Making the value of technology clear
Putting Data into Context
The top data management challenges, however, go beyond managing files. They include change management and managing configurations and BOMs. These processes require more than controlling files, they demand the ability to put the data into a product context. This involves managing the complex relationships between parts and assemblies to accurately manage and communicate product details.
NPD Extends Challenges
Beyond core data management challenges, companies struggle when supporting new product development (NPD). NPD crosses both departmental and company boundaries, raising the stakes on data management. Not surprisingly, the top challenges stem from collaborating with others across the business and the supply chain, and managing designs along with their associated NPD projects. Challenges also include extending designs to incorporate manufacturing information and supporting cross-departmental processes.
Companies Routinely Miss NPD Targets
The impacts of these challenges also include missed deadlines and budgets. About two-thirds of companies routinely miss design due dates, project/program budgets, and time to market goals by more than 5%. About one-third miss quality targets at that level. Manufacturers lose time and money because of inadequate data management.
Get Started and Grow Value
PDM offers an opportunity for companies to get started and grow. Our research, “The Facts About Managing Product Data,” details that it doesn’t have to take a lot of time and money to implement PDM. Further, it shows that starting small doesn’t seem to hamper performance, an almost identical percentage of Top Performers start with limited scope as do Others.
Based on these findings, we recommend that companies start small, gain value, and then extend PDM scope and benefits over time.
*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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[post_content] => Do you worry about overheating in your product designs? Are you sure you have specified the right pump for your system? Do you make design decisions related to air flow, heat transfer, pressure, and other related physical phenomena?
During this on-demand webinar titled, "Are you using CFD during design?" Tech-Clarity's Michelle Boucher and Chris Watson from Siemens explain different ways Computational Fluid Dynamics (CFD) may help you develop even better designs. During the webinar, you will learn:
[post_title] => CFD webinar : Are you using CFD during design?
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How can manufacturers grow profits by designing, selling and producing personalized products? Manufacturers have significantly increased the level of personalization in their products over the past five years, and customization will accelerate over the next five. Why? Companies across the manufacturing industries recognize that tailoring products drives increased differentiation, higher sales, and better margins. How can manufacturers take advantage of this trend to drive better top line growth and bottom line profits? We surveyed 285 companies to find out. Let’s take a look!
Please enjoy the summary below. For the full Growing Product by Personalizing Products eBook, visit our sponsor SolidWorks (registration required).
Customization is Compelling
People have been talking about mass personalization, lot sizes of one, customization, and other configuration strategies for years. Why does this strategy continue to show up in corporate agendas? It’s likely a natural reaction to limited choices dictated by mass production and cost reduction. But at a more basic level, it’s a simple matter of money.
We asked survey respondents to share the benefits their companies get from selling customized products. The results show that customization helps drive growth and profitability. The most commonly mentioned benefits, increasing sales and differentiating from competitors, grow the top line. But the benefits also extend to driving higher bottom line profitability. About one-half of respondents report they increase profit margins by personalizing.
Additional Goals
There are other drivers as well. For example, there are industries where customization is simply a necessity. In these cases, products typically need to fit into unique customer situations, like fitting a piece of equipment into existing plant infrastructure. Another example is that 84% of Aerospace & Defense respondents say configuration is an industry necessity, most likely to meet specific customer performance specifications.
Consumer-oriented companies, including Apparel / Footwear and Consumer Products, also report benefits related to consumer experience. In addition to increasing sales through customization, both are more likely than other industries to benefit from gaining a “cool factor” and offering a compelling website experience from personalization.
Almost three-quarters of surveyed companies say that the level of customization has increased over the last five years. Very few companies, only 3%, say it had decreased. Looking to the next five years we see a similar picture. In fact, about one-half say that customization will increase “significantly” over that time period. As we depict in the graph, it’s important to remember that future growth is in addition to the increases they’ve already seen!
Consumer Industries Growing Faster
Consumer-oriented companies are experiencing the greatest increases. Over 40% of Apparel / Footwear and Consumer Products companies have grown customization significantly, with almost three-quarters expecting significant growth! High Tech / Electronics also expects to grow more than average over the next five years. Personalization hasn’t reached its peak!
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).
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.
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.
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).
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.
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.
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.
But more often, a solution that fulfilled company needs at a certain point in time just isn’t enough anymore due to:
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.
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 *
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.
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.
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.
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.
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.
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.
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).
Table of Contents*
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.
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.
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.
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:
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.
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.
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.
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.
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.
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.
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.
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.
Based on this research and our experience, we recommend that Automotive companies:
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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:
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.
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.
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:
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.
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.
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.
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:
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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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?
Successful BOM communication across Engineering, Purchasing and Manufacturing:
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?
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.”
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.”
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
How do top performing companies better leverage Product Data Management to hit their product development targets? We surveyed over 165 manufacturers and gained some telling insights. Our research finds that the current state of design data management continues to yield too many problems, too much wasted time, and missed product development targets. Top Performing companies, on other hand, spend less non-value-added time on data management and are better able to hit their product development goals. How do these Top Performing manufacturers improve product development performance and spend less time managing data? Let's find out.
Please enjoy the summary below. For the full report, please visit our sponsor Autodesk (registration required).
Putting Data into Context
The top data management challenges, however, go beyond managing files. They include change management and managing configurations and BOMs. These processes require more than controlling files, they demand the ability to put the data into a product context. This involves managing the complex relationships between parts and assemblies to accurately manage and communicate product details.
NPD Extends Challenges
Beyond core data management challenges, companies struggle when supporting new product development (NPD). NPD crosses both departmental and company boundaries, raising the stakes on data management. Not surprisingly, the top challenges stem from collaborating with others across the business and the supply chain, and managing designs along with their associated NPD projects. Challenges also include extending designs to incorporate manufacturing information and supporting cross-departmental processes.
Companies Routinely Miss NPD Targets
The impacts of these challenges also include missed deadlines and budgets. About two-thirds of companies routinely miss design due dates, project/program budgets, and time to market goals by more than 5%. About one-third miss quality targets at that level. Manufacturers lose time and money because of inadequate data management.
Get Started and Grow Value
PDM offers an opportunity for companies to get started and grow. Our research, “The Facts About Managing Product Data,” details that it doesn’t have to take a lot of time and money to implement PDM. Further, it shows that starting small doesn’t seem to hamper performance, an almost identical percentage of Top Performers start with limited scope as do Others.
Based on these findings, we recommend that companies start small, gain value, and then extend PDM scope and benefits over time.
*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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