Let’s start with the digital thread. That’s probably the most straightforward concept and one that provides tangible value. The digital thread, in its simplest definition, is the collection of information used to define, engineer, and develop a product. Ideally it moves beyond the manufacturer into the in-service part of the equipment lifecycle. It offers a view of the digital continuity of the life of the device.
The value for medical device companies, in a nutshell, is end-to-end traceability. It’s the connection between everything from patient needs and early requirements through the patient experience, including post market surveillance requirements required by the EU MDR. It provides a broad base of information that allows medical device companies to analyze and learn from history, for example tracking down root causes for a CAPA.
The digital thread also clearly supports regulatory requirements related to these needs including the DHF and UDI, including all of the local variants of the regulations. In addition, the digital thread also provides an integrated source of data that can be used to prepare submission documentation. With the digital thread as the trusted data source, medical device companies can automate much of the process to generate these crucial reports.
Digital Twin
One of the key contributors to the digital thread is the Digital Twin. The digital twin has multiple definitions, but it starts at the core as a complete, digital model of the device. It incorporates a holistic view of the design to a level of granularity that companies can accurately simulate and predict device performance and behavior. There is clear overlap with the digital thread in this part of the definition.
The value of the digital model for medical device companies is a cohesive view of the device. It allows people from various disciplines to contribute their part of the design and see it in the context of the whole product. It allows engineers to analyze and optimize performance early in the product lifecycle, catching errors and improving performance in silica before physical prototypes are developed. As regulatory bodies get more comfortable with simulation data, the digital twin may also play a big part in reducing the length and cost of clinical trials. The digital thread also delivers quality management and regulatory value including the development of the DMR.
Connected Digital Twin
The value of the digital twin expands dramatically when it goes beyond device production and into usage. Some would say a digital twin without connectivity isn’t a complete twin, but regardless of definitions a digital model is highly valuable. But a connected one adds significantly greater value.
The rise of the IoT adds a new dimension to the value available from the digital twin. Companies can collect real-world device performance and associate it back with the intention of the design model. This can help identify issues where devices are not performing as designed, and may provide an early indicator of a potential variance.
A second aspect of the digital twin is identifying differences between predicted and actual device performance where the device is operating as designed, but not as intended. In these cases, there are gaps in the simulated performance of the digital model that can be addressed to improve simulations and understanding of how devices perform in the field.
Medical device companies gain significant value from the connected digital twin. It rounds out the information in the DMR and supports a more robust data set for UDI. It could also be used early in the lifecycle to help support clinical trials, as well as other regulatory demands throughout the lifecycle.
Digital Twin of the Plant
Another aspect of the digital twin is creating digital twins of the equipment used to produces devices. Companies can create fully functioning models of machines, lines, and plants to design, simulate, and optimize production. As with the digital twin of the product, connecting the digital twin provides even greater value. In this case, it may include the IIoT in addition to the IoT.
The digital twin of the plant helps medical device companies validate production methodology, SOPs, and set critical control points to improve control, reduce variability, and improve quality. It can also be used to validate process control intent with regulatory bodies. These twins, along with the digital twin of the device (which should be integrated) can also help automate regulatory submissions. Again, we see significant overlap in the use of digital tools in the medical device industry.
Analytics
The final piece of the puzzle we’ll discuss today is data analytics. Life sciences companies have been using analytics in multiple aspects of their business for quite some time. The digitalization of the underlying information in the design, engineering, manufacturing, and use of the device dramatically expands the opportunities. Companies now have a much broader data set to analyze and transform into intelligence.
Medical device companies can leverage big data analytics in conjunction with the digital twin and digital thread to identify trends and correlations previously hidden in non-digital or non-integrated data sets. Analytics can be used in multiple phases of the device lifecycle, from identifying process control parameters drifting toward spec limits to analyzing adverse event data in the field. This can make existing processes better, for example being able to more quickly identify root causes for CAPAs. It can also support newer requirements like post market surveillance in the EU and the upcoming shift to focusing on patient outcomes. It can also benefit patients, for example predictive analytics may be able to identify potential failures prior to their occurrence and prevent adverse events. Finally, additional insights may create a new source of innovation that leads to new and better treatment options.
IoT
The last area to discuss is the IoT. We’ve already mentioned it while discussing the earlier digital topics, it’s hard not to given it’s significant potential to change the relationship between medical devices, the manufacturer, healthcare professionals, payers, and the patient. But there is much more to this topic, so we’ll save this for a later post.
Our Take
Digitalization of the medical device industry takes the value of new technologies and techniques and extends them to improve both company profitability and patient outcomes. In the end, the buzzwords represent new capabilities with real potential to help medical device companies innovate, drive rapid product design, speed approvals, improve quality, and achieve higher levels of compliance. These are all important for them to continue their mission to improve patient welfare in today’s complex healthcare environment.
You can find more information about digitalization for medical devices from our sponsor, Siemens PLM.
You can also find more information from Tech-Clarity on digitalization in the medical device industry please see our The Digitalization Opportunity for Medical Device Companies (video) or Digitalization in the Medical Device Industry (animation).
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[post_content] => How can manufacturers and service providers drive additional productivity and profitability by developing equipment intelligence by monitoring equipment health? Learn how the IIoT, edge computing, and analytics help companies predict and mitigate equipment issues before they disrupt production.
Manufacturers can now identify trends and data relationships that previously went undiscovered by combining data from multiple sources with information from sensored equipment, whether they are monitoring their own facilities or products they service at their customers' sites.
Watch the Engineering.com webcast replay, sponsored by Siemens (no charge, registration required).
Key takeaways include:
How manufacturers and service providers are expanding data gathered from equipment, both new and old
How edge computing and analytics can turn mass volumes of data into actionable intelligence
How an IIoT platform can help companies more rapidly take advantage of these opportunities
[post_title] => IoT Equipment Health Monitoring (webcast)
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[post_content] => How can companies improve service and gain tangible ROI by remotely monitoring equipment using the IoT? This buyer's guide offers practical advice for companies starting their remote monitoring journey to transform the way they service their equipment whether it's on site, in the field, or at a customer location. At the same time, it offers recommendations to ensure that early projects build a foundation for future machine monitoring and Internet of Things value. As usual, this guide helps companies set functional requirements for their solution, but also addresses implementation, adoption, and partner criteria that help ensure companies get value from their solutions today and well into the future.
Please enjoy the summary below. For the full Buyer's Guide, please visit our sponsor PTC (no charge, registration required).
Table of Contents
Improve Service ROI, Build your IoT Foundation for the Future
Remote Monitoring Drives Service Performance *
Access Equipment and Equipment Data *
Communicate with Equipment *
Leverage the Edge to Pre-Process Communication *
Share Actionable Service Information *
Implementation and Adoption *
Selecting a Strategic Partner *
Next Steps
Buyer’s Guide Checklist *
Improve Service ROI, Build your IoT Foundation for the Future
Companies are leveraging the IoT to digitally transform their business and the results are impressive. But many struggle choosing a place to begin. One proven way to get started is by remotely monitoring machines. This initiative allows manufacturers to quickly achieve IoT value while paving the way for even more substantial benefits over time.
The most common way that companies gain tangible ROI from IoT is through improved service. The IoT lets companies transform service to generate more – and more profitable – service revenue. They do this by moving from reactive to proactive to predictive service, and leveraging advanced technologies like AI, machine learning, and big data analytics. They can also adopt new service delivery processes like remote service. But the most common first step is reducing cost of service through remote monitoring.
This guide briefly shares the tangible, practical first steps companies can take to improve service through IoT remote equipment monitoring and how IoT Platforms help deliver the value. Then, the majority of the buyer’s guide focuses on the important requirements companies must consider to ensure a successful initiative.
Next Steps
Leveraging the IoT can help companies improve service for themselves and their customers by reducing cost and transitioning to proactive and predictive service. Remote monitoring allows companies to identify and resolve issues remotely, providing faster service and increased uptime for the customer while reducing the cost of truck rolls and putting service technicians on site. It can go beyond cost savings to create a new source of revenue from paid upgrades or remotely enhancing equipment capabilities or permissions by “unlocking” enhanced capabilities via a subscription.
*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.
[post_title] => Improving Service with IoT Remote Monitoring (Buyer's Guide)
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[post_content] => How do Top Performers in the chemical industry leverage digitalization in the chemical lab to overcome their innovation struggles? A Tech-Clarity survey shows that chemical companies face a myriad of innovation-related challenges including cost pressure, sustainability, more customer-driven products, and specialized / performance materials. This infographic provides a graphical snapshot of the research sharing that Top Performers are more than three times more likely to have a fully digital lab than their lesser performing competitors. While few have fully digital labs, the benchmarks show that increased digital maturity in the laboratory leads to better innovation and product development performance.
Please enjoy an excerpt of the infographic below, thanks to our sponsor Dassault Systèmes BIOVIA. For more information on the report, you can read a summary of the underlying research report on our site.
For the full infographic and research report and more information, please visit our sponsor Dassault Systèmes BIOVIA and click on the report or infographic in the Resource Center on the right (no charge, no registration required).*This summary is an abbreviated version of the report and does not contain the full content. Links to download the full infographic and underlying repport are available above.If you have difficulty obtaining a copy of the report, please contact us using the "Contact" link below.
[post_title] => How Digital Chemical Labs Drive Innovation (infographic)
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How can companies manage their portfolios and product development processes in order to more reliably hit their product innovation and commercialization challenges? How does digital transformation raise the bar on product portfolio management? Tech-Clarity was commissioned by Planview, Inc. to conduct their Sixth Product Portfolio Management Benchmark Study to find out. The research uncovered five best practices that Top Performers follow more frequently than others, resulting in their higher performance in revenue growth, profit margin expansion, and percent of sales from new products than their competitors. The survey also took a hard look at how digitalization impacts product planning and development, and finds that the transition to smarter, more connected products makes current PPM challenges worse.
This Sixth Product Portfolio Management Benchmark Study surveying more than 400 industry practitioners finds that companies continue to struggle to meet product innovation and commercialization targets. Survey respondents indicate they hit product launch dates just 54% of the time, on average, and meet revenue targets only 55% of the time. New results from the ongoing product development benchmarking research commissioned by Planview show that companies continue to grapple with some of the same challenges they have for the last decade, including having too many projects for their resources. Despite proven best practices for developing successful, pr products, many companies continue to suffer the pitfalls of poor Product Portfolio Management practices.
Digital Transformation Raises the Bar on Product Innovation and the Product Portfolio Management Discipline
Now is the time to address Product Portfolio Management process and performance gaps. New survey questions gauging how the transition to smarter, more connected products and the digital enterprise impacts product innovation indicate that current challenges are about to get worse. This is critical given the major digital transformation facing the manufacturing industry. According to McKinsey’s Why Digital Strategies Fail, only 8% of companies said their current business model would remain economically viable if their industry keeps digitizing at its current course and speed. Manufacturers that don’t successfully digitalize, even the largest companies, stand the risk of losing market share, and they are responding accordingly about 13% are currently delivering smarter, more connected products, another 44% are either actively developing or actively researching them. A further 27% are considering adding them. This is having a significant, direct impact on product – and Product Portfolio Management – complexity.
The Best Practices
In summary, the best practices identified by the benchmarks research show that Top Performers are more likely to:
Have access to more accurate, timely portfolio data to make decisions
Follow portfolio processes more consistently
Reallocate people and money to higher value innovations
Have better portfolio and capacity management and planning
Companies continue to miss their product development targets, most notably time to market and related product revenue goals. Too many still fall victim to common Product Portfolio Management challenges, despite the availability of proven best practice processes and technology. Analyzing the Top Performers provides a roadmap that can help other companies overcome challenges and achieve higher levels of innovation and product profitability. Others can learn by example, recognizing that leading companies have better data, follow more consistent processes, are able to reallocate people and money to higher value innovations, and have better control of resource capacity – enabling all of this with the use of PPM software. The time to improve Product Portfolio Management performance is here. As the benchmark study shows, the move toward smarter, more connected products and digitalization will significantly increase product and product development complexity. Product Portfolio Management best practices can improve development of current products and prepare companies for the heightened challenges of digital transformation. PPM technology is positioned to address real challenges and improve value today and throughout the digital transformation.
*This summary is an abbreviated version of the Executive Brief and does not contain the full content. A link to download the full research is available above.If you have difficulty obtaining a copy of the report, please contact us using the "Contact" link below.
[post_title] => Five Things Top Performers Do Differently to Deliver Profitable, Innovative Products (PPM survey results)
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[post_content] => How can engineers be productive and innovate when suppliers, customers, other departments, and even different design teams use a variety of CAD tools? This webcast shares how CAD interoperability helps companies survive when multi-CAD is simply the reality they live with every day. The webinar shares customer stories and best practices from our recent eBook and includes a number of options that companies can consider to help manage the mayhem. In addition, Autodesk will share how their customers leverage associative interoperability of non-native CAD to help make product development more efficient, even when designs inevitably change.
Register for the Machine Design webcast (no charge, registration required).
Webcast Description
Does this sound all too familiar? Spending hours working on customers designs before we can do any real value-added work. We waste time re-importing design changes from customers and still have to redo all of our modifications like adding ribs or creating tool paths. There is no way we can afford a license for all the different CAD software packages.
Well if it does, you are not alone. CAD interoperability challenges communicating with customers, suppliers and internally is a real beast and leads to significant non-value added work. In this webinar we will discuss the unavoidable reality of multi-CAD and ways to manage the mayhem without wasting so much time and actually thriving!
In this webinar we will cover:
Why multi-CAD impacts productivity and profitability
How CAD Interoperability allows you to overcome the challenges and work better internally, with customers, and with the supply chain
What to look for in your CAD solution
[post_title] => The CAD Interoperability Survival Guide (webcast)
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[post_content] => How can Aerospace and Defense companies leverage the cloud to improve innovation, engineering, and manufacturing across the product lifecycle? We surveyed over 250 companies and analyzed the progress, plans, and success factors for supporting product innovation with cloud solutions of over 70 of these companies that serve the A&D industry. The research analyzes both challenges faced and benefits achieved by A&D companies using cloud-based applications. The eBook shares implementation, adoption, operational, and business benefits of cloud systems and how they impact today's digital A&D 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 summary below for no charge.
For the full report, please visit our sponsor Dassault Systèmes (no charge, registration required).
You can also watch our Tech-Clarity TV episode sharing the research highlights here.
Product Innovation Platforms
Before talking about the evolution to the cloud, it’s important to understand how software for product innovation, engineering, and manufacturing has evolved. CAD and other engineering software tools have allowed Aerospace and Defense (A&D) companies to design products that were previously unachievable. They have evolved to model and simulate new materials, advanced manufacturing methods, and multiple aspects of products to more accurately predict behavior.
Engineering tools are integrated with data and process management solutions that support products, processes, and programs. These product lifecycle tools have evolved to support a broader view of the product and support a wider range of processes ranging from ideation to certification.
Now, the move to the digital enterprise demands more. Software systems must support a more fully integrated approach, enable data-driven design, and support model-based systems engineering. They have to encourage real-time collaboration across disciplines and the supply chain, and support digital continuity where different domains contribute their design perspectives into a comprehensive, cohesive product model.
This is the Product Innovation Platform (PIP), which creates a comprehensive digital thread, supports a cohesive digital twin, and breaks the paradigm of disparate, file-based systems. And, it’s moving to the cloud.
Given that, we conducted a survey to find out how manufacturers are approaching the cloud opportunity. We gathered over 250 survey responses from manufacturing and engineering services firms, and took a closer look at approximately 70 of them that serve the A&D industry. Let’s take a look!
A&D is (Generally) Open to the Cloud
Manufacturers across industries have begun to adopt cloud solutions, and Top Performing manufacturing companies are more open to using cloud solutions, although it’s important to note that this finding is not specific to the Product Innovation Platform. This survey shows that A&D is actually a bit less conservative about the cloud than some might think, at least on a general level. When asked about their company’s strategy or standard for the use of cloud IT solutions, over one-third say they choose the most capable solution, and another 15% favor or use the cloud unless no other software is available. On the other hand, only about one-quarter of A&D companies surveyed say they do not consider or allow cloud.
(more in the full eBook)
A&D has Mixed Views on PIP in the Cloud
Views on the cloud change when related to the PIP. We asked companies about their views on software to support the product lifecycle including CAD, ALM, EDA, CAM, simulation, PDM, PLM, MES / MOM, product analytics, or other related solutions – effectively the components of the PIP. About one-quarter of A&D companies indicate that they use the cloud for some elements of the PIP, and about another one-quarter are implementing, planning to implement, or researching the cloud opportunity.
(more in the full eBook)
Conclusions and Recommendations
Implementing a cloud solution offers benefits along implementation, operational, and business dimensions. While these cloud-specific benefits are important, it’s important to recognize that most companies rightfully place a higher priority on PIP functionality. A&D companies are not willing to trade off the PIP features that directly impact their success drivers – quality, performance, reliability, innovation.
But A&D companies also need to reduce cost. PIP capabilities can deliver on this need, and cloud deployments can further reduce cost even further.
Cloud has value, but A&D companies face a number of challenges when implementing it, including security, performance, and availability. These are important concerns that should be addressed through SLAs, standards, and audit procedures. It’s important to understand, though, that in many ways cloud deployments actually help with these aspects by offering shared services with dedicated specialists.
The cloud also provides unique opportunities not available with traditional implementations. These include instant scalability, “elastic” computing power, and the valued-added services capability viewed very favorably by survey respondents.
A&D has been using the cloud for some time, and are generally open to the cloud, but they’re mixed on the use of cloud for PIP capabilities. This is especially true for suppliers, who are perhaps waiting for the OK from the majority of their OEMs. These views may change with better education about standards and audit processes.
Cloud benefits are available, and they’re compelling. Today’s highly capable solutions are bringing the power of mature PIP capabilities with cloud benefits. We expect to see usage continue to grow, although cautiously.
*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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[post_content] => [caption id="attachment_7006" align="alignright" width="350"] Download a PDF Summary of the Research[/caption]
How can companies improve business results by increasing the digital maturity in their chemical labs? The Digital Chemical Lab, Top Performers Digitalizing Their Chemical Laboratories, shares insights from a survey of over 170 chemical companies examining their lab processes, data, solutions, and digital maturity. The survey benchmarks the level of digitalization against business performance, finding that Top Performers are more likely to employ best practice, digital lab management practices and solutions to drive innovation, agility, and efficiency.
Please enjoy the summary below, or click the report to download a summary of the report (no charge, no registration required).
For the full research and more information including a related infographic, please visit our sponsor Dassault Systèmes BIOVIA and click on the report in the Resource Center on the right (no charge, no registration required).
Table of Contents
Executive Overview
Chemical Companies Face Multiple Business Challenges
Operational Challenges in the Lab Make Improvement Hard
Why Digitalize? The Status Quo Won’t Scale
What’s Driving Chemical Companies Digital?
Digitalization in the Lab – When, not If
Digitalization Falters beyond the Lab
Identifying the Top Performers
Top Performers Have Better Capabilities for R&D and the Lab
Top Performers are More Digitalized
Identifying Best Practices for the Digital Chemical Lab
Prerequisites for the Digital Chemical Lab
Digital Chemical Lab Basics
Digital Best Practices for the Chemical Lab
Enabling Technology for the Digital Chemical Lab
Enabling the Digital Chemical Lab with a Solution Platform
Conclusion
Recommendations
About the Author
About the Research
Executive Overview
Chemical companies rely on R&D and their laboratories to innovate so they can compete in increasingly crowded, global markets. In fact, innovation emerged as the most common problem in our recent chemical industry survey, with one-half of respondents citing it as their top business challenge (Figure 1). Of course, chemical companies face a host of shared challenges that they must address, including managing costs, capturing global markets, and driving sustainability.
Chemical companies also report related, operational challenges in the lab (Figure 2) that likely contribute to their business challenges and make change difficult. These challenges include research productivity, inability to find data, difficulty with new product development, traceability, and more.
Digitalization can help address these challenges by driving innovation, agility, customer-centricity, and quality. We surveyed over 170 chemical companies to understand their intent, status, and outcomes related to digitalizing the chemical laboratory. We used the survey to analyze digital best practices to see which correlate with higher performance and help companies meet their business objectives. Our key findings include:
Most chemical companies have started to adopt digitalization
Digital transformation is further along in the lab than beyond the lab
Chemical companies report varied levels of digital maturity
We identified the industry’s Top Performers, those with better revenue growth, margin expansion, innovation, and time-to-market performance, to understand their digital practices. We found that these leaders exhibit higher digital maturity than other companies, particularly in more advanced capabilities like chemical simulation and knowledge management. They also report much better operational capabilities in the lab. How do Top Performers reach these higher levels of performance? Top Performers:
Are more digital in the chemical laboratory
Have invested in more digital lab best practices
Use more specialty scientific software
Value a platform approach to integrate and support the digital enterprise
These findings help us understand what Top Performers do differently to achieve their higher levels of success. They also serve as a model for chemical companies looking to improve innovation and overcome challenges – and most importantly drive better business results. Let’s take a look at what we learned.
Conclusion
Chemical companies are challenged to improve their innovation and product development performance while controlling cost. They face significant operational issues that make these business improvements hard to achieve. Digitalization holds significant promise to address these issues and improve performance because it’s proven to accelerate the pace of innovation, increase agility, and improve efficiency.
The transition to the digital chemical lab has begun. Today, however, most chemical companies have only partially digitalized. Top Performers, though, have greater digital maturity than their lesser-performing competitors. They’ve adopted more digital R&D and lab capabilities, particularly when you look beyond the basics to best practices.
Top Performers have implemented more specialized R&D and lab management systems to support their best practice processes. Based on the survey results, we believe that these capabilities help the Top Performers achieve better operational R&D and laboratory performance and drive better business performance. Our overall conclusion is that digital best practice processes and chemical laboratory management solutions provide a competitive advantage that helps chemical companies drive higher levels of innovation and profitable growth.
Finally, we believe that digitalization will lead to significant market disruption across the chemical industries and result in a significant change in market leadership. Digital transformation supported by best practices and a platform of integrated R&D and laboratory solutions will be a key differentiator to enable the future Top Performers that will lead the industry. The time to digitally transform the chemical laboratory is now.
Recommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations. Chemical companies should:
Ensure the digital chemical lab prerequisites and basics are in place
Pursue digital laboratory best practices including reuse, simulation, and knowledge management to differentiate and drive higher levels of innovation
Leverage specialized laboratory and R&D software to drive better business performance
Pursue a chemical laboratory systems platform strategy to further improve performance and gain a market advantage
Leverage digitalization processes, tools, and techniques to take advantage of the current market disruption and gain market position
Copyright Notice
Unauthorized use and/or duplication of this material without express and written permission from Tech-Clarity, Inc. is strictly prohibited. This report is licensed for distribution by Dassault Systèmes BIOVIA.
*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.
[post_title] => The Digital Chemical Lab (survey results, white paper)
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[post_content] => How do top performing companies plan and deliver profitable portfolios of smarter, more connected products? Join this webcast to hear what recent survey results tell us about developing innovative products in the digital age. The webcast includes results from the 6th Product Portfolio Management Benchmark study, conducted by Tech-Clarity and sponsored by Planview.
Hear Tech-Clarity's Jim Brown and Planview's Carrie Nauyalis share their insights about best practices to find out some surprising things that companies that deliver more innovative, profitable product portfolios than their competitors do differently.
Register for the Planview sponsored webcast now (no charge, registration required).
[post_title] => Secrets to Delivering Smart, Connected Product Portfolios (webcast)
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[post_content] => How can manufacturers bridge the knowledge gap between design and procurement?The Manufacturer's Guide to Bridging the Engineering-Purchasing Gap shares our perspective on how manufacturers can take a digital approach to sharing critical BOM data from Engineering with Purchasing so they can reduce cost, improve efficiency, and prevent late shipments due to part shortages.
Please enjoy the article below, or click the title to download the full PDF (no charge, no registration required).
For more information on closing the Engineering-Purchasing gap, please visit our sponsor OpenBOM.
The Manufacturer's Guide to Bridging the Engineering-Purchasing Gap
How can manufacturers deliver every customer order on time without incurring excess cost and delays from part shortages? They have to streamline operations and information flow across departments including Engineering and Purchasing. Today’s disconnected processes and systems aren’t acceptable when people expect business systems to work as well as the Amazon app on their smartphone. It’s time for manufacturers, big and small, to start embracing digital approaches to improve operational performance.
A Practical Shift to Digital
Manufacturers are going digital to meet today’s market demand for innovation and agility. The status quo isn‘t good enough any more, and those that hold on to old ways of running a manufacturing company using emails and spreadsheets will find it hard to compete.
But “going digital” doesn’t have to mean huge consulting fees and expensive software. It can be very practical. For example, companies can choose a problem area that causes them trouble, such as collaborating between Engineering and Purchasing to build prototypes or small production runs, and take a digital approach to improving it.
The Design to Procurement Gap
Let’s look at closing the communications and information gap between design and procurement. Engineering and Purchasing need to be on the same page to meet customer ship dates or risk losing revenue and customer satisfaction. A simple thing like sharing part requirements gets challenging with different configurations, changing designs, and dynamic supply chains. Experience shows that this complexity leads to errors in the world of office documents, shared drives, emails, and other ad hoc tools that lead to using outdated and incorrect information.
Manufacturers need to close the information gap by providing centralized, shared information in a digital format. Information buried in a spreadsheet or a CAD file isn’t much more effective than hand-written notes on a whiteboard. Some people have visibility to the information, and hope that it’s accurate, but others are left guessing. The core of this communication is parts, organized in BOMs, to let people know what, when, and how much they need to buy and make. Beyond this, companies need to gather purchasing information that’s typically spread out in multiple catalogs or websites to make a buying decision.
The process is challenging in any organization, whether the responsibility is on one person, one department, multiple departments, or spread out across a global supply chain that includes contract manufacturers. More importantly, it leads to late orders and excess cost. A digital, cloud-based approach can help streamline the process, improve speed, and reduce errors. Let’s look at it from three different perspectives – the Engineering, Purchasing, and Operations views.
The Engineering Perspective
What does Engineering need from the design – procurement workflow? They want to make sure that everyone downstream has the data they need to make their products right. But they don’t want to have to reenter a lot of information in a complex tool to do it. And if it’s cumbersome, they’ll wait until the information is finalized so nobody sees it until the last minute. They want to export their BOMs from their CAD tool, add data like materials or other specs, pull in standard part data where they can, have it all easily accessible to the right people, and have everything stay in sync when they make changes. They would also love to be able to access a cohesive design history covering all revisions and changes, a complete digital thread of the product development process.
The bottom line is that they want to make sure whoever is buying parts, even if it’s a contract manufacturer on the other side of the planet, has accurate part requirements data so they can get it right and fulfill their design intent.
The Purchasing Perspective
What does the Procurement Specialist need from the design – procurement workflow? Clearly they need visibility to the parts they need to order in an accurate, timely parts list. They need to know what’s needed, when, and with what specifications as soon as possible, even if it’s not final, so they have time to plan. They also want to hear about changes immediately, before it’s too late and they have to expedite and/or return parts.
Purchasing also wants accurate part information for themselves and others to make the right decisions, to have everyone use the same part numbers so they can manage inventory and where-used, and optimize part buys. They want to optimize their procurement strategy by guiding Engineers to make the right part selections. But they want this without having to use a complex tool or enter information manually that could be imported from suppliers, websites, or catalogs.
The bottom line is they want accurate data so they can make sure Manufacturing has the parts they need on-hand, without overpaying or carrying too much inventory.
The Operations Perspective
Operations just wants everything to run smoothly. They want everybody to be on the same page so nobody makes mistakes and buys or builds the wrong thing. They want this so that customers aren’t upset about missed ship dates and they don’t suffer from excess cost from poor contracts, rush shipping, or excess inventory. They want to avoid lost productivity and expediting missing or lost parts. They also need to manage spend, so they want to make sure they’re getting the best pricing from multiple suppliers, catalogs, and/or websites.
The bottom line is that they want to reduce risk and protect revenue by keeping everyone coordinated to get the product out of the door. They can’t afford ad-hoc tools that don’t work for everyone, but also don’t have time to train engineers and purchasing people to be power users for complicated software. And they probably don’t have the appetite to install new hardware and software, and would prefer simple tools that work but don’t suffer from the shortcomings of office productivity tools.
Key Takeaways
The common thread across of these roles is the desire for accurate data and simplicity. Companies can’t afford disconnects in today’s agile, digital-speed world. They have to avoid the errors and inefficiencies of general tools like spreadsheets and generic cloud file storage, leverage common data to avoid mistakes in the supply chain, and develop the ability to easily gather information to make the right buying decisions.
It’s time for manufacturers to analyze their basic requirements to close the design to procurement gap, find a solution that fits their needs, and do so in a way that’s consistent with their willingness to take on the learning curve, cost, and complexity of enterprise solutions. It’s a good idea to start small and grow, but stay away from dead-end office automation tools or generic file sharing solutions that don’t address their collaboration needs. Companies of all sizes should consider easy to adopt, easy use, cloud-based solutions to streamline processes and close information their information gaps.
[post_title] => Bridging the Gap Between Engineering and Purchasing
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[post_content] => How does product design, development, and engineering need to change in order to support digital products?
Key Considerations for Selecting a Smart, Connected Product Design Solution eBook shares that today's new product development (NPD) processes simply aren't comprehensive enough to effectively design smart, connected products. What do manufacturers need to look for in their engineering software solution to support products in the IoT era and support their digital transformation? The guide shares requirements that manufacturers can use to select the best software for their needs considering functionality, selecting the right partner, and what to look for to ensure effective implementation and adoption. The eBook shares considerations for multiple aspects of the engineering process ranging from conceptual design through validation and verification.
Please enjoy the summary below*.
For the full report, please visit our sponsor PTC (no charge, registration required).
Product Development Needs to Evolve to Support Today’s Products
Manufactured products have evolved rapidly over the last decade or so. Items ranging from cars to coffee makers have transitioned from primarily mechanical things to smart, connected products that interact with other products as part of a system in a system of systems world.
These products are much more than just a piece of equipment. They incorporate intelligence, data, and the ability to communicate with cloud and corporate software that together can be leveraged to change the customer value proposition. Some companies are even offering their products as a service (PaaS), charging for usage or output instead of the product delivering it.
Today’s new product development (NPD) processes simply aren’t comprehensive enough to effectively design smart, connected products. What needs to change? Companies need to:
Include all functional departments early in the NPD process, for example inviting corporate IT to specify cloud and enterprise system enhancements
Change the product design process to incorporate new decisions such as where to place sensors
Adapt the product innovation process to take advantage of new insights available from smart, connected products in the field, including actual operating conditions
Conclusions and Recommendations
It’s time for companies to make the transition to designing smart, connected products. The business benefits are compelling, and we believe that those that implement these capabilities first will put their competitors at a disadvantage.
To adapt, companies need to make changes to their NPD processes and technology. They need to involve more disciplines early in the design process, include a new series of decisions in their design process, and learn from real product performance by “closing the loop” between design and operation.
In order to take advantage of the digital opportunities, companies must evolve modeling, design collaboration, and simulation to support connected design including design decisions related to:
Conceptual design and requirements
Data design
Sensor strategy
Communication plan
Validation and verification
In addition to finding the right software, they should focus on implementation and adoption needs to make sure their investments will result in improved business results. Lastly, they should make sure to partner with a company that has both business and technical expertise to help direct them through their transition. This partner should also be investing in the IoT and digital enterprise so they can offer guidance along the journey and provide an opportunity to grow as market needs evolve.
It's time to act. With the move toward a sharing economy, we believe that companies that simply develop and sell products will put themselves at a significant disadvantage to companies that design, develop, and stay in touch with their products throughout the product’s life. Companies that don’t embrace digitalization and start offering more than a physical product stand the risk of being commoditized.
*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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PLM helps manufacturers improve innovation and product development performance through streamlined processes, centralized data, and integrated tools. It’s a key part of any manufacturer’s digitalization strategy. Learn how manufacturers are leveraging the cloud to remove the barriers to achieving the strategic benefits of Product Lifecycle Management. Join an interesting panel discussion between Tech-Clarity, Sogeti, and Microsoft to learn how implementing PLM in the cloud provides implementation, operation, and business benefits and gives manufacturers a low risk, high reward way to progress on their digital transformation.
Register for the Sogeti sponsored webinar now (no charge, registration required).
[post_title] => PLM in the Cloud Webcast with Sogeti, and Microsoft
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[post_content] => How can retail companies improve their decisions to survive in today's complex omnichannel environment and anticipate changes in trends in a dynamic and volatile market? Can predictive retail analytics help? If so, what should retailers look for in a solution?
The value of connecting multiple databases on a single platform
How applying machine learning to analytics helps retail companies
Examples of how predictive analytics solutions can help retailers
Access the event here.
[post_title] => Retail Analytics Solutions (webcast)
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[post_content] => How can manufacturers get more value from their digital initiatives by leveraging the Internet of Things (IoT)? Manufacturers who embrace digitalization gain increased agility, innovation, speed, quality, and profitability in design, development, manufacturing, and the service lifecycle. One of the key enablers of these improvements is establishing a closer connection between product models and how physical products operate in the field. The digital twin leverages detailed 3D models, IoT data, and analytics to significantly change the relationship manufacturers have with their products and their customers, driving new sources of value for both.
In this Engineering.com webinar sponsored by Siemens PLM, Tech-Clarity's Jim Brown will explore how companies that embrace digitalization and the digital twin will displace competitors who stick with the status quo.
Key takeaways include:
How a digital twin helps create competitive differentiation
How manufacturers can transform product performance and service through better product insights
How a digital innovation platform supports the digital twin
Register for the webcast now (no charge, registration required).
[post_title] => Enabling the Digital Twin with IoT (webcast)
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[post_content] => How can medical device companies balance quality, innovation, compliance, and profitability? Where does a PLM solution fit in? Is it possible to achieve a single source of truth?
Listen to Claus Gärtner, Head of Operations & Quality IT at Roche Diabetes Care, René Zoelfl PTC Life Sciences Development Manager, and Tech-Clarity's Michelle Boucher discuss how to support the development of medical devices. This discussion was an interactive panel discussion highlighting topics such as:
The PLM journey taken by Roche Diabetes Care
What drove Roche Diabetes Care to adopt a PLM system
The results Roche Diabetes Care have achieved with PLM
Perspectives of software solution selection criteria to support quality initiatives.
Access the event here.
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[post_content] => How can manufacturers quickly gain value from remote equipment monitoring using the Internet of Things to begin their digital and service transformations? The Monitoring Equipment with IoT Quick Start Guide eBook offers pragmatic advice for companies that want to jump-start their IoT initiative with a practical approach that leads to much more significant value over time.
Please enjoy the summary below.
For the full eBook click the title to download the full PDF(no charge, no registration required) thanks to our sponsor PTC.
Jump-Start Your IoT Initiative
Manufacturers are making major business improvements using the Internet of Things (IoT). They’re delivering value to customers in new ways and exploring new business models like selling outcomes versus products or shifting to a predictive service model. Some companies are well on their way to this strategic value, while for others it may seem out of reach.
How can your company jump-start your IoT initiative? One proven way to get started with IoT is by remotely monitoring machines, either in your own plants or in your customers’ facilities. This gives you the real-time information you need to quickly identify failures and fix equipment more efficiently, improving service while reducing cost. Remote equipment monitoring provides value in the short term and helps develop a strong analytics foundation for your broader IoT strategy.
This Quick Start Guide shares suggestions on what companies can do to get equipment connected, start gathering data, and put the data to use. Let’s get started!
Next Steps
Remote monitoring using the IoT can provide rapid value by helping your company gain visibility to your equipment. The value is strategic, but getting started doesn’t need to be intimidating. You can start small and grow value over time. Your investment can provide a valuable foundation to build on as you connect more equipment or implement more advanced features.
It’s important to find an IoT platform that offers a variety of predefined connectivity and application options so you don’t need to undertake a large integration project from scratch. Find a solution and IoT-savvy partner that can get you started with a simple project, but that offers the business knowledge and advanced tools needed to help you expand on your early success.
Remote equipment monitoring lets companies reduce service cost, increase service revenue, develop stronger relationships, and start the transition to proactive and predictive service. It’s time to get started to improve value for your company and your customers.
*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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[post_content] => What steps should you take to transform your product design processes so you can develop smarter products?
Tech-Clarity's Top Five Tips to Transform Product Design for Smarter Products shares advice to help companies on their journey to develop smarter products. For many, making products smarter and connected is a key product trend that is becoming increasingly important for innovation and competitivedifferentiation. Plus many customers are starting to expect it. However, successfully developing smarter and connected products requires changes to your design process. At the same time, it's hard to know what you don't know. As you embark on that journey toward smarter and connected products, there will be lots of lessons learned. Based on survey research, Tech-Clarity has identified five tips to give you some hindsight and help you on that journey with the benefit of some of the lessons learned by other.
Please enjoy the summary* below.
For the full eBook, please visit our sponsor SOLIDWORKS (free of charge, registration required).
The Journey Toward New Development Approaches
The emergence of smart, connected technologies is enabling unprecedented innovation. We have public trash cans that let trash collectors know when they need to be emptied. Pill bottles that remind you to take your medication. Complex machinery that notifies you when it needs servicing. The opportunities and growth potential seem limitless. Technology has become so critical, 52% of companies developing smart products fear losing market share unless they continually make products smarter. On top of that, 47% worry about reduced revenue.
With this in mind, we can expect to see a continual increase in the amount of software and electronics in products. Even 25% of companies that have not already made their products smarter, plan to add software and electronics over the next five years.
To successfully take advantage of the opportunity and transform products into intelligent systems, companies should embark on a journey to perfect development processes and manage the additional complexity. This eBook outlines steps to make your journey to transform your products a success.
You Don’t Know What You Don’t Know
While emerging technologies open doors for innovation and opportunity, they introduce new challenges. However, as you start your journey, it is hard to know what you don’t know. Learning from the experiences of others to minimize or avoid common challenges should be a first step. Even if you have already started your journey, knowing where to focus your energy for improvement can minimize risk. Based on the experiences of over 180 manufacturers, the top six challenges of making smarter products are:
Products become much more complex
Knowledge silos / lack of cross-functional knowledge
Ensuring product requirements are met
Lack of visibility into the impact of design decisions across disciplines
Tools are incompatible across engineering disciplines
Identifying system level problems sooner
These challenges create barriers during your journey to improve your development process. Overcoming them requires putting the right processes and technology in place.
*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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How can manufacturers design systems with greater confidence the system will work as designed?
Tech-Clarity's Smart Systems Buyer’s Guide for Systems Engineers and IoT Solution Architects helps manufacturers develop selection criteria to evaluate software solutions to support system design. The guide targets systems engineerings, IoT solution architects, and others involved with designing systems.
Tech-Clarity’s Buyer’s Guides go beyond software functionality to provide a framework of requirements that impact implementation success and long-term ROI.
Please enjoy the summary below, or click the report to download a PDF overview.
For the full report, please visit our sponsor, PTC, here(free of charge, 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
Executive Overview
In today’s world, fierce global competition is driving companies to seek new ways to competitively differentiate their products. Many companies are incorporating embedded software into their products to set their products apart from the competition. Embedded software offers opportunities to incorporate intelligence into a product as well as offer customers a more personalized experience. The Internet of Things (IoT) takes this even further by creating exciting possibilities for new and differentiated services for products with smart, connected devices.While bringing together mechanical components, electronics, and software presents exciting opportunities for innovation, it also brings unique challenges and adds new levels of complexity to today’s products and product development processes. The same goes for connected products as you add sensors, streaming data, and an ecosystem of connected systems. Whether you are a systems engineer or IoT solutions architect, expert systems engineering practices are critical to the success of today’s products. An essential part of implementing expert systems engineering practices is having the technology to support them. This buyer’s guide will help manufacturers select the right software to support systems engineering.
This guide is composed of 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 investigate when selecting software tools to support systems engineering.
Figure 1: Systems Engineering Evaluation Framework
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. With expert systems engineering practices, companies will be even more competitive in ways that will lead to higher growth and greater profitability.
This framework will be useful to a variety of roles, not just systems engineers. As companies develop IoT enabled smart connected devices and products, they will struggle with many of the same challenges that expert systems engineering practices solve. Many of these IoT related roles are newer, but involve end-to-end responsibility for designing and architecting the overall system as well as mapping business needs to the system and technical requirements. Functions also include developing the technical specifications for the connected system. These roles include, but are not limited to titles such as:
IoT Solutions Architect
DevOps IoT
Internet of Things Solutions Engineer
M2M and IoT Product Management and Engineering
Technology Manager, Software Engineering (IoT)
Solutions Engineer (IoT)
Principal Technical Architect (IoT)
Innovation Manager for Industry 4.0
Product Manager
This guide is not an all-encompassing requirements list. It provides a high-level overview of systems engineering needs. In addition to the systems engineering capabilities discussed in this buyer’s guide, companies should also consider needs for the tools of individual engineers for each engineering discipline.
Conclusion
Expert systems engineering practices are key to taking 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, electrical, and software components 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 means there is risk things will go wrong. The impact of these problems can have a significant business impact and hurt the profitability of the product. Implementing expert systems engineering practices, with the right software tools to support them, can manage this complexity, making it easier to bring profitable products to market successfully. 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 by providing 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 important to ensure that functionality, service, vendor, and special requirements are all considered when selecting a solution.
Recommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations:
Identify and weigh systems engineering requirements based on company needs, existing applications, industry, and unique product and process requirements
Use high-level requirements such as the ones in this guide to evaluate solutions based on business fit before engaging in detailed evaluations
Consider long-term business and process growth needs and the potential to scale across product lines, departments, and engineering silos
Consider all stages of systems engineering from process, requirements, design, and validation when investing in systems engineering solutions
Think about all roles that can benefit from systems engineering best practices such as IoT solution architects
Select a vendor who will be a trusted partner
[post_title] => Smart Systems Buyer’s Guide for Systems Engineers and IoT Solution Architects (white paper)
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[post_content] => How can manufacturers ensure they get the most value from a new PDM solution? The PDM Buyer's Guide provides criteria for companies to select the right Production Data Management system to manage the complexity of today's products and product development environments. Manufacturers have many choices for managing critical CAD files and product data, including shared drives and the modern equivalents - DropBox, Drive, Google Drive, and a host of other options. But our research shows that they'll get more value from a structured, collaborative data management solution designed to support product development and further into the product lifecycle. This paper shares requirements for the basic capabilities companies need from PDM - Designing, Accessing, and Sharing product data.
Our Buyer's Guides look beyond software requirements to the other elements that help companies get value from their solutions, including criteria to consider for implementation, adoption, service, and vendor selection. This guide also covers special needs including advice for smaller and larger manufacturers and shares considerations for addressing some specific industry needs and supporting the transition to the digital enterprise.
Please enjoy the summary below, or click the report to download a PDF overview (no charge, no registration required).
For the full Buyer's Guide, please visit our sponsor PTC (no charge, registration required).
Table of Contents
Introducing the PDM Buyer’s Guide
The Product Data Management Imperative
Analyze PDM Capabilities
Assess Service Requirements
Consider Vendor Requirements
Identify Unique Company Needs
Conclusion
Recommendations
About the Author
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. Manual and ad-hoc approaches such as shared folders, FTP, Dropbox, box, and hard drives are simply not good 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 for your business has a large impact on productivity, product success, and profitability.The PDM Buyer’s Guide is a reference tool to provide direction about what to look for when selecting a PDM system for your company. The guide is composed of four sections covering software functionality, service requirements, vendor attributes, and special company considerations. Each of these sections includes a checklist with key requirements to investigate when selecting PDM software. The guide focuses on common requirements that form the foundation of PDM for manufacturers:
Getting files under control so people can find the right revision with confidence
Making sure concurrent updates don’t overwrite each other to avoid “the last save wins” syndrome
Making information easily accessible and consumable to teams outside of Engineering for reviews and downstream processes
Safely sharing information with customers, partners, and the supply chain
Ensuring intellectual property (IP) is captured and securely accessible regardless of who stored it
Getting away from complicated shared drive structures that lead to errors
Making sure people don’t manufacture or purchase against the wrong drawing
Providing “one version of the truth” versus multiple copies of designs
Beyond these basics, there are special considerations for smaller companies and for the largest of enterprises. There are also special considerations for some industries. The guide addresses these and then goes beyond software functionality to focus on the entire experience of owning and operating the solution. The guide and associated checklists include product, infrastructure, implementation, service, and business requirements – all of which impact the benefits received and total cost of ownership (TCO) of PDM.
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.
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. These companies start with PDM and evolve though 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.
In addition, PDM is becoming the core 3D foundation for the digital enterprise, supporting advanced initiatives like the Internet of Things (IoT), model-based design (MBD), and three dimensional augmented / virtual reality. Modern PDM / PLM systems should enable a product digital twin that can serve as the central foundation on which to consolidate (or view) a variety of product-related data captured in systems across the enterprise. It’s important to consider these needs when selecting your software and ensure that your solution has the capability to expand with your growing needs.
Conclusion
PDM helps manufacturers address market complexity and improve business performance. As Tech-Clarity’s Managing Engineering Data concludes, “Product data management is the fundamental building block of any engineering software strategy and helps companies get the most out of their precious engineering resources.” 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 business continues to digitalize
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.
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.
Reccommendations
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 evaluations
Consider using more simple, commodity technical solutions like cloud or managed services solutions for smaller companies, companies that wish to move quickly, or those with limited IT resources
Take user adoption into account, including simplified access and increased visualization for non-engineering resources
Consider using more full-featured, scalable solutions for larger organizations that have more demanding process and scalability needs and can afford the IT resources required to support capabilities such as site synchronization
Take into account long-term business and process growth needs including digitalization and IoT initiatives
Consider the potential to expand to a more capable PLM system when choosing a PDM system, but start small and get value along the way during implementation
*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.
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[post_content] => How can monitoring equipment remotely provide value and help get your IoT initiative started? Jim Brown joins PTC's Michael Anderson for a webcast discussion to find out. Jim will share perspectives from his research including an overview of how remote equipment monitoring via the IoT can help drive significant service improvements. Jim will share tips from his upcoming Remote Equipment Monitoring Quick Start Guide including key things manufacturers should consider as they consider an initiative or select a solution to support this aspect of their digital transformation. Jim and Michael will also answer audience questions.
Register for the webinar now (no charge, registration required)
[post_title] => Jumpstarting IoT with Remote Equipment Monitoring (webcast)
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[post_content] => Tech-Clarity research shows that the majority of manufacturers believe that digitalization is important or critical to achieving their business strategy (see figure). Over one-third say that it’s critical. Digitalization in medical device design and manufacturing has significant promise, but what does it actually mean?
Medical device companies, already struggling with how to address critical initiatives like UDI and the Case for Quality, are inundated with information about “digitalization” accompanied with a host of buzzwords including Digital Twins, Digital Threads, and more. How do they really apply to the design, approval, production, and lifecycle management of medical devices? We’ll try to put it into practical terms.
Digital Thread
Let’s start with the digital thread. That’s probably the most straightforward concept and one that provides tangible value. The digital thread, in its simplest definition, is the collection of information used to define, engineer, and develop a product. Ideally it moves beyond the manufacturer into the in-service part of the equipment lifecycle. It offers a view of the digital continuity of the life of the device.
The value for medical device companies, in a nutshell, is end-to-end traceability. It’s the connection between everything from patient needs and early requirements through the patient experience, including post market surveillance requirements required by the EU MDR. It provides a broad base of information that allows medical device companies to analyze and learn from history, for example tracking down root causes for a CAPA.
The digital thread also clearly supports regulatory requirements related to these needs including the DHF and UDI, including all of the local variants of the regulations. In addition, the digital thread also provides an integrated source of data that can be used to prepare submission documentation. With the digital thread as the trusted data source, medical device companies can automate much of the process to generate these crucial reports.
Digital Twin
One of the key contributors to the digital thread is the Digital Twin. The digital twin has multiple definitions, but it starts at the core as a complete, digital model of the device. It incorporates a holistic view of the design to a level of granularity that companies can accurately simulate and predict device performance and behavior. There is clear overlap with the digital thread in this part of the definition.
The value of the digital model for medical device companies is a cohesive view of the device. It allows people from various disciplines to contribute their part of the design and see it in the context of the whole product. It allows engineers to analyze and optimize performance early in the product lifecycle, catching errors and improving performance in silica before physical prototypes are developed. As regulatory bodies get more comfortable with simulation data, the digital twin may also play a big part in reducing the length and cost of clinical trials. The digital thread also delivers quality management and regulatory value including the development of the DMR.
Connected Digital Twin
The value of the digital twin expands dramatically when it goes beyond device production and into usage. Some would say a digital twin without connectivity isn’t a complete twin, but regardless of definitions a digital model is highly valuable. But a connected one adds significantly greater value.
The rise of the IoT adds a new dimension to the value available from the digital twin. Companies can collect real-world device performance and associate it back with the intention of the design model. This can help identify issues where devices are not performing as designed, and may provide an early indicator of a potential variance.
A second aspect of the digital twin is identifying differences between predicted and actual device performance where the device is operating as designed, but not as intended. In these cases, there are gaps in the simulated performance of the digital model that can be addressed to improve simulations and understanding of how devices perform in the field.
Medical device companies gain significant value from the connected digital twin. It rounds out the information in the DMR and supports a more robust data set for UDI. It could also be used early in the lifecycle to help support clinical trials, as well as other regulatory demands throughout the lifecycle.
Digital Twin of the Plant
Another aspect of the digital twin is creating digital twins of the equipment used to produces devices. Companies can create fully functioning models of machines, lines, and plants to design, simulate, and optimize production. As with the digital twin of the product, connecting the digital twin provides even greater value. In this case, it may include the IIoT in addition to the IoT.
The digital twin of the plant helps medical device companies validate production methodology, SOPs, and set critical control points to improve control, reduce variability, and improve quality. It can also be used to validate process control intent with regulatory bodies. These twins, along with the digital twin of the device (which should be integrated) can also help automate regulatory submissions. Again, we see significant overlap in the use of digital tools in the medical device industry.
Analytics
The final piece of the puzzle we’ll discuss today is data analytics. Life sciences companies have been using analytics in multiple aspects of their business for quite some time. The digitalization of the underlying information in the design, engineering, manufacturing, and use of the device dramatically expands the opportunities. Companies now have a much broader data set to analyze and transform into intelligence.
Medical device companies can leverage big data analytics in conjunction with the digital twin and digital thread to identify trends and correlations previously hidden in non-digital or non-integrated data sets. Analytics can be used in multiple phases of the device lifecycle, from identifying process control parameters drifting toward spec limits to analyzing adverse event data in the field. This can make existing processes better, for example being able to more quickly identify root causes for CAPAs. It can also support newer requirements like post market surveillance in the EU and the upcoming shift to focusing on patient outcomes. It can also benefit patients, for example predictive analytics may be able to identify potential failures prior to their occurrence and prevent adverse events. Finally, additional insights may create a new source of innovation that leads to new and better treatment options.
IoT
The last area to discuss is the IoT. We’ve already mentioned it while discussing the earlier digital topics, it’s hard not to given it’s significant potential to change the relationship between medical devices, the manufacturer, healthcare professionals, payers, and the patient. But there is much more to this topic, so we’ll save this for a later post.
Our Take
Digitalization of the medical device industry takes the value of new technologies and techniques and extends them to improve both company profitability and patient outcomes. In the end, the buzzwords represent new capabilities with real potential to help medical device companies innovate, drive rapid product design, speed approvals, improve quality, and achieve higher levels of compliance. These are all important for them to continue their mission to improve patient welfare in today’s complex healthcare environment.
You can find more information about digitalization for medical devices from our sponsor, Siemens PLM.
You can also find more information from Tech-Clarity on digitalization in the medical device industry please see our The Digitalization Opportunity for Medical Device Companies (video) or Digitalization in the Medical Device Industry (animation).
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Tech-Clarity research shows that the majority of manufacturers believe that digitalization is important or critical to achieving their business strategy (see figure). Over one-third say that it’s critical. Digitalization in medical device design and manufacturing has significant promise, but what does it actually mean? Medical device companies, already struggling with how to address critical initiatives…
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How can manufacturers ensure they get the most value from a new PDM solution? The PDM Buyer’s Guide provides criteria for companies to select the right Production Data Management system to manage the complexity of today’s products and product development environments. Manufacturers have many choices for managing critical CAD files and product data, including shared…
How can monitoring equipment remotely provide value and help get your IoT initiative started? Jim Brown joins PTC’s Michael Anderson for a webcast discussion to find out. Jim will share perspectives from his research including an overview of how remote equipment monitoring via the IoT can help drive significant service improvements. Jim will share tips from his upcoming Remote…