The Four Dimensions of PLM ExpansionPLM implementations must go beyond the basics to support operational excellence. We’ll discuss four important ways that PLM has expanded in order to support operational excellence:
Process: Improving processes beyond basic revision control and release to manufacturing
People: Including more people and departments beyond Engineering, including partners, the supply chain, and customers
Lifecycle: Supporting upstream and downstream capabilities beyond design
Product: Expanding beyond product design to a full product definition
Each of these expands the value of PLM, supports more mature product innovation practices, and helps make better use of product information throughout the enterprise. Together, they support the pursuit of operational excellence.
Expanding Communication with PLM
Another valuable dimension of PLM expansion is by supporting broader communication and collaboration between Engineering and the rest of the business. This can be looked at in two directions:
Inbound: Enabling engineers to better use information coming out of other business areas such as Procurement, Quality, Manufacturing, and others to design for operational excellence
Outbound: Making better use of information coming out of Engineering in other areas of business such as Marketing, Sales, Service, and more to support broader product innovation, development, manufacturing, and support process to drive operational efficiency
"To start, PLM supports document management, design control, and training. That sets the foundation for product development process compliance. Then, you can build on that to support operational needs like NCMR, suppliers, CAPA, change control, and complaint handling as you go to the commercial phase." - Scott King, Director, IRIDEX CORPORATION
"We started with ECOs, took some small bites, then expanded it more broadly by implementing it with supply chain, customers, drawings, orders, contract tracking, and source tracking. They lend themselves perfectly to PLM." - John Baumann, CEO, THINGAP, INC.
Conclusions and Next Steps
Moving Toward Operational Excellence
Manufacturers have to recognize the need for innovation, agility, and operational improvement. Business risk and disruption are threatening profitability and survival for many businesses. Products and markets have changed, demanding more.
Recognize the New Role of the Engineer
To support more supply-chain centric, operationally-focused product development processes the role of engineers has changed. They must be able to access a wider array of information in order to make broader product-related decisions. This, in turn, changes the requirements for the PLM systems that support them.
Choose the Right PLM Solution to Drive Operational ExcellenceThe four dimensions of PLM expansion provide a framework to understand what’s needed to drive operational excellence. Traditional, Engineering-centric PLM systems are not sufficient for fast-moving industries like high-tech and medical devices. Companies in these industries need a PLM solution built for the enterprise and the supply chain.
Lastly, manufacturers must get a solution that delivers on the promise of PLM. Systems selections and implementations should be driven by cross-functional teams that represent all aspects that impact product profitability. Selection requirements should span the enterprise and focus on how the system supports the new role of engineers and product developers. This is the way that companies can ensure that they select the right PLM systems to drive operational excellence.
*This summary is an abbreviated version of the research and does not contain the full content. For the full research, please visit our sponsor QuadRite (registration required).If you have difficulty obtaining a copy of the report, please contact us.
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[post_content] => What does future-proof manufacturing plant floor software look like? Is it possible to have all the flexibility and choices each site needs and still adhere to enterprise standards? Yes; find out what modern MES architecture can promise for this uncertain era. Listen to the recording of this fireside chat to find out:
Why plant floor software must reach beyond functional fit into MES architecture
How to be ready for anything: M&A, new plants, new regulations, moving products between plants
The benefits of easily moving software to public or private cloud, on-prem, or hybrid
Why containerization, orchestration, DevOps, and one-click deployment from a central CoE can avoid the MES trap of fit that fades over the years
Tech-Clarity’s Julie Fraser will be hosting a panel including Luis Ponte, Product Development Director of Critical Manufacturing, Ralph Loura the CIO and Peter Brostowicz the VP IT Applications and Data from skyrocketing designer and manufacturer of innovative optical and photonic products Lumentum. Bring your questions on IT approaches innovative manufacturers are taking to continue disrupting their markets by being more resilient, responsive, and agile than others.
[post_title] => MES Architecture for More Resilient, Responsive, and Agile Manufacturing (webcast)
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[post_content] => Tech transfer is critical to competitiveness in the life sciences industry. Yet most companies still rely on document-based, manual, people-dependent processes to transfer analytical and manufacturing methods. How can life sciences companies digitally transform tech transfer to improve efficiency and success?Join this webcast to hear the benefits of:
Transitioning to a data-driven process
Digitalizing tech transfer data and processes
Taking a holistic approach to product data modeling
Register for this Fierce Biotech webcast featuring speakers from Tech-Clarity and Dassault Systemes BIOVIA.
For related research, please read our Driving Tech Transfer Performance in Life Sciences eBook.
Speakers:Jim BrownPresidentDigital Innovation Research Tech-ClarityDr. Daniela JansenDirector of Product Marketing at Dassault Systèmes BIOVIA
[post_title] => Improve Tech Transfer with Digital Transformation (webcast)
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[post_content] => Can improving design data management practices improve innovation and product development performance? We surveyed 131 companies to understand how they manage CAD files, bills of material, and other product-related information to find out.
Please enjoy the summary below.* For the full report, please visit our sponsor Siemens (registration required).
For related research, please see two of our prior surveys on design data management best practices to see what’s changed: Design Data Management Maturity Improves Profitability, Analyzing Best Practices for Managing Designs from 2017 and Best Practices for Managing Design Data from 2012.
Table of Contents
Executive Overview
The Importance of Effective Data Management
Data Management Must Address Today's Challenges
Data Management Challenges Reduce Productivity
Evaluating the Practices of the Top Performers
Data Management Practices of the Top Performers
Enabling Top Performing Product Development
Top Performers are More Likely to Embrace the Cloud
Conclusions and Recommendations
About the Research
Acknowledgments
Leveraging Data Management to Enable Product Development
Analyzing Data Management Practices for Successful Product Development
How do design data management practices impact product development performance? We surveyed 131 companies that design, engineer, and/or manufacture products to understand how they manage design data like CAD files, bills of material, and other product-related information to find out. We conducted this study as a follow-up to our previous studies to understand what has changed over time.
Executive Overview
Survey ApproachTech-Clarity research shows that effective data management helps companies design innovative, high-quality products quickly and efficiently. This report shows how data management best practices relate to business performance based on 131 responses to a web-based data management survey.
Researchers benchmarked participating companies on their performance related to quality, innovation, product development speed, and efficiency. Survey analysis compared companies with the highest performance in these important product development metrics with their data management approaches.
Top Performers Have More Effective Data Management
The data shows that Top Performing product developers are more likely to have very effective data management capabilities. Top Performers are more likely to be able to:
Find the data they need
Share it with others
Manage their design projects
Provide the correct data to manufacturing
The results confirm that data management continues to be an important enabler to design and develop profitable products.
Top Performers use the Cloud and Advanced Data Management Techniques
The data also shows that Top Performers take a different approach to data management. Top Performers, on average:
Are more likely to use advanced features of their data management systems beyond simply storing and controlling CAD files
Are 70% more likely to share data using the cloud for design and/or engineering
Have 3 times as many people using their PLM system*
Are 4.3 times as likely to have third parties such as customers and suppliers use their PLM systems *
The findings show that managing design data by itself is no longer enough to excel in product development. Companies must collaborate more broadly and do more with their product data to drive higher levels of product development performance. The results also show a strong correlation between product development success and the emerging use of the cloud for sharing product data.
*Of those that use PLM
Conclusions and Recommendations
Conclusions
Effective design data management fundamentals enable better product development performance. The data shows, however, that companies face significant challenges in managing their critical design data due to product complexity. These challenges can lead to quality problems and inefficiency, and prevent companies from taking advantage of strategic opportunities such as design reuse. Addressing these challenges with effective design data management practices and technology leads to significant business advantages, including improved efficiency, quality, and time to market.
Top Performers are more effective at data management and take a more collaborative approach to managing designs. To enable this, Top Performers leverage more mature use of their design data management systems. The fundamentals of design data management, supported by an effective data management solution, provide significant business value and provide a foundation that can be expanded on for future benefits. But to differentiate today, companies must go beyond controlling and accessing data.
Recommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations:
Ensure that your business has the basic fundamentals of data management in place, but expand the maturity of data management usage to drive higher value
Improve design data management effectiveness to improve business performance in product design and development
Explore the use of cloud collaboration to improve data management and product development performance
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full report, please visit our sponsor Siemens (registration required).If you have difficulty obtaining a copy of the research, please contact us.
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[post_content] => Is it time to change the way manufacturing processes are developed? Products have dramatically increased in complexity and time-to-market expectations continue to shrink. Is a virtual, 3D based manufacturing engineering transformation the way for manufacturing engineers to ramp up products quicky without compromising quality? Join Tech-Clarity’s Jim Brown and Dassault SystèmesDelmia’s Strategic Business Development Director Adrian Wood in a panel discussion investigating the need and potential to evolve the way manufacturing processes are developed.Register now for the first of a three-part webinar series.
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[post_content] => Is PLM ready to support the future of the digital consumer packaged goods industry? Join an interactive panel discussion featuring:
Jim will share findings from his latest research on the State of PLM in CPG to frame the discussion. Register for this Kalypso hosted webcast by visiting the Kalypso Next Generation of PLM page and scrolling down to Register Now. You can also download the related research from that page, or learn more about the State of PLM in CPG 2022 research on our site.
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[post_content] => Jim Brown is hosting a panel of experts to discuss the challenges, benefits, and approaches for deploying simulation technology as a part of a digital twin initiative. Join the fourth interactive discussion in the AMC Bridge Executive Series on Tuesday, April 26, 2022, at 12:30 p.m. EST. Speakers:
Register now to hear insights from this executive panel, brought to you by AMC Bridge.
To view past webcasts, please visit:
https://tech-clarity.com/aec-digital-twin-webcast/10947
https://tech-clarity.com/cloud-engineering-software-webcast/10541
https://tech-clarity.com/industrial-additive-webcast/10420
[post_title] => The Role of Simulation Technology in Digital Twins (webcast)
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[post_content] => Heavy equipment is becoming more connected, autonomous, smart, and electrified. Given the increased complexity, how can manufacturers optimize equipment performance without compromising time-to-market? Learn how companies can increase performance engineering maturity to develop more innovative, high-performance equipment with fewer prototypes and lower costs. Register for this live Siemens webcast on April 26th at 11am to learn the four ways equipment manufacturers can drive higher performance engineering maturity.
For related research, please read our Increasing Performance Engineering MaturityeBook.
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[post_content] => How much better would your products be if you could improve engineering productivity by reducing engineering time wasters? Engineers regularly lose productivity to non-value-add tasks that not only rob them of their ability to innovate, but also threaten their company’s ability to compete, differentiate, and grow. Imagine the potential of identifying and removing the most common non-value-add activities engineers face and empowering them to focus on better products. This research, The Business Value of Reducing Engineering Time Wasters, examines how engineers spend their time, where they lose productivity, and the impact on the business. It then identifies solutions and approaches to reduce time wasters. Based on a survey of 228 manufacturers, it focuses on smaller and medium-sized companies and looks at the challenges and opportunities from their perspective.
Please enjoy the summary* below. For the full research, please visit our sponsor Siemens (registration required).
Table of Contents
Executive Summary
Product Development Is Critical to Business Strategies
The Time Wasters
Implications of Time Wasters to the Business
A Solution to Avoid Time Wasters
Defining Product Complexity
Business Value from PLM
Extending PLM Use Results in Greater Satisfaction
How Companies implement PLM
Additional Values Due to the Cloud
Conclusions
Recommendations
About the Research
Acknowledgments
Executive Summary
Engineers Impact Business Success
Exceptional products are critical to success, regardless of whether a company's business strategy is to grow or improve margins. Likewise, engineers are crucial to ensuring products have what it takes to succeed in the market. Therefore, empowering engineers is key to the successful execution of business strategies.
Too Many Time Wasters
Unfortunately, engineers report spending too much time on non-value-added work with too many interruptions, taking them away from critical innovation work. Furthermore, 96% of surveyed companies say this loss in engineering productivity comes at a significant business cost due to missed deadlines, higher costs, less innovation, and poor quality. To overcome productivity losses, one approach is to manage product data better and make it accessible to those who need it, when they need it.
Reclaiming Wasted Time
This report identifies major engineering time wasters and examines them across the dimensions of both company size and product complexity. It explores how companies of all sizes reclaim lost time by examining the use and value of PLM (Product Lifecycle Management) solutions to centralize data across multiple domains, manage processes, and collaborate better. PLM users reported fewer changes due to outdated information and errors, significantly reducing non-value-added work and shortening development times. This report also looks at how companies select and use PLM solutions, including cloud-based implementations.
Conclusions
Reclaiming Lost Time
Smaller and medium-sized companies prioritize their future growth and sustained success on winning in the marketplace with better, differentiated products. To support this, they can give their product development capabilities a significant boost by eliminating the time wasters that consume engineers' valuable time.
Companies of all sizes find that PLM can empower their engineers to innovate by significantly reducing engineers' time on non-value-added tasks. As a result, they can enjoy a competitive advantage. In addition, technology advances, such as cloud-based offerings, can reduce implementation time, cost, and difficulty, making PLM more accessible to smaller and medium-sized companies.
Recommendations
Next StepsBased on industry experience and research for this report, Tech-Clarity offers the following recommendations to smaller and medium-sized companies:
Consider the business impact of engineering time wasters on your company and make investments to minimize them. By empowering engineers to focus more time on value-added work, you will get to market faster with better, more differentiated products.
Consider how challenging it can be to find and recruit engineering talent in today’s business climate. Freeing engineers from time-wasting tasks can help take some pressure off your existing staff, improving their work environment and productivity, and reducing the need to add more.
Look at PLM as a potential solution to reduce engineering time wasters. Smaller and medium-sized companies report that PLM offers benefits such as centralizing data, supporting multiple domains, managing processes, and improving collaboration. This frees engineers from tasks that waste their time so they can focus more on engineering and innovation.
Use PLM for more than managing data. Those most satisfied with PLM also use it to manage engineering change processes, access control, requirements, and release processes.
Extend the use of PLM to a broader audience beyond engineering. Those most satisfied with it include management, manufacturing, quality, and sales as users.
Select a solution that has the flexibility to configure to your processes. An overwhelming 74% who found the implementation easy, identified this as helpful to the implementation.
Consider a cloud solution. Interestingly, 78% of those who implemented a cloud solution considered the deployment easy and implemented it in half the time required by those using a non-cloud solution.
*This summary is an abbreviated version of the research and does not contain the full content. For the full research, please visit our sponsor Siemens (registration required).If you have difficulty obtaining a copy of the report, please contact us.
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[post_content] => What should you look for in a systems engineering solution for your company to manage multi-discipline systems?As products become smarter and more connected, they also get more complex. Expert systems engineering practices can help to manage this complexity, especially when you are developing multi-discipline systems. The right technology can also be critical to support those practices. This buyer’s guide, Engineering Buyer’s Guide for Multi-Discipline Systems: The Expert Solutions Guide, provides a framework to evaluate systems engineering solutions to help you select the right solution for your company. It provides checklists for software requirements across multiple aspects of systems engineering, requirements to make the implementation a success, vendor requirements, and special considerations. By evaluating these requirements, you will be better positioned to select the right solution to successfully manage multi-discipline systems.Please enjoy the summary* below. For the full research, please visit our sponsor PTC (no registration required).
Table of Contents
Executive Overview
The Business Value of Systems Engineering
Start with Process Definition
Manage Requirements
Design the System
Design the System to be Modular
Support Product Line Variants
Enable Detailed Design
Support Connectivity
Verify and Validate the System
Assess Service Requirements
Consider Vendor Attributes
Identify Specific Needs for Your Company
Conclusion
Recommendations
About the Author
Acknowledgments
Executive Summary
Fierce global competition continues to drive companies to seek new ways to competitively differentiate their products. Many achieve this differentiation through smarter and more connected products. This approach creates many innovative possibilities for new products and services.
While smarter products and connectivity create exciting opportunities for innovation, they also bring unique challenges and add new levels of complexity. Much of this complexity comes from requirements to integrate mechanical components, electronics, and software. Connectivity adds further complexity as you add sensors, streaming data, and an ecosystem of connected systems. Whether you are a systems engineer, product architect, or domain-specific engineer, addressing this complexity requires expert systems engineering practices.
To set the foundation for expert systems engineering practices, companies should focus on the entire systems engineering process, ensuring there are solutions for all aspects of systems engineering. Expert systems engineering practices will help companies become even more competitive in ways that will lead to higher growth and greater profitability.
The right technology is an essential part of implementing and supporting these expert systems engineering practices. The right technology will enable improved collaboration, better traceability with a digital thread, and earlier visibility to potential problems. This will result in a more efficient development process while reducing the risk of finding errors late in the process, helping to avoid delays and increased costs. This buyer’s guide will help manufacturers select the right software to support systems engineering.
This guide comprises four major sections covering systems engineering software tool functionality, service requirements, vendor attributes, and special company considerations (Figure 1). Each section includes a checklist of key requirements to support your selection process for systems engineering software tools.
Conclusion
Expert systems engineering practices are vital to take advantage of innovation available through embedded software and the Internet of Things. The opportunities to create smart, connected devices can help companies set their products apart from the competition, helping them win new customers and increase revenues. However, bringing together systems of mechanical components, electronics, and software is complex. That complexity grows exponentially as companies try to meet the various needs of customers with different configurations. Connected systems add even further complexity as you add sensors, streaming data, and connected ecosystems.
Complexity increases the risk that things will go wrong. The impact of these problems can have a significant business impact and hurt product profitability. Implementing expert systems engineering practices, with the right software tools to support them, can manage this complexity, making it easier to successfully bring profitable products to market. Even if today’s smart, connected devices are relatively simple, as they evolve and offer critical services such as those that impact safety, they will increase in complexity and need the same level of expert systems engineering practices.
These practices and the supporting solution are not just limited to systems engineers either. There are a variety of IoT-related roles involved with planning, designing, and architecting connected systems, such as IoT solution architects, who will struggle with the exact same challenges as systems engineers. Companies planning for growth should consider both current and future needs.
However, there are so many aspects of systems engineering; determining the right solution for your company can be very difficult. Using a high-level list of tool and process evaluation criteria such as the ones in this guide can help narrow down potential solutions. The lists provide a quick “litmus test” to determine if a solution and partner are a good fit before conducting detailed functional or technical reviews. In the end, it is crucial to ensure that functionality, service, vendor, and special requirements are all considered when selecting a solution.
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full report, please visit our sponsor PTC.If you have difficulty obtaining a copy of the research, please contact us.
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How can manufacturers bounce forward from disruption with smart manufacturing? Read our short post for some insights from our research and then join a live event to learn from Tech-Clarity's Jim Brown and a variety of other speakers in a live Industry 4.0 event.
Industry Disruption is the New Normal
Today’s global manufacturing industry is more susceptible to global disruptions than ever. In the past decade, we’ve had to recover from earthquakes, volcanoes, tsunamis, political uncertainty, and a global pandemic. These events have led to demand volatility, supply chain disruptions, and workforce impacts. Consequently, our research finds that about three-quarters of companies have experienced an increase in business risk and disruption over the prior five years.
Responding to Adversity by Bouncing Forward
The manufacturing industry, however, did not give up. Instead, our research shows that:
86% of companies increased their focus and attention on digital transformation as a response to disruption
49% of companies accelerated technology adoption.
In short, we’ve seen many manufacturers “bounce forward” from recent disruptions, coming out of the turmoil in a better position to succeed long term. For example, about one-half of companies increased corporate agility and collaboration capabilities. Unfortunately, we also saw companies in the heart of the COVID disruption reduce focus on environmental and social responsibility. This appears to be recovering, and will be a key part of long-term business success in manufacturing.
Top Performers Get More Value by Acting on Digital Data
One of the keys to success is digitalizing data and processes. Our research shows that Top Performing companies are:
50% more likely to have fully digital design data than poorer performing companies.
Three times as likely to have fully digital design and development processes.
These digital advantages don’t end in design, they continue into manufacturing. In fact, Top Performers are:
Three times as likely to integrate IT and OT data and systems.
They can also put this data into action, for example Top Performers are:
More than three times as likely to be able to provide access to manufacturing data in time to impact performance.
That’s a big deal!
Interested in More?
Don’t miss out on the opportunity to learn how to navigate your smart factory initiatives at our exclusive event on April 28th 12:00pm-4:30pm at the Great Lakes Brewery in Cleveland, OH.The jam-packed agenda includes industry expert panel, a networking Lunch, a deep dive roundtable session, and a happy hour (where the real secrets are revealed)!This is your opportunity to learn how industry leaders took advantage of the emerging technology and lowered costs while simplifying operations. Register now to network with industry peers and experts. Limited seating at this intimate event!For full event information and registration please visit the event sponsor, FactoryEye. Click here to view the full list of speakers. You can also view the event brochure here.
A version of this post originally appeared as a guest post on the FactoryEye site.
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[post_content] => Is PLM living up to its potential in consumer packaged goods? Is it ready to support today's digital transformation strategies? What is the status quo for PLM in CPG? We surveyed over 150 companies to find out.
Please enjoy the summary below.* For the full report, please visit our sponsor Kalypso (registration required).
Table of Contents
The Digital Transformation Imperative
PLM Plays a Vital Role in Digital Transformation
PLM Provides Multi-Faceted Business Value
The Untapped Value of PLM
Extending PLM Value Requires Vision
PLM Implementations Must be Made Future Ready
Identifying Top Performing CPG Product Developers
Adopt More Digital Product Design Approaches
Be More Strategic About PLM
Utilize PLM More Broadly
Take Advanced Approaches to Product Definition
Leverage Advanced Product Formulation Techniques
The State of PLM Implementations
Move to the Cloud
Conclusions
About the Research
Acknowledgments
Is PLM Meeting Its Potential?
PLM: Innovation Platform of Product Governance Utility?Product Lifecycle Management (PLM) promises enhanced product innovation and faster time to market, leading to higher market share and increased profitability. Who doesn't want these strategic, top-line benefits?
PLM implementations, however, typically focus on increasing control, compliance, governance, quality, and product development efficiency. Those are valuable benefits, but are they enough? Is PLM living up to its potential? And is PLM ready to support today's digital transformation strategies?
PLM Plays a Vital Role in Digital Transformation
Support Digital Transformation
PLM is the backbone of the digital enterprise. Respondents rated the importance of PLM to the strategic initiatives discussed above. A full 85% of companies see PLM as critical or important to digital transformation, and one-quarter say it is critical. On the other hand, only 3% see it as not important or relevant to supporting this strategic business imperative.
Support Digital Threads, Twins
The conclusion that PLM plays a vital role in digital transformation is supported by its importance for digital thread and digital twin initiatives. Over one-half of CPG companies say that PLM is important or critical to supporting the digital thread. Respondents report very similar views on the importance of PLM to support digital twin initiatives. The findings confirm our experience that PLM is an important part of digital transformation in the CPG industry.
The Untapped Value of PLM
Achieve Top-Line Benefits
CPG companies surveyed for this study were asked what goals they have achieved from PLM. The top two benefits, faster product development and improved product innovation, can lead to higher market share and greater revenue. Increased quality may also help improve sales and the top line. About half of the CPG companies polled report they receive each of these benefits. They also reported cost savings and operational benefits.
Extend PLM
CPG companies can achieve greater benefits if they extend their PLM systems to more people, greater functionality, and additional processes. The most commonly reported driver of significant new value for CPG companies is extending PLM to more people. In many cases, this may be possible with their existing PLM solutions. The same is likely true for extending PLM to more processes. For some, they may also be able to implement capabilities in their existing system that are currently going unused.
Improve Integration
In addition to extending PLM, or perhaps supporting it, is better PLM integration. Between one-third and one-half say that better integration with design tools would add significant value. Integration increases efficiency, collaboration, and the ability to iterate design options. This integration may include formulation, packaging, label design, and CAD tools. Beyond tool integration, many companies report they would gain higher value with better / more integration with business systems, which likely includes ERP and potentially others like CRM and MES.
Conclusions
Top Performers Show That PLM Systems Can Deliver More Value
PLM provides significant top-line, bottom-line, and operational value for CPG companies. Surveyed companies report multiple business benefits ranging from time-to-market improvements to increased compliance and traceability.
Even with the high level of value realized, there is more to be achieved by extending PLM further. Top Performers set the stage to show how Others can get the most out of their current PLM investments. Top Performers, more than Others:
View PLM as a strategic platform for product innovation
Recognize the value of PLM internally and in the value chain
Extend PLM to more departments
Digitalize data and processes
Use more (and more advanced) PLM capabilities
Use more advanced data modeling and simulation capabilities
PLM Systems Must Evolve to Support Digital TransformationThe majority of CPG companies believe their existing PLM systems are adequate for their current needs. But they also recognize that PLM is vital
to achieving their highly strategic, digital transformation initiatives. The current status quo of using multiple systems, which are typically customized and not fully integrated into the ecosystem, is an inhibitor to achieving digital transformation and extended value. Not surprisingly, the majority of surveyed participants don’t believe their current PLM system will meet their company’s future needs.
Top Performers point the way toward the future of PLM. They adopt PLM as a platform for the enterprise and supply chain that is more integrated, more advanced, more widely adopted, and kept more current. It’s important to note that the systems have typically been heavily customized, and not everyone can afford the tradeoffs between customization, cost, and keeping implementations up to date. But they are rewarded with better innovation, product development, and compliance – all of which help drive higher profitability.
The Future is Bright, But There is Work to be Done
PLM is already driving a lot of value, but the status quo finds most CPG companies unprepared for the future. PLM needs are changing, and PLM must adapt and evolve. CPG companies that want to retain or improve their product innovation performance must continue to improve their PLM implementations and capabilities.
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full report, please visit our sponsor Kalypso.If you have difficulty obtaining a copy of the research, please contact us.
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[post_content] => How can increasing performance engineering maturity help manufacturers ensure they’ve fully optimized equipment performance? How does “shifting left” with simulation and closed-loop feedback help improve performance without compromising project due dates?
Please enjoy the summary* below. For the full research, please visit our sponsor Siemens (registration required).
Table of Contents
The Performance Engineering Imperative
Predicting Equipment Performance Virtually
Create Holistic Equipment Models
Predict Performance Through Simulation
Improve Predictive Through Testing
Improve Predictions with Field Data
Improve Equipment Performance with Lower Overhead
Acknowledgments
The Performance Engineering Imperative
Increasing Market Demands
Engineers need to continuously improve and optimize equipment designs. Global competition is intense and the performance bar is constantly being raised. Equipment must meet increasingly challenging market demands for weight, fuel efficiency, sustainability, regulatory compliance, and more connected operations environments while still meeting aggressive time-to-market requirements. Some manufacturers are also evolving to new business models, such as product-as-a-service (PaaS), where profitability relies directly on equipment performance in the field.
Increasing Product Complexity
Harder targets are made even more challenging because of increased product complexity. Equipment is more electrified, autonomous, connected, and configurable than ever. Companies must adopt systems, and systems-of-systems, engineering approaches. At the same time, manufacturers are adopting new materials such as composites, advanced manufacturing methods including additive manufacturing, and innovative design techniques such as generative design. These innovations create designs that can’t be easily validated using historical tests and product performance, demanding new approaches.
Simulation is Critical, but not Enough
Computer Aided Engineering (CAE) has clearly helped manufacturers overcome complexity and reach new performance levels. But the time has come to explore new digital technologies. Traditional simulation benefits may no longer meet the demands of digitalization trends.
In order to get products right the first time, and to “shift left” optimization to get to the best design faster, companies have to be able to predict equipment performance in a variety of facets, including:
Holistically by managing tradeoffs
Accurately by gaining a meaningful understanding of the impact of engineering decisions
Efficiently by making it feasible to optimize early and often throughout the design process
And they have to do this virtually, with fewer costly and time-consuming prototypes. Given these needs, how can they raise their maturity and performance?
Improve Equipment Performance with Lower Overhead
Adopt Predictive Performance Engineering
Like predictive service, which has proven value, predictive performance engineering has tremendous business potential. The approach allows companies to unlock new levels of innovation and performance while simultaneously improving efficiency and reducing cost. Manufacturers that improve performance engineering maturity will likely be able to develop more innovative, high-performance equipment at a lower cost. At the same time, they will no longer have to trade off hitting their certification and market readiness objectives in order to reach performance goals.
Improve Performance Engineering Maturity
Companies can increase performance engineering maturity by improving the following four processes:
Create holistic equipment models
Predict performance through simulation
Improve predictions through testing
Improve predictions with field data
Improvement in any of these areas can drive meaningful improvements and ROI. Each of these steps reduces engineering effort, product development time, and costly physical prototypes. At the same time, it allows equipment manufacturers to be more competitive by continuously raising the bar for safer, greener, more reliable, high-performing products.
Get Started
Companies should consider starting their performance engineering journey with a realistic assessment of current maturity. From there, they should explore the improvement opportunities in this eBook to increase performance engineering maturity, then adopt more advanced processes and technology to drive meaningful equipment and process improvement. After early improvement, they can expand on their success by continuing to improve performance engineering maturity.
*This summary is an abbreviated version of the research and does not contain the full content. For the full research, please visit our sponsor Siemens (registration required).If you have difficulty obtaining a copy of the report, please contact us.
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[post_content] => What do industry experts and your manufacturing peers have to say about smart manufacturing? Join this live event on April 28th in Cleveland, Ohio to find out. Our own Jim Brown will keynote the conference, sharing his views on how manufacturers can “bounce forward” from recent disruptions with smart manufacturing solutions. Then you’ll hear from a host of great speakers and have the opportunity to join roundtable sessions to learn from the presenters, panelists, and peers alike.And if that’s not enough, the Cleveland Manufacturing event starts with lunch and is followed up with a happy hour. Join us to share your experience and learn from others.List of speakers:
For full event information and registration please visit the event sponsor, FactoryEye. You can also view the event brochure here.
[post_title] => Knowledge is Power: The Secrets of Industry 4.0 (live event)
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[post_content] => How much of your industrial design work can be leveraged during detail design? Could your products be even better if you had more time to get concepts right by reducing non-value-added work?An overwhelming 76% of manufacturers agree that spending more time on concept and industrial design would improve products. Unfortunately, industrial designers waste significant time on non-value-added work, which holds them back. Read our eBook, Seven Ways to Reduce Non-Valued-Added Work in Industrial Design to learn how to reduce wasted effort so that Industrial Designs can work more efficiently to help your company develop even better products. You will also learn way to improve collaboration between industrial designers and design engineers.
Please enjoy the summary below.* For the full report, please visit our sponsor Dassault Systèmes SOLIDWORKS (registration required).
For related research, please read our eBook, How to Reduce Non-Valued-Added Work in Engineering to learn more about how to reduce wasted effort and increase focus on value-added engineering and innovation work.
Table of Contents
Executive Summary
Importance of Concept and Industrial Design
Identifying Top Performers
Strategies to Reduce Non-Value-Added Work
1. Improve Efficiency with a Single Solution
2. Support Reuse by Leveraging the Concept during Detail Design
3. Enable Easy Iterations
4. Facilitate Internal Feedback
5. Solicit Customer Feedback
6. Select an Ideal Solution
7. Tie it Together on a Platform
Recommendations
About the Research
Acknowledgments
Executive Summary
Reducing Non-Value-Added Work
An overwhelming 76% of manufacturers agree that spending more time on concept and industrial design would improve products. Unfortunately, industrial designers waste significant time on non-value-added work, which holds them back. Further, detail designers waste even more time recreating industrial design details. Reducing this non-value-added work could help a company get to market faster, optimize profitability, maximize revenue potential, and offer more competitive offerings.
Interestingly, 99% say that technology should play a role in limiting this non-value-added work. Moreover, the research identified key ways technology can help.
Seven Practices
This report reveals seven practices that will reduce non-value-added work in industrial design:
Use a single solution to support industrial and detail design.
Leverage more of the concept model during detail design.
Streamline design iterations between industrial and detail design.
Facilitate internal feedback with more efficient design reviews.
Involve customers as early as possible.
Ensure your solution meets the unique needs of industrial designers.
Tie everything together with a cloud platform.
Other Key Findings
The research also revealed several other interesting findings, including:
95% of Top Performers who use a single solution for both industrial and detail design rate their remodeling process as ‘excellent’ or ‘very good.’
71% of industrial designers say it would save time if customers could provide more feedback early on.
Industrial designers identify the top quality of an ideal industrial design solution as one that supports both subdivision and parametric modeling.
Recommendations
Recommendations and Next Steps
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations:
Investments to improve the efficiency of industrial and concept design can offer a competitive advantage.
Consider a single solution to support industrial and detail design so that rather than wasting time importing, exporting, fixing, and recreating data, designers can spend more time on critical design work.
Ensure that detail designers can reuse as much of the concept design as possible. Reinventing the wheel by recreating design details already in the concept model wastes their time. Instead, they could use that time to innovate, improve product quality, or beat deadlines to get to market faster.
Reduce barriers to iterations so industrial and detail designers can remodel the design as needed to improve upon ideas, implement engineering changes, or fix manufacturability issues. When their work is siloed, iterations involve importing and exporting data, which wastes hours.
Improve the timeliness of internal feedback with more streamlined ways to solicit feedback and more efficient design reviews. Real-time visibility to design progress on a single, integrated design collaboration platform can improve collaboration to efficiently collect feedback.
Involve customers as early as possible to provide feedback to help ensure your product aligns with customer needs.
When selecting a single solution for industrial and detail design, ensure it supports both subdivision and parametric modeling.
Tie everything together with a cloud platform so that you have the infrastructure to support better collaboration, and designers can access the software capabilities they need on the hardware they prefer.
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full report, please visit our sponsor Dassault Systèmes SOLIDWORKSIf you have difficulty obtaining a copy of the research, please contact us.
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[post_content] => Our research shows that companies with the highest tech transfer performance digitalize their tech transfer data and processes. But what does digital tech transfer look like, and how do you get there? This how-to guide shows life sciences companies the way.
Please enjoy the summary* below. For the full research, please visit our sponsor Dassault Systèmes (registration required).
Table of Contents
Why Digitalize Tech Transfer?
Digitalize Data
Automate Data Gathering
Integrate Data and Processes
Expand Collaboration
Gain and Leverage Knowledge
Adopt Best Practices to Improve Tech Transfer
About the Research
Acknowledgments
Why Digitalize Tech Transfer?
Tech Transfer Objectives
The World Health Organization explains that “Technology transfer can be considered successful if there is documented evidence that the RU (receiving unit) can routinely reproduce the transferred product, process, or method against a predefined set of specifications as agreed with the SU (sending unit).” That may be true, but is that enough to define success from a business perspective? Companies have to be able to not just effectively transfer technology from early discovery to manufacturing. They have to do so efficiently, with quality, to compete.
Identifying Best Practices
Our report, Digitalizing Tech Transfer, benchmarked companies on their:
Speed in achieving steady-state, full-rate production
Yield and product quality in early production, and
Their overhead cost to support tech transfer.
Researchers used these benchmarks to identify best practices that lead to successful tech transfer performance. These best practices include digital data, processes, and technology.
Driving Tech Transfer ImprovementsThis guide identifies key steps life sciences companies must take to implement best practices and improve tech transfer performance:
Digitalize Data
Automate Data Gathering
Integrate Data and Processes
Expand Collaboration
Gain and Leverage Knowledge
All of the steps rely on digitalizing data and adopting a data-centric tech transfer approach to leverage the data and improve communication. We’ll explore each of these steps in the following pages.
For more details from this earlier research, please see Digitalizing Tech Transfer.
Adopt Best Practices to Improve Tech Transfer
Take the Time to Get it Right
It’s time for life sciences companies to digitalize tech transfer. Tech transfer success for analytical and manufacturing methods is critical to business success and profitability in the life sciences industry. But tech transfer success is multi-dimensional. Tech transfer requires agility, but speed without quality isn’t enough.1 Getting tech transfer projects right the first time helps save money and get to market faster.
Improving Tech Transfer through Digitalization
Digitalizing tech transfer processes and data is fundamental to improving tech transfer success and broader continuous improvement. The following steps can further drive best practices and performance improvements:
Digitalize Data
Automate Data Gathering
Integrate Data and Processes
Expand Collaboration
Gain and Capture Knowledge
These steps build on each other to create a digital, data-centric tech transfer approach. Successfully improving tech transfer performance and results requires integrated, open systems that can connect data across the product lifecycle from early discovery through operations and transcend lab, plant, and corporate boundaries.
*This summary is an abbreviated version of the research and does not contain the full content. For the full research, please visit our sponsor Dassault Systèmes (registration required).If you have difficulty obtaining a copy of the report, please contact us.
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[post_content] => How can startup companies improve their chances of success? Our Startup Survival Guide reveals both how and why simulation can provide startups an edge to launch a successful product. As part of a cloud platform, CAE can also be more accessible to startups.
Please enjoy the summary* below. For the full research, please visit our sponsor Dassault Systèmes (registration required).For more information on simulation, see our related research How to Survive and Win New Markets By Getting Even More Value from Simulation andHow to Engineer High-Performing, Quality Products without Extra Cost.
Executive Summary
Endless Possibilities
Recessions and the years following them often mark the birth of new businesses, making this a very exciting time for entrepreneurs. With expanded options for funding and opportunities for new technologies to enable innovation, there are endless possibilities for startups. As a result, we are now seeing more successful new companies than ever before.
Unfortunately, for every success story, there are even more startups that do not make it. It is hard to start a new business from scratch as funding is limited, and competing with more established companies that have more resources can be challenging.
The good news is that for many, modern software tools are closing the resource gap. New software solutions, supported by a modern infrastructure, allow even the smallest businesses access to resources that previously were available only to large companies with deep pockets.
Cloud-Based Simulation
A cloud-based simulation software platform is one such tool. Simulation software allows you to evaluate more options in less time, optimize the design, and catch problems early in the design process. In addition, startups can avoid significant upfront investments in software and hardware by using a cloud-based solution. Plus, companies do not need to worry about investing precious resources in an IT department to implement and maintain it.
This Report
This report discusses the most common reasons startups fail and explains how a cloud-based simulation platform can help. By taking advantage of the technology, it can allow you to:
Access more funding
Improve profitability
Get the product right
Validate market needs
Leverage the right talent
This powerful combination can help you add your company’s name to the growing list of successful startups.
Typically, it is not a single problem that leads to failure, but the ability to simultaneously address all of this will go a long way toward improving your chance of success. A cloud-based simulation solution can help you tackle the multifaceted challenges of starting a new business to profitably bring your ideas to reality.
Table of Contents
The Opportunities for Startups
1. Access More Funding
2. Improve Profitability
3. Get the Product Right
4. Validate Market Needs
5. Leverage the Right Talent
Recommendations
Acknowledgments
Recommendations
Recommendations and Next StepsBased on industry experience and research for this report, Tech-Clarity offers the following recommendations:
Use simulation to demonstrate progress to investors to help justify additional funding.
Leverage a cloud platform to preserve capital by avoiding high upfront costs for software licenses and investments in high-end hardware.
Optimize your product for quality and cost to maximize profitability and allow you to price your product competitively.
Support rapid iterations with simulation to develop a more innovative, competitive product.
Take advantage of simulation in the cloud to validate your product early and often with potential customers to verify it will meet market needs.
Tap into additional expertise as needed with a simulation cloud platform that will provide flexibility to easily collaborate with third parties.
*This summary is an abbreviated version of the research and does not contain the full content. For the full research, please visit our sponsor Dassault Systèmes (registration required).If you have difficulty obtaining a copy of the report, please contact us.
[post_title] => Five Ways Simulation Enables Startups
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[post_content] => How can you ensure that you choose the right PDM software and partner for your business? The right system serves as the backbone for digital transformation and impacts productivity, product success, and profitability. How can you make sure to get it right?
Please enjoy the summary* below. For the full research, please visit our sponsor PTC (registration required).
Table of Contents
Introducing the PDM Buyer's Guide
Using the PDM Buyer's Guide
Analyze PDM Capabilities: Control
Analyze PDM Capabilities: Access
Analyze PDM Capabilities: Share
Assess Service Requirements
Service Requirements: Implementation
Service Requirements: User Adoption
Service Requirements: Support
Consider Vendor Requirements
Identify Unique Company Needs
Support the Digital Enterprise
Conclusion
Recommendations
Acknowledgments
Introducing the PDM Buyer's Guide
Product Data Management (PDM) is an important tool to help manufacturers overcome the complexities of designing, developing, producing, and supporting today’s products and product development processes. Manual and ad-hoc approaches such as shared folders, cloud storage, and hard drives are simply not effective solutions to manage critical, complex product information. These approaches may work for very small organizations, but quickly falter as organizations grow and must share information beyond a few core engineers. These techniques also fail to manage data relationships and complex file structures common to 3D CAD systems. PDM systems are purpose-built to address these issues.
PDM is a structured, collaborative solution that helps manufacturers control, access, and share crucial product data. Selecting the right PDM system can have a large impact on productivity, product success, and profitability. How can you ensure that you choose the right software and partner for your business?
Purpose of the Guide
The PDM Buyer’s Guide is not intended to provide an all-encompassing requirements list. Instead, it covers the high points that manufacturers should look for in a PDM system. Think of this as a “PDM litmus test” to see if a solution is a good high-level fit for your business before spending significant time and effort analyzing detailed features and functions.
Consider Broader Requirements
Although the checklists focus only on PDM requirements, it’s important to consider more than your current needs when choosing a system. Many companies eventually want to grow beyond basic PDM to a more complete PDM system. These more advanced capabilities are covered in our Expanding Beyond Your Outgrown PDM System Buyer’s Guide. Other companies may start with PDM and evolve through a maturity process to a more complete Product Lifecycle Management (PLM) environment. PLM extends the core PDM foundation to support more product development and engineering processes, manage a richer view of products, include more people in product development, and support processes further upstream and downstream from Engineering in the product lifecycle (Figure 1).
Conclusion
Adopt Common Requirements for PDM
PDM helps manufacturers address complexity and improve business performance. When evaluating PDM, manufacturers need to take into account:
Product requirements
Implementation, adoption, and support requirements
Vendor / business requirements
Special requirements based on company size (particularly for very small or very large organizations)
Special considerations to meet industry needs
Future requirements as the manufacturing industry continues to digitally transform
The final collection of requirements for any given company will be unique and must be prioritized based on contribution to supporting your implementation and achieving your business objectives. Some evaluation criteria may be critical, while others should carry a lower weight. The key is to select a solution that best fits the needs of the business and can be realistically supported.
Using a high-level list of requirements such as the ones in this guide can help you narrow
down potential solutions by providing a quick “litmus test” to determine if a solution and partner are a good fit before conducting detailed functional or technical reviews. For example, smaller companies may want to emphasize ease of implementation and support in their initial evaluation. Larger manufacturers, on the other hand, might emphasize more mature engineering change processes and require a more scalable solution like extended PDM.
Plan for the Future
Remember, it’s critical to consider both current and future needs when evaluating potential solutions. You should consider the possibility that your company may want to expand into a more full-featured system and look for a PDM system that can serve as a foundation for a broader PLM implementation and support your company’s digitalization objectives. You should also consider how likely it is that your business will grow and ensure that the solution you implement can scale to enterprise capabilities and provide enterprise functionality. From a PDM perspective, it’s important to implement what is needed today, but know where the business is going and select a platform that can grow with the business. Lastly, it’s important to consider the cloud a requirement regardless of whether your company is ready for the transition.
Recommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations:
Identify and weigh PDM requirements based on company needs, company size, industry, and any unique company needs
Use high-level requirements such as the ones in this guide to evaluate solutions based on business fit before engaging in detailed, technical evaluations
Consider using the cloud or managed services solutions for companies that wish to move quickly, have limited IT resources, want to reduce overhead, or want to modernize their IT infrastructure
Take user adoption into account, including simplified access, increased visualization, and task-specific apps for non-engineering resources
Take into account long-term business and process growth needs including digital transformation, AR / VR, and IoT initiatives
Consider the potential to expand to a more capable extended PDM or PLM system, but start small and get value along the way during implementation
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full research, please visit our sponsor PTC (registration required).If you have difficulty obtaining a copy of the research, please contact us.
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How do you manage system family engineering?
As today’s products become increasingly complex, managing their different configurations becomes exponentially more challenging. Trying to trace which features you need to support required functions can be tedious, time-consuming, and error-prone. At the same time, the age of digital transformation has driven companies to find new ways to become more efficient. Those who have been successful, enjoy competitive advantages that make it hard for their competitors to keep up. Some companies are realizing these efficiencies with feature-based product line engineering. To learn more about this approach and determine if it is right for your company, watch this webcast to hear from Tech-Clarity’s Michelle Boucher and BigLever Software’s Dr. Charles Krueger.Webinar details:Title: How to Use a Modern Digital Approach to System Family Engineering to Stay Ahead of the CompetitionAccess: The on-demand webinar here
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[post_content] => What could justify replacing the MES in an operating semiconductor fab? Advanced capabilities that traditional MES cannot model or support. Significant changes in the business of making microelectronics have created the need for much greater agility and complexity of processing. Seeking out a system that can support current operations is crucial to ongoing competitiveness.Reimagining Semiconductor MES: Advanced Fab Capabilities for Agility and Success supports semiconductor companies in understanding why the changes to their business demand truly modern, supportive software. Reimagining an MES that supports advanced capabilities in fabs - and then investing in it - is the path to ensure semiconductor company profitability and agility today and into the future.
For related research, please read The Manufacturing Data Challenge.
Please enjoy the summary* below. For the full research, please visit our sponsor Critical Manufacturing (registration required).
Table of Contents
New Semiconductor Imperatives
Topic: Skyrocketing Demand Puts Pressure on Fabs
Innovation Issues
Meeting Demand
Processing Challenges
Progress Matters
Quality Demands
Empowering the Workforce
IT Overwhelm
Streamlining Information Systems
MES Reimagined
Reimagine and Reinvest in MES
Acknowledgements
New Semiconductor Imperatives
Keeping up with rising demand, product portfolio growth, complex products, processing mix, and new application requirements creates tremendous challenges for semiconductor makers. Companies must increase their pace of both learning and ramping up new products and processes.
Production operations are a pinch point. To handle new demands, companies must optimize further. Thus, it is imperative to reimagine the manufacturing execution system (MES) for semiconductor to meet today’s needs. MES must expand beyond work-in-process (WIP) and track and trace to become the data platform for production innovation, change, and efficiency. All types of facilities face this need, and modern MES can serve silicon, R&D, front-end fabs, back end, and even module production. While no longer isolated, front-end fabs face particular challenges and urgency due to their array of advanced capabilities.
Reimagine and Reinvest in MES
Expect More in SoftwareOver the past several years, fab processes have changed, and your Manufacturing IT must as well. Open your minds to reimagine what MES is and does. Evaluate MES against customer requirements and strategic business needs. As this paper describes, modern MES solutions go far beyond track and trace and WIP management to support advanced semiconductor processing capabilities.Evaluate the Need Most semiconductor fabs have a vast “hidden fab” where workarounds have become the norm. To understand that count how many systems you use to support fab operations todaymeasure how much time, effort, and energy your team spends finding and consolidating data for day-to-day operations understand how much time the Manufacturing IT team spends maintaining and customizing the MES. If you’re dissatisfied with the answers, look for software that supports your fab’s advanced capabilities.Reinvest in MESPush MES providers to get what you need. Some specifics you might need are in Figure 5. Beyond specifics, you need a smooth and coherent flow of data in the fab and into the enterprise. Speed of learning all you need to ramp up for NPI and continue improving yield and serving the market opportunities lies in that manufacturing data management. Investing is urgent – you can’t be as resilient nor as profitable as you want without data that’s in context and ready to use.*This summary is an abbreviated version of the research and does not contain the full content. Please visit our sponsor Critical Manufacturing for the full research (registration required). If you have difficulty obtaining a copy of the report, please contact us.
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[post_content] => How can PLM, traditionally an engineering-centric solution, drive innovation, agility, and operational excellence? Manufacturers need to create agility in their business and processes so they can respond to increasing business risk and bounce forward better than ever. To do this, Engineering and product development have to fundamentally change. They have to focus on the big picture, not just engineering, to develop profitable products. PLM’s role needs to expand to support them.Read our eBook to understand how to choose the right PLM to support operational excellence.
Please enjoy the summary* below. For the full research, please visit our sponsor QuadRite (registration required).
Table of Contents
Risk and Disruption Demand Change
The Evolution of Engineering
Choosing PLM
The Basics
Expanding PLM for Operational Excellence
Expanding PLM - Process
Expanding PLM - People
Expanding PLM - Lifecycle
Expanding PLM - Product
Conclusions and Next Steps
Acknowledgments
Expanding PLM for Operational Excellence
The Four Dimensions of PLM ExpansionPLM implementations must go beyond the basics to support operational excellence. We’ll discuss four important ways that PLM has expanded in order to support operational excellence:
Process: Improving processes beyond basic revision control and release to manufacturing
People: Including more people and departments beyond Engineering, including partners, the supply chain, and customers
Lifecycle: Supporting upstream and downstream capabilities beyond design
Product: Expanding beyond product design to a full product definition
Each of these expands the value of PLM, supports more mature product innovation practices, and helps make better use of product information throughout the enterprise. Together, they support the pursuit of operational excellence.
Expanding Communication with PLM
Another valuable dimension of PLM expansion is by supporting broader communication and collaboration between Engineering and the rest of the business. This can be looked at in two directions:
Inbound: Enabling engineers to better use information coming out of other business areas such as Procurement, Quality, Manufacturing, and others to design for operational excellence
Outbound: Making better use of information coming out of Engineering in other areas of business such as Marketing, Sales, Service, and more to support broader product innovation, development, manufacturing, and support process to drive operational efficiency
"To start, PLM supports document management, design control, and training. That sets the foundation for product development process compliance. Then, you can build on that to support operational needs like NCMR, suppliers, CAPA, change control, and complaint handling as you go to the commercial phase." - Scott King, Director, IRIDEX CORPORATION
"We started with ECOs, took some small bites, then expanded it more broadly by implementing it with supply chain, customers, drawings, orders, contract tracking, and source tracking. They lend themselves perfectly to PLM." - John Baumann, CEO, THINGAP, INC.
Conclusions and Next Steps
Moving Toward Operational Excellence
Manufacturers have to recognize the need for innovation, agility, and operational improvement. Business risk and disruption are threatening profitability and survival for many businesses. Products and markets have changed, demanding more.
Recognize the New Role of the Engineer
To support more supply-chain centric, operationally-focused product development processes the role of engineers has changed. They must be able to access a wider array of information in order to make broader product-related decisions. This, in turn, changes the requirements for the PLM systems that support them.
Choose the Right PLM Solution to Drive Operational ExcellenceThe four dimensions of PLM expansion provide a framework to understand what’s needed to drive operational excellence. Traditional, Engineering-centric PLM systems are not sufficient for fast-moving industries like high-tech and medical devices. Companies in these industries need a PLM solution built for the enterprise and the supply chain.
Lastly, manufacturers must get a solution that delivers on the promise of PLM. Systems selections and implementations should be driven by cross-functional teams that represent all aspects that impact product profitability. Selection requirements should span the enterprise and focus on how the system supports the new role of engineers and product developers. This is the way that companies can ensure that they select the right PLM systems to drive operational excellence.
*This summary is an abbreviated version of the research and does not contain the full content. For the full research, please visit our sponsor QuadRite (registration required).If you have difficulty obtaining a copy of the report, please contact us.
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