts so issues like reduced production rates can be addressed before they arise or escalate. Predict and Improve Equipment Availability One of the most promising ways manufacturers improve productivity is through predictive analytics. Instead of maintaining production equipment on estimated service intervals, manufacturers can monitor equipment to identify when it begins to show signs of wear or failure, such as higher temperatures or vibration. But analytics can also find hidden patterns, anomalies, or trends in operational data that may indicate a pending equipment failure. Transitioning to predictive service allows manufacturers to reduce downtime and avoid the cost of unnecessarily taking equipment offline for maintenance when it’s not necessary. Of course, not every issue can be predicted, and in those cases IoT and the digital twin can provide the intelligence needed to improve issue identification, reduce repair time, and analyze root causes. The resulting enhanced productivity from better equipment performance and availability directly drives improved profitability.
Improve Product Quality
Monitor and Maintain Product Quality
The next way that digital twins offer tangible business value to plants is by improving quality. Manufacturers can use the IIoT to monitor production and compare it to the digital twin to find goods that are trending out of spec. For example, they could compare product tolerances with IIoT feeds from metrology devices to find anomalies. Then, they can use trend charts, histograms, or dashboards with alerts to identify potential quality slippage.
Control and Assure Process Quality
In addition to measuring production output, manufacturers can monitor the production process to build quality in. They can collect KPIs like cycle times or track control parameters to identify when processes aren’t fully in control so they can intervene.
Manufacturers can also use analytics to understand the relationship between variability in production specifications and output to help identify factors that lead to quality slippage. They can use artificial intelligence (AI) to gain insights from a combination of enterprise system data, environmental conditions, operator information, equipment setup, and machine settings. This can help them close the loop between engineering and actual resulting product performance characteristics, for example finding relationships between equipment settings or environmental factors and defects. They can also leverage AI to identify early indicators that production isn’t behaving as expected in order to identify and correct errors in real time.
Next Steps
The Digital Industrial Revolution Requires Action Today’s manufacturers need to deliver high operational efficiency in order to compete. It’s time for them to digitalize to gain important benefits – agility, productivity, quality, cost, customer satisfaction, and responsiveness – and remain competitive into the future. Manufacturers can apply the digital twin concept to products, plants, or both to drive new levels of quality and productivity. The digital twin and the IIoT are key digitalization enablers with tangible, proven value.
Get Started
To get started, manufacturers can choose between a number of valuable initiatives to leverage the digital twin, IIoT, and analytics. For example, they can use the digital twin, IIoT, and analytics to:
- Gain equipment intelligence and improve uptime
- Shift from preventative to predictive maintenance
- Monitor production to rapidly identify and correct quality or productivity issues
- Leverage actual results from the physical twin to improve simulations by feeding the digital twin with observed production scenarios and parameters
- Explore new business models by applying digital twin capabilities to their own products
To learn more, see the related Buyer's Guide for Retail Predictive Analytics.
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How can you empower design engineers to make more informed decisions that can help set your products apart from the competition?
Tech-Clarity’s Empowering Design Engineer infographic helps answer this question based on a survey of 195 companies.
The infographic reveals top qualities that will make products more competitive over the next five years. These product qualities depend on good engineering decisions. Yet, 76% rate these decisions as ‘somewhat hard’ to ‘extremely difficult.’
The infographic uncovers a potential approach to make these decisions easier. The infographic also explores how new approaches to simulation may help make CAE a powerful tool for design engineers.
View the full infographic from our sponsor PTC (no registration required).
To learn more, see the related Revolutionizing Simulation for Design Engineers research report.
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[post_content] => BOM Processes Rely on Inadequate Solutions
Ineffective BOM Processes Cause Disruption
BOM management is critical to connecting design, purchasing, and production across a manufacturing business. Ineffective BOM processes, though, lead to low productivity and costly errors.
With that in mind, why do so many manufacturers rely on substandard BOM management approaches like spreadsheets and email? Is there a better way for companies to support BOM-related processes?
Table of Contents
- BOM Processes Rely on Inadequate Solutions
- The BOM is the Fundamental Communication Tool
- The BOM Process Status Quo
- The Five Fundamentals of a Successful BOM Process
- 1) Aim for Accuracy
- 2) Keep Data Current
- 3) Manage Complete BOMs
- 4) Communicate BOM Data Clearly
- 5) Put BOM Data into Action
- Next Steps
- Acknowledgments
The BOM is the Fundamental Communication Tool
BOMs are the Backbone of the Manufacturing Industry BOMs are the fundamental way that manufacturers define, communicate, and realize their products. The bill of material is essentially the backbone of the manufacturing business, specifying what to buy and what to build. In many companies, BOM communication has to bridge disciplines across company boundaries. BOMs are The Primary Communication Tool in Industry Sound BOM processes create a bridge that crosses all parts of the organization. They document engineering designs and provide the information that Purchasing needs to order parts. Then, they deliver the data needed for Manufacturing to plan and execute orders. BOM data also serves as the backbone for others to roll up important attributes like weight, costs, and more.
Successful BOM communication across Engineering, Purchasing and Manufacturing:
- Helps improve productivity
- Reduces the number of shipments delayed by missing parts
- Drives down scrap from using wrong parts or revisions
- Improves cost through item reuse
The BOM Process Status Quo
Spreadsheets are the de facto Standard
The easiest way to sum up the BOM process status quo in most manufacturers is with a single word – spreadsheets. BOM processes frequently involve very complex spreadsheets. They are hard to interpret, lead to duplicating data, don’t manage data relationships, and often contain errors. As our BOM Management Buyer’s Guide shares, many companies manage BOMs in ways that don’t adequately support the business, including documents or embedding BOMs into CAD drawings in addition to spreadsheets.
Sharing BOMs via Email Creates Risk
Spreadsheets are not good for data management, and they are even more problematic when they’re shared through email. As soon as a BOM is attached to an email it creates a risk that somebody will access it after it is no longer valid. These informal methods are also challenging because data in a spreadsheet can’t easily be integrated with downstream people, processes, and systems. Because of this, unmanaged methods fall apart quickly for all but the simplest of companies.
Why Accept the Current Status Quo?
Why do manufacturers put up with this? Perhaps because it’s the way they’ve always done it. Perhaps they don’t recognize how many of their issues have poor BOM processes as the root cause. In many cases, they are just believe that fixing the problem is going to be complicated, time-consuming, and require expensive solutions.
They think that putting the basics of BOM management in place is going to slow them down, and that they’re not ready for a PLM or ERP system. This is particularly true for smaller companies. But big companies often run with immature BOM management processes as well. How can manufacturers upgrade the status quo without adding additional cost and overhead?
The Five Fundamentals of a Successful BOM Process
Get BOM Processes in Control Manufacturers who are ready to replace spreadsheets and email and get BOM processes under control can do so with reasonable effort. By focusing on the basics, they can make rapid improvements to productivity and reduce the impact of BOM-related errors. This leads to the question “What are the most important factors needed to improve BOM process?” We’ve identified five key areas that can easily be addressed and make a big impact on the business. Focus on the Fundamentals BOM Processes should be implemented and enabled in a way that ensures that they are:- Accurate
- Current
- Complete
- Clear
- Actionable
Lower the Barriers and Increase Collaboration with a Targeted Cloud Solution
One option is using a targeted cloud solution built to address the five BOM Process Fundamentals. Many companies are considering cloud software because it lowers the barriers to adopting new technology. The cloud also helps ensure that everyone access the latest data, and that data is digitally accessible instead of locked up in files or on drawings. As David Anderson of Verdetech Products shares, “We’re trying to do everything on the web so we have universal data access.”
1) Aim for Accuracy
Provide Accurate Data Downstream
Manufacturers rely on their BOM to let downstream operations know what they need to execute on. Clearly, accurate information is important or the wrong parts could be ordered or an incorrect revision could be produced.
Get Data from the Source
How can companies make sure their information is accurate? First, existing data should be gathered directly from the source whenever possible instead of manually reentered. For BOM information, this means pulling product structures and metadata from CAD in order to capture the engineer’s intent. Beyond initially collecting this data, it must be kept in sync as designs change.
Allow Visibility and Collaboration
Secondly, the information should be available and visible to people across different roles, including those in the supply chain. They should have the ability to review and provide input based on their perspective and expertise.
Avoid Duplicate BOM and Item Information
Finally, information should have a single master source. This means that part information shouldn’t be input on a BOM by BOM basis. Part data should come from an item master that can be kept up to date centrally. Then, that data should be dynamically supplied to the BOM. This keeps information up to date, helps encourage accuracy, reduces duplication, and allows companies to determine where parts are used.
Unfortunately, our research shows that about two-thirds of companies find data inconsistencies between systems at least on a weekly basis. Part data duplication on each BOM will, by its nature, become inaccurate. This doesn’t have to be the case. “We have a parts catalog for parts used over and over in different projects to create a single version of truth,” says Michael White of Digitalcarbon. “I just edit my catalog and bring part data into my BOMs.”
2) Keep Data Current
Keep BOMs Up to Date
Outdated data has lost its value, regardless of how accurate it may have been. BOM data needs to be up to date, and manufacturers have to be confident that they can access the current version when they need it. How can manufacturers ensure they keep their BOMs current? In addition, how they can know what their BOM looked like at a certain point in time if they have to go back to resolve issues?
Put BOMs Under Change Control
BOM data has to be kept under a managed change process. Change management is critical to tracking revisions and history. It ensures that people accessing the BOM to do their job can be assured that they are working on the latest design. As Verdetech Products’ David Anderson shares, “When someone asks what the product costs, I don’t have to worry if it’s current or not.”
Avoid Duplicating BOM Data in Emails
Of course, data currency is highly dependent on how the data is shared and accessed. Information sent in a spreadsheet or document via email is immediately outdated. As soon as BOM data is attached to an email, it is no longer under control and creates a risk that someone will access outdated information to guide their work, leading to errors. “Once you copy a BOM and send it out by email you lose control if you make an adjustment or a change,” explains Michael White of Digitalcarbon.
Keep Data Centralized and Accessible
Email is a helpful tool for alerts and notifications, but not as a place to store data. Email alerts should point to common data. In many cases, companies are turning to the cloud because it’s accessible inside and outside of the business and everyone will always get the same.
3) Manage Complete BOMs
Create Complete Product Definitions
Manufacturers rely on their BOMs to communicate the complete product composition, and do it in the right context. A BOM isn’t just a collection of parts or a CAD structure. While CAD integration is important, it doesn’t tell the whole story. As David Anderson of Verdetech Products explains, the BOM can communicate a rich amount of product data. “There’s a mass of information that’s all interrelated, it’s important to encapsulate that knowledge instead of going back through emails and trying to recreate it,” he says.
Manage BOM Relationships to Prevent Data Duplication
This information can include technical specifications like materials or commercial information like preferred suppliers. As mentioned earlier, it’s important not to duplicate information from the item master. In the same way, vendor information should come from a vendor database so the information can be validated, there’s no duplication, and Purchasing can find all references where the vendor is used.
Organize BOM Data by Role
BOM structures don’t always fit the right format for execution, and have to be modified to provide the right information. For example, companies may want to add non-modeled parts, consumables, tooling, or other information. Also, people have different perspectives and need different data to play their role. For example, a designer might model an assembly with all of its underlying parts, but Purchasing my view it as a single item from a supplier. In a similar way, third parties like suppliers may only require access rights to a subset of information. Data has to be organized for the intended user and match their execution needs.
Create New Knowledge
BOM data can be used to calculate new details, including cost rollups, weights, ordered quantities, and more. These calculations are very hard to accomplish in spreadsheets due to the way they are organized. BOM data can also provide a rich source of insight by applying business intelligence and machine learning. The key consideration, though, is that all of this information should be kept in context.
4) Communicate BOM Data Clearly
Focus on Clarity of Communication
A BOM isn’t valuable unless it can be easily understood by the people that need product information to do their jobs. Remember, it’s a communication tool. Too frequently, BOMs are large lists of numbers that mean very little to most people. How can companies ensure their BOMs are usable by others?
Create Personalized Data Views
First, different people need different views to make the BOM clear. It’s import to provide information that’s role and task appropriate. For example, people in the supply chain don’t know your part numbers and you probably only want to share a subset of information with them.
Present BOMs in a Visual Context
Second, information should be presented in a visual, intuitive way. Thumbnails of parts, particularly if they are 3D, are much more approachable than long lists of numbers. Multilevel views that allow you to expand, contract, flatten, and drill down to get more information or access CAD files are more valuable than complex colors and indentations in spreadsheets.
Make BOM Data Accessible Downstream Digitally
Lastly, data needs to be interpreted by other systems as well as people. BOM data should be accessible in a database, not locked up in a spreadsheet or CAD file.
5) Put BOM Data into Action
Put BOMs to Use
Information is important, but has to be put to use to provide value. How can manufacturers ensure that their data can be used to drive higher efficiency and reduce errors?
Extend BOM Knowledge to Support Downstream Processes
Effective BOM execution combines data with BOM processes. It creates an integrated process that connects design intent from Engineering with what’s needed to fulfill it downstream. BOM quantities aren’t for reference only, they should be accessible for procurement requirements and manufacturing quantity calculations. They should also be available for rollups like costs or material quantities to make decisions.
Leverage BOM Explosions for Procurement and Production Planning
A BOM solution should also allow BOM explosions to help plan production and communicate demand to suppliers. It should share that information with an ERP system if available.
Consider Simpler Solutions
Some solutions are blurring the lines between BOM definition and execution by supporting additional BOM-related tasks like orders and. These solutions are worth a look, can provide value with fewer barriers to adoption, and can serve as a foundation to grow from at the point the company is ready for more formal systems like PDM, PLM, and/or ERP.
Next Steps
Go Beyond the Status Quo to Prevent Mistakes Today’s BOM process status quo, frequently relying on inadequate technology like spreadsheets and email, leads to inefficiency, excess cost, mistakes, quality issues, and late orders. The consequences of poor processes, especially for a smaller company, can be significant. As David Anderson of Verdetech Products shares, “Sometimes you get away with things by luck, but a major problem could kill a company.” It’s time for companies to raise the bar on BOM data and processes.
Take Advantage of Performance Improvements
Effective BOM management creates a cohesive process that connects everything from design to purchase orders to production. It goes further to provide the right information, including historical data, to resolve service issues. An effective process leverages a wealth of information in context, including CAD, items, and vendors, without duplicating data or allowing it to be shared without control.
Get Started
For many companies, implementing traditional systems may feel too cumbersome. But that doesn’t mean they can’t improve. Manufacturers can focus on the five identified opportunities to improve BOM processes and improve performance by using lighter weight, targeted cloud solutions. Cloud software fosters collaboration and comes with lower barriers to adoption. These systems can help manufacturers take a big step in the right direction and provide room to grow in the future. It’s time to get started, start small, and incrementally improve BOM processes to reduce errors and improve performance.
Acknowledgments
About the Author Jim is a recognized expert in enterprise software for manufacturers with over 25 years of experience in application software, management consulting, and research. He has extensive knowledge on how industrial companies use product innovation, product development, engineering, and other enterprise solutions to improve business performance. Jim is actively researching the value of improving product innovation and operational performance through digitalization. [post_title] => The Five Basics of Effective BOM Processes (eBook) [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => billofmaterials-management [to_ping] => [pinged] => [post_modified] => 2022-11-14 22:28:16 [post_modified_gmt] => 2022-11-15 03:28:16 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=7823 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 1 [filter] => raw ) [13] => WP_Post Object ( [ID] => 7799 [post_author] => 2572 [post_date] => 2019-05-01 14:32:36 [post_date_gmt] => 2019-05-01 18:32:36 [post_content] =>
Imagine what you could do if you could get almost a third of your time back? In a guest post on the Sodius Willert blog, Michelle Boucher shares research on how much engineering time is wasted on non-value added work and explains what you can do.
Focus on the Work You Enjoy
As an engineer, what gets you excited about your job? For most, it’s getting to work on really cool projects and innovating. Unfortunately, a good chunk of your time is wasted on other things, taking you away from the work you enjoy doing and the work that adds value for your company.How Do You Limit Non-Value Added Work?
Research from Tech-Clarity’s Reducing Non-Value Added Work in Engineering reveals that engineers waste a startling 32% on non-value added work. That’s a lot of lost opportunity. Imagine what you could do if you could get almost a third of your time back? Much of this non-value added work is related to the many manual tasks associated with managing, sharing, and finding data. Data tends to be stored in multiple places, so there is no single source of truth.
Without a single source of truth, there is no traceability across the data. It then becomes practically impossible to identify the impact of an update to requirements, new design work, or changes to other parts of the design. Without traceability, changes can not automatically propagate across all product data. Instead, changes and updates become a very manual, if not impossible, process to identify everything that is impacted and update it. This is further complicated if the same data is located in multiple places. The situation creates a significant risk for outdated and conflicting data. Unfortunately, this costs the company in numerous ways, which we will explore further.
The Cost of Outdated Information
When design work is based on outdated information, error will be inevitable. These errors result in costly rework and redesign. Wasting even more time to correct these problems means poor efficiency which can delay time to market. As the design nears completion, there are fewer options to fix problems, so errors become much more expensive and time consuming to fix. Plus, with limited options, solutions may be less than ideal, which will hurt product quality or drive up cost. Of course, if problems are missed entirely, there will be even bigger quality problems in the field. The combination of poor quality, higher cost, and late to market all hurt competitiveness which can reduce revenue opportunities. This problem gets even worse when multiple engineering disciplines are involved. When products integrate mechanical components, electronics, and embedded software, there are inherent silos. Continue to the Sodius Willert blog for the full post. [post_title] => How to Avoid Non-Value Added Work for Engineers (guest post) [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => non-value-added-work [to_ping] => [pinged] => [post_modified] => 2022-11-14 22:25:36 [post_modified_gmt] => 2022-11-15 03:25:36 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=7799 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [14] => WP_Post Object ( [ID] => 7516 [post_author] => 2572 [post_date] => 2019-04-25 11:30:48 [post_date_gmt] => 2019-04-25 15:30:48 [post_content] =>How do you navigate complex, omnichannel environments and manage multiple sources of data to make the best decisions? Can predictive analytics help?
Tech-Clarity’s Retail Analytics Buyer's Guide explains how predictive analytics provide better visibility across your retail business so that you can make better decisions to become more competitive. As the retail industry faces significant disruption, new approaches are required to survive. With volatile markets and fierce competition, the right decisions are critical to survival. Unfortunately, complex omnichannel environments, global supply chains, and dynamic development teams make it practically impossible to get timely visibility into the business. Even if you can, will you have confidence in your decisions? With the right predicative analytics solution, you can overcome these challenges, but only if you select the right technology. The research identifies eight capabilities to look for in a predicative analytics solution. These capabilities will help you make better decisions about your retail business.
Click here for the full eBook, thank you to our sponsor PTC.
WHY ARE PREDICTIVE ANALYTICS CRITICAL FOR TODAY’S RETAILERS?
In the retail industry, you need to support a complex, global, omnichannel environment, while navigating a dynamic market filled with economic volatility. It is not easy, especially as consumers have become more empowered and demanding through social media and online resources. To be successful, you need to make fast decisions, identify opportunities, respond to changing trends, react to competitors, adjust to shifts in the supply chain, and more. It’s complex. In many cases, margins are so thin that missing a trend, failing to spot an opportunity, or making the wrong decision can significantly hurt profitability. A few weak seasons can be disastrous for a brand.

Making things even harder, the barriers to entry have dropped. It’s no longer enough to compete by becoming the biggest brand and leveraging scale. Online marketplaces have expanded the reach of start-ups and small companies. In many cases, the playing field has been leveled as resources that were only available to the largest companies are now available to everyone. This situation has further intensified the competition. Retail companies who can respond to market changes before their competitors will have the advantage.
To survive, retail companies must be nimble enough to react quickly, but they can only do that with the right insights. Information and knowledge are now competitive weapons and technology can be key to unleashing its potential. That knowledge comes from every aspect of the organization from business operations, product trends, supplier information, and more. This buyer’s guide reveals how retail companies can capitalize on their knowledge and uncovers eight capabilities that will help put the right technology in place to support them.
HOW DO PREDICTIVE ANALYTICS HELP?
The top challenges uncovered by research conducted by BOF and McKinsey reveal the importance of getting instant insights. The economic uncertainty related to events such as Brexit, a rise in protectionist policies in the US, a volatile stock market, and more can erode consumer confidence and make it even harder to predict buying trends. Key insights will help overcome some of this uncertainty. With online shopping and social media, consumers are more informed than ever, creating a need for retailers to know how they can best influence buying behavior. The right data, in context, will help. Merchandise needs to be at the right place at the right time while avoiding excess inventory. Retailers need to offer consumers the experiences that will keep them coming back, with the right products that reflect the latest trends. Again, analytics will guide those decisions.
SELECT THE RIGHT RETAIL PREDICTIVE ANALYTICS SOLUTION FOR YOUR NEEDS
By selecting the right software, you should get timely insights to help you bring the right products to market, optimize the management of supply chains, influence buying behavior and more. These needed insights will help you make smarter decisions which should lead to better operating margins
*This summary is an abbreviated version of the eBook and does not contain the full content. A link to download the full eBook is available above.
If you have difficulty obtaining a copy of the research, please contact us using the “Contact” link below.
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As our changing world impacts product design, how should CAD evolve? How can CAD support your efforts to adopt some of the latest technologies?
During the PTC on-demand virtual session, “The Renaissance of CAD: What's New, What's Now & What You Can Do With It” you will hear about some of the latest advancements in product design and how CAD has evolved to support them. Sessions include topics on IoT, generative design, simulation, additive manufacturing, and augmented reality.
During the simulation session, Tech-Clarity’s Michelle Boucher shares highlights from her recent research on simulation and how CAE can be a valuable tool for design engineers. Watch Michelle's session here. To read more about Michelle's research on simulation click here.
Watch all the sessions here.
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[post_content] => How can food and beverage companies use digitalization to dramatically increase flexibility, enhance consumer responsiveness, and improve productivity? This episode of Tech-Clarity TV, Revolutionizing Food and Beverage Production with the Industrial IoT and the Digital Twin, shares how food producers can leverage digital twins and the IoT to improve performance.
https://youtu.be/kGb6utklQwk
Transcript
The food and beverage industry is facing major disruption New competitors are adopting digital technologies and taking on the largest of companies, competing with unprecedented innovation and agility. Consumers are demanding more. To rise to the challenge, food and beverage plants need to increase flexibility while maintaining high productivity and compliance to ensure consumer confidence. The digital revolution has begun. Food companies have to leverage digital tools including the Internet of Things, the Digital Twin, the Cloud and Analytics to drive agility and consumer responsiveness. Using the IoT, digital food and beverage companies tap into data from a variety of sources and use analytics to gain deep consumer insights. Then, they quickly reformulate digital recipes to respond to trends. They leverage plant automation to capitalize on changing preferences. Digitalization allows food and beverage companies to get products that consumers want to market faster than the competition. But leading companies go beyond just internal agility and responsiveness. They use the IoT to gain advanced insights to optimize recipes and production schedules. The digital plant acts as one with their supply chain to rapidly adjust to changing supply and demand. Digital food and beverage companies also turn to digitalization to drive higher productivity. They reduce downtime by monitoring equipment health and servicing equipment before it fails using the Industrial IoT and predictive maintenance. They improve yields by identifying and correcting production issues in real-time. They use the IoT and analytics to benchmark performance to identity improvement opportunities. They use the digital twin of their plant to simulate and validate the impact of changing equipment. They quickly deploy new recipes, packaging and equipment using virtual commissioning. Finally, they identify opportunities to more accurately simulate production based on IoT data and a closed loop digital twin to better reflect reality and improve optimization using real-world information. Digitalization helps food and beverage companies improve throughput, increase uptime, decrease cost, improve quality and support high levels of traceability and compliance. It enables companies to raise the bar on innovation and agility without compromising productivity, cost or quality. The time has come for food and beverage plants to digitalize in order to survive in the digital age. To learn how, watch the rest of our video series on digitalization in the food & beverage industry. And learn more from our sponsor, Siemens PLM, a leader in digitalization for the food & beverage industry. [post_title] => IoT, Industrial IoT, and Digital Twins in Food & Beverage Production (animation) [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => iot-twin-foodbeverage [to_ping] => [pinged] => [post_modified] => 2022-12-02 15:05:38 [post_modified_gmt] => 2022-12-02 20:05:38 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=7752 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [17] => WP_Post Object ( [ID] => 7580 [post_author] => 2572 [post_date] => 2019-04-03 14:25:01 [post_date_gmt] => 2019-04-03 18:25:01 [post_content] =>How can you get the quickest return on your investments in technology?
As we look ahead to the coming decade, technology will become increasingly critical for your company to stay competitive. New technology can include CAD, CAE, PLM, 3D printing, IoT, and more. However, for that technology to work for your business, your implementation must be successful. With a new technology, often it is the cultural changes that can derail the project. Starting with a plan to overcome challenges like this can be the most important part of a successful implementation. Tech-Clarity’s Ten Practices to Successfully Implement Technology shares 10 best practices to support the implementation and adoption of new technology so that you can get the expected return on your technology investments as quickly as possible.
Please enjoy the summary* below.
For the full eBook, please visit our sponsor SOLIDWORKS (free of charge, registration required).
HOW CAN YOU GET THE MOST FROM YOUR TECHNOLOGY INVESTMENTS?
Staying competitive in today’s global market means developing exceptional products that are innovative, high quality, and cost-effective. With so much to consider, how can you get ahead? For many, technology, including software tools, is the answer. Technology investments can help you grow your business, expand your customer base, and extend your services. With great software tools, you can accomplish more than you thought possible. Unfortunately, ignoring opportunities for improvement can stagnate the business, which can eventually lead to lost market share.
The key is selecting the right technology solution and successfully adopting it. This eBook identifies best practices for successful technology adoption to position your company for success for the next decade.

TECHNOLOGY SUPPORTS INNOVATION EFFORTS
Outsource vs. Internal Development?
Innovation often requires new skills. Many find they lack the internal expertise to take advantage of new materials, use the latest manufacturing techniques, support connectivity, or benefit from other industry advancements. When faced with this challenge, you can outsource or try to develop the skills internally. Regardless of which option you choose, technology will make it easier.
Support Outsourcing with Technology
For some, outsourcing can be a great option as a way to tap into expertise that you lack. When outsourcing, technology can ensure good collaboration, support communication, keep design data in sync, and protect intellectual property. As an example, cloud solutions can offer a platform to share data with third parties in a secure manner.
Technology Lowers Internal Development Cost
For other companies, especially smaller businesses, the overhead associated with outsourcing may be too much. It takes time to familiarize a third party with your product lines, manage quality, and coordinate changes, especially for highly engineered products. In these cases, it may be easier to do everything in-house. Again, technology can make that easier with software tools that have embedded intelligence to guide the design or manufacturing process.
RECOMMENDATIONS AND NEXT STEPS
Technology can have a significantly impact on your business in a positive way. It can be the key to help you expand, grow, and evolve your business. However, as good as the technology may be, it will only help your company if you take the right steps to ensure the adoption is successful.
The following checklist will help you achieve success:
- Determine Your Business Needs Upfront
- Be Open to Change
- Keep the Focus on Customers
- Consider Vision and Future Needs
- Keep it Simple
- Automate Tedious Workflows
- Manage Scope
- Manage the Role of Team Members
- Overcome the Resistance to Change
- Provide Training
- Establish Success Factors
By following these ten recommendations, your company will be better positioned to successfully adopt technology and realize the expected ROI even faster.
*This summary is an abbreviated version of the eBook and does not contain the full content. A link to download the full eBook is available above.
If you have difficulty obtaining a copy of the research, please contact us using the “Contact” link below.
[post_title] => Ten Practices to Successfully Implement Technology (eBook) [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => ten-practices-to-successfully-implement-technology-ebook [to_ping] => [pinged] => [post_modified] => 2022-11-14 22:28:16 [post_modified_gmt] => 2022-11-15 03:28:16 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=7580 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [18] => WP_Post Object ( [ID] => 7670 [post_author] => 2 [post_date] => 2019-04-01 09:44:21 [post_date_gmt] => 2019-04-01 13:44:21 [post_content] => How have manufacturers' opinions on using the cloud to support product innovation, product development, and engineering changed? How does that impact cloud adoption? Read the guest post in full in the Digital Transformation section of the Siemens PLM Community blog. Jim Brown recently shared a guest post on the Siemens' blog offering our experience on cloud adoption and starts a discussion about the variety of benefits that engineering software on the cloud offers. The post includes information from our prior research on using cloud for PLM, including this flowchart for companies to use when considering their cloud strategy.
Times have changed. We've seen a shift from companies questioning if they should use the cloud to asking "why not?" use the cloud. Many viewed slower cloud adoption for PLM and other engineering solutions as a reluctance to put IP in the cloud, but our research and experience point to another reason. The solutions available on the cloud versus more traditional deployments simply did not offer equivalent capabilities. Now, we're seeing a different mindset.
Our conclusion is that the appetite for cloud solutions is increasing. At the same time, options are expanding to include more traditional solutions, along with their deep functionality, in a cloud offering. It’s time for more companies to take a look.
[post_title] => Why Not Adopt Cloud for Product Innovation and Engineering? (guest post)
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How do you empower engineers to design the best products possible?
Research from Tech-Clarity’s Revolutionizing Simulation For Design Engineers research report finds that design engineers lack confidence in design decisions 28% of the time. The research identifies the most common ways engineers deal with this uncertainty, its impact, and how to improve confidence. This research study, based on a survey of 195 companies, examines the design process and identifies top challenges that hold engineers back. The report reveals how to empower engineers with insight to improve product quality, lower cost, and accelerate time-to-market, all while developing more innovative products and the role that CAE can play.
Please enjoy the summary* below.
For the full research report, please visit our sponsor PTC (free of charge, registration required).
ENGINEERING DECISIONS CAN MAKE OR BREAK YOUR PRODUCTS
How do you empower engineers to design the best products possible?
Engineers want to design great products. Unfortunately, factors like increasing product complexity, competing design criteria, and knowing how design decisions impact other parts of the design make it hard. On top of this, ever-shrinking timelines mean engineers have their work cut out for them. Yet, exceptional engineering has become critical to success in today’s competitive global market.
WHAT’S MOST IMPORTANT FOR YOUR PRODUCT’S MARKET SUCCESS?

Product Quality
As companies face mounting pressure from global competitors, engineering criteria have become essential to competitively differentiate products. In fact, 80% of survey respondents believe that product quality is the most important product attribute to keep products competitive (see graph). Reliability and cost come next. This indicates customers have high expectations for quality and durability but don’t want to overpay. To be successful, companies should balance these criteria.
Engineering Decisions Are Critical – and Not Easy
Requirements for quality, reliability, and cost often conflict so balancing them is no small feat. Unfortunately, product complexity makes it hard for engineers to know the full impact of each design decision. Indeed, 76% of survey respondents rate design decisions that impact product competitiveness as ‘somewhat hard’ to ‘extremely difficult.’ This leads many engineers to overengineer, which unfortunately drives up cost.
Companies who can make this decision process easier will have an advantage.

RECOMMENDATIONS TO IMPROVE ENGINEERING DECISIONS
To help improve engineering decisions, Tech-Clarity offers the following recommendations:
- Empower design engineers with simulation tools to help guide their decisions.
- Use simulation as early as possible during concept and design.
- Rely on simulation as a design tool to optimize the design and provide directional guidance.
- Consider new approaches to simulation that are tailored for design engineers and make setting up an analysis easier.
- Look for a simulation solution that can offer instant results.
*This summary is an abbreviated version of the report and does not contain the full content. A link to download the full report is available above.
If you have difficulty obtaining a copy of the research, please contact us using the “Contact” link below.
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What is the impact of disruptive industry forces like digital transformation and sustainability on long-term business success, and how are companies responding? Companies are facing pressure from all angles, threatening their long-term survival and success. Business is digitalizing and customers are demanding more. The workforce is aging. Natural resources are increasingly constrained as populations grow and urbanize. New technologies like artificial intelligence and the IoT are creating opportunities but upsetting the status quo. As if that’s not enough to deal with, political uncertainty is the new reality.
What sustainability pressures are executives worried about and what strategies are they adopting in response? We surveyed over 150 executives from companies with greater than 1,000 employees to find out.
Please enjoy the summary below. For the full Executive Strategies for Long-Term Business Success research, please visit our sponsor Dassault Systemes (registration required).
Table of Contents
- Disruptive Forces Threaten Business Sustainability
- Business Risk and Disruption are on the Rise
- What Drives Long-term Company Success?
- What’s Driving Company Strategy?
- Innovation Basics and Beyond Lead to Success
- Workforce Development is Critical to Success
- Economic, Environmental, and Social Sustainability
- Executives Must Lead Their Companies to Succeed
- Execution Faces a Variety of Barriers
- Sustainability has Unique Challenges
- Managing Change is a Multi-Faceted Issue
- Conclusions and Next Steps
- About the Research
- Acknowledgments
Business Risk and Disruption are on the Rise
Market Reinvention is Increasing Surveyed executives share that their markets have experienced increased business risk and disruption over the last five years. About three-quarters of companies say this turmoil has increased, with almost one-quarter saying it has increased “significantly.”
Larger Companies Face Greater Risk
Larger companies are experiencing greater challenges. A full one-half of companies with over 10,000 employees say that risk and disruption have increased “significantly.” The status quo is changing, and market leaders are at risk of disruption while challengers have great opportunities.
Few are Exempt from the Impact
Today’s industrial revolution is extremely broad. Out of all of the companies surveyed, only 4% said that this market upheaval has decreased. No participants indicate it has decreased “significantly.”
It’s Time to Act
Executives have to sustain business performance despite these conditions – or better yet find a way to capitalize on the disruption. Let’s take a deeper look at the business sustainability challenges companies face and what they’re doing about it.
What’s Driving Company Strategy?
Executives are Looking to the Future
With disruption and competing needs, what do companies take into consideration when developing and executing their business strategies? The most commonly reported corporate strategy and initiatives drivers are new market opportunities and long-term growth objectives. In fact, only 13% of respondents indicate that short-term profits influence their direction, reflecting a longer-term horizon for these decisions.
Companies Respond to Outside Pressure
Executives also report that consumer pressure and non-governmental organization (NGO) reporting influence their strategy decisions, as do financial market perception and regulation.
Although the overall results show only about one one-third of respondents say regulation impacts strategy, C-Level execs are 40% more likely to view governmental regulations as a driver than VPs and Directors. In addition, companies with over 5,000 employees are almost twice as likely to drive strategy based on government regulation.
Regulation and Oversight Drive Sustainability
Corporate responsibility and environmental issues do not directly make the list of top strategic influences, but other driving forces such as consumer pressure, NGO reporting, and regulation influence these important issues indirectly.
The influences vary by regions. For example, North America is more focused on consumer pressure and regulation than the average across regions, while Europe is more focused on NGO reporting. These factors likely drive these markets toward sustainability.
Conclusions and Next Steps
Industry Risk and Disruption Demand Change
Global markets are undergoing major disruption. Companies have to adapt to survive and prosper into the future. Current shifts in business models, technology, the environment, and socio-economic factors can challenge leaders and provide challengers the opportunity to become a disruptor. One thing is certain, the status quo is changing rapidly.
Companies are Choosing their Sustainability Initiatives
Executives are identifying and prioritizing the actions they believe will take their businesses into the future. Today, companies are focused most commonly on economic sustainability, with a strong emphasis on product and service innovation. They are keenly focused on making the transition to digital business models in order to stand the test of time.
At the same time, they recognize the need for greater environmental and social responsibility, particularly reacting to regulatory demands. In addition, customer perceptions and NGO reporting are likely encouraging sustainable approaches.
Finally, executives recognize they need to invest in the workforce of the future. This includes getting the most out of existing resources as well as attracting and retaining new talent. In order to gain value from their human resources, they are also focused on the ability to capture company knowledge and know-how.
Putting Initiatives into Action
There are numerous initiatives underway, each with their own level of executive sponsorship, funding, enterprise change management, and technology support. Companies have to take on the challenge of prioritizing and supporting each of these initiatives in order to create long-term, sustainable business success. In particular, surveyed companies would benefit from more attention to enabling enterprise technology.
*This summary is an abbreviated version of the research and does not contain the full content. A link to download the full report is available above.
If you have difficulty obtaining a copy of the report, please contact us using the "Contact" link below.
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