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Imagine you are a supplier working for several customers, such as big OEMs or smaller companies. In Dec 2020, I wrote about PLM and the Supply Chain because it was an underexposed topic in many companies. Suppliers need their own PLM and IP protection and work as efficiently as possible with their customers, often the OEMs.
Most PLM implementations always start by creating the ideal internal collaboration between functions in the enterprise. Historically starting with R&D and Engineering, next expanding to Manufacturing, Services and Marketing. Most of the time in this logical order.
In these implementations, people are not paying much attention to the total value chain, customers and suppliers. And that was one of the interesting findings at that time, supported by surveys from Gartner and McKinsey:
- Gartner: Companies reported improvements in the accuracy of product data and product development as the main benefit of their PLM implementation. They did not see so much of a reduced time to market or reduced product development costs. After analysis, Gartner believes the real issue is related to collaboration processes and supply chain practices. Here the lead times did not change, nor did the number of changes.
- McKinsey: In their article, The Case for Digital Reinvention, digital supply chains were mentioned as the area with the potential highest ROI; however, as the image shows below, it was the area with the lowest investment at that time.
In 2020 we were in the middle of broken supply chains and wishful thinking related to digital transformation, all due to COVID-19.
Meanwhile, the further digitization in PLM (systems of engagement) and the new topic, Sustainability of the supply chain, became visible.
Therefore it is time to make a status again, also driven by discussions in the past few weeks.
The old “connected” approach (loose-loose).
A preferred way for OEMs in the past was to have the Supplier or partner directly work in their PLM environment. The OEM could keep control of the product development process and the incremental maturity of the BOM, where the Supplier could connect their part data and designs to the OEM environment. T
The advantage for the OEM is clear – direct visibility of the supplier data when available. The benefit for the Supplier could also be immediate visibility of the broader context of the part they are responsible for.
However, the disadvantages for a supplier are more significant. Working in the OEM environment exposes all your IP and hinders knowledge capitalization from the Supplier. Not a big thing for perhaps a tier 3 supplier; however, the more advanced the products from the Supplier are, the higher the need to have its own PLM environment.
Therefore the old connected approach is a loose-loose relationship in particular for the Supplier and even for the OEM (having less knowledgeable suppliers)
The modern “connected” approach (wins t.b.d.)
In this situation, the target infrastructure is a digital infrastructure, where datasets are connected in real-time, providing the various stakeholders in engagement access to a filtered set of data relevant to their roles.
In my terminology, I refer to them as Systems of Engagement, as the target is that all stakeholders work in this environment.
The counterpart of Systems of Engagement is the Systems of Record, which provides a product baseline, manufacturing baseline, and configuration baseline of information consumed by other disciplines.
These baselines are often called Bills of Information, and the traditional PLM system has been designed as a System of Record. Major Bills of Information are the eBOM, the mBOM and sometimes people talk about the sBOM(service BOM).
Typical examples of Systems of Engagement I have seen in alphabetical order are:
- Arena Solutions has a long-term experience in BOM collaboration between engineering teams, suppliers and contract manufacturers.
- CATENA-X might be a strange player in this list, as CATENA-X is more a German Automotive consortium targeting digital collaboration between stakeholders, ensuring security and IP protection.
- Colab is a provider of cloud-based collaboration software allowing design teams and suppliers to work in real time together.
- OnShape – a cloud-based collaborative product design environment for dispersed engineering teams and partners.
- OpenBOM – a SaaS solution focusing on BOM collaboration connected to various CAD systems along with design teams and their connected suppliers
These are some of the Systems of Engagement I am aware of. They focus on specific value streams that can improve the targeted time to market and product introduction efficiency. In companies with no extensive additional PLM infrastructure, they can become crucial systems of engagement.
The main challenge for these systems of engagement is how they will connect to traditional Systems or Records – the classical PLM systems that we know in the market (Aras, Dassault, PTC, Siemens).
Image on the left from a presentation done by Eric Herzog from SAAB at last year’s CIMdata/PDT conference.
You can read more about this here.
When establishing a mix of Systems of Engagement and Systems of Record in your organization digitally connected, we will see overall benefits. My earlier thoughts, in general, are here: Time to split PLM?
The almost Connected approach
As I mentioned, in most companies, it is already challenging to manage their internal System of Record, which is needed for current operations and the traceability of information. In addition, most of the data stored in these systems is document-driven, not designed for real-time collaboration. So how would these companies collaborate with their suppliers?
The Model-Based Enterprise
In the bigger image below, I am referring to an image published by Jennifer Herron from her book Re-use Your CAD, where she describes the various stages of interaction between engineering, manufacturing and the extended enterprise.
Her mission is to promote and educate organizations in moving to a Model-Based Definition and, in the long term, to a Model-Base Enterprise.
The ultimate target of information exchange in this diagram is that the OEM and the Supplier are separate entities. However, they can exchange Digital Product Definition Packages and TDPs over the web (electronically). In this exchange, we have a mix of systems of engagement and systems of record on the OEM and Supplier sides.
Depending on the type of industry, in my ecosystem of companies, many suppliers are still at level 2, dreaming or pushed to become level 3, illustrating there is a difficult job to do – learning new practices. And why would you move to the next level?
Every step can have significant benefits, as reported by companies that did this.
So what’s stopping your company from moving ahead? People, Processes, Skills, Work Pressure? It is one of the most common excuses: “We are too busy, no time to improve”.
A supply chain collaboration hub
On March 21, I discussed with Magnus Färneland from Eurostep their cloud-based PLM collaboration hub, ShareAspace. You can read the interview here: PLM and Supply Chain Collaboration
I believe this concept can be compelling for a connected enterprise. The OEM and the Supplier share (or connect) only the data they want to share, preferably based on the PLCS data schema (ISO 10303-239).
In a primitive approach, this can be BOM structures with related files; however, it could become a real model-based connection hub in the advanced mode. “
Now you ask yourself why this solution is not booming.
In my opinion, there are several points to consider:
- Who designs, operates and maintains the collaboration hub?
It is likely not the suppliers, and when the OEM takes ownership, they might believe there is no need for the extra hub; just use the existing PLM infrastructure. - Could a third party find a niche market for this? Eurostep has already been working on this for many years, but adopting the concept seems higher in de BIM or Asset Management domains. Here the owner/operator sees the importance of a collaboration hub.
A final remark, we are still far from a connected enterprise; concepts like Catena-X and others need to become mature to serve as a foundation – there is a lot of technology out there -now we need the skilled people and tested practices to use the right technology and tune solutions concepts.
Sustainability demands a connected enterprise.
I focused on the Supplier dilemma this time because it is one of the crucial aspects of a circular economy and sustainable product development.
Only by using virtual models of the To-Be products/systems can we seriously optimize them. Virtual models and Digital Twins do not run on documents; they require accurate data from anywhere connected.
You can read more details in my post earlier this year: MBSE and Sustainability or look at the PLM and Sustainability recording on our PLM Global Green Alliance YouTube channel.
Conclusion
Due to various discussions I recently had in the field, it became clear that the topic of supplier integration in a best-connected manner is one of the most important topics to address in the near future. We cannot focus longer on our company as an isolated entity – value streams implemented in a connected manner become a must.
And now I am going to enjoy Liveworx in Boston, learning, discussing and understanding more about what PTC is doing and planning in the context of digital transformation and sustainability. More about that in my next post: The week(end) after Liveworx 2023 (to come)
With great pleasure, I am writing this post, part of a tradition that started for me in 2014. Posts starting with “The weekend after …. “describing what happened during a PDT conference, later the event merged with CIMdata becoming THE PLM event for discussions beyond marketing.
For many of us, this conference was the first time after COVID-19 in 2020. It was a 3D (In person) conference instead of a 2D (digital) conference. With approximately 160 participants, this conference showed that we wanted to meet and network in person and the enthusiasm and interaction were great.
The conference’s theme, Digital Transformation and PLM – a call for PLM Professionals to redefine and re-position the benefits and value of PLM, was quite open.
There are many areas where digitization affects the way to implement a modern PLM Strategy.
Now some of my highlights from day one. I needed to filter to remain around max 1500 words. As all the other sessions, including the sponsor vignettes, were informative, they increased the value of this conference.
Digital Skills Transformation -Often Forgotten Critical Element of Digital Transformation
Day 1 started traditionally with the keynote from Peter Bilello, CIMdata’s president and CEO. In previous conferences, Peter has recently focused on explaining the CIMdata’s critical dozen (image below). If you are unfamiliar with them, there is a webinar on November 10 where you can learn more about them.
All twelve are equally important; it is not a sequence of priorities. This time Peter spent more time on Organisational Change management (OCM), number 12 of the critical dozen – or, as stated, the Digital Transformation’s Achilles heel. Although we always mention people are important, in our implementation projects, they often seem to be the topic that gets the less focus.
We all agree on the statement: People, Process, Tools & Data. Often the reality is that we start with the tools, try to build the processes and push the people in these processes. Is it a coincidence that even CIMdata puts Digital Skills transformation as number 12? An unconscious bias?
This time, the people’s focus got full attention. Peter explained the need for a digital skills transformation framework to educate, guide and support people during a transformation. The concluding slide below says it all.
Transformation Journey and PLM & PDM Modernization to the Digital Future
The second keynote of the day was from Josef Schiöler, Head of Core Platform Area PLM/PDM from the Volvo Group. Josef and his team have a huge challenge as they are working on a foundation for the future of the Volvo Group.
The challenge is that it will provide the foundation for new business processes and the various group members, as the image shows below:
As Josef said, it is really the heart of the heart, crucial for the future. Peter Bilello referred to this project as open-heart surgery while the person is still active, as the current business must go on too.
The picture below gives an impression of the size of the operation.
And like any big transformation project also, the Volvo Group has many questions to explore as there is no existing blueprint to use.
To give you an impression:
- How to manage complex documentation with existing and new technology and solution co-existing?
(My take: the hybrid approach) - How to realize benefits and user adoption with user experience principles in mind?
(My take: Understand the difference between a system of engagement and a system of record) - How to avoid seeing modernization as pure an IT initiative and secure that end-user value creation is visible while still keeping a focus on finalizing the technology transformation?
(My take: think hybrid and focus first on the new systems of engagement that can grow) - How to efficiently partner with software vendors to ensure vendor solutions fit well in the overall PLM/PDM enterprise landscape without heavy customization?
(My take: push for standards and collaboration with other similar companies – they can influence a vendor)
Note: My takes are just a starting point of the conversation. There is a discussion in the PLM domain, which I described in my blog post: A new PLM paradigm.
The day before the conference, we had a ½ day workshop initiated by SAAB and Eurostep where we discussed the various angles of the so-called Federated PLM.
I will return to that topic soon after some consolidation with the key members of that workshop.
Steering future Engineering Processes with System Lifecycle Management
Patrick Schäfer‘s presentation was different than the title would expect. Patrick is the IT Architect Engineering IT from ThyssenKrupp Presta AG. The company provides steering systems for the automotive industry, which is transforming from mechanical to autonomous driving, e-mobility, car-to-car connectivity, stricter safety, and environmental requirements.
The steering system becomes a system depending on hardware and software. And as current users of Agile PLM, the old Eigner PLM software, you can feel Martin Eigner’s spirit in the project.
I briefly discussed Martin’s latest book on System Lifecycle Management in my blog post, The road to model-based and connected PLM (part 5).
Martin has always been fighting for a new term for modern PLM, and you can see how conservative we are – for sometimes good reasons.
Still, ThyssenKrupp Presta has the vision to implement a new environment to support systems instead of hardware products. And in addition, they had to work fast to upgrade their current almost obsolete PLM environment to a new supported environment.
The wise path they chose was first focusing on a traditional upgrade, meaning making sure their PLM legacy data became part of a modern (Teamcenter) PLM backbone. Meanwhile, they started exploring the connection between requirements management for products and software, as shown below.
From my perspective, I would characterize this implementation as the coordinated approach creating a future option for the connected approach when the organization and future processes are more mature and known.
A good example of a pragmatic approach.
Digital Transformation in the Domain of Products and Plants at Siemens Energy
Per Soderberg, Head of Digital PLM at Siemens Energy, talked about their digital transformation project that started 6 – 7 years ago. Knowing the world of gas- and steam turbines, it is a domain where a lot of design and manufacturing information is managed in drawings.
The ultimate vision from Siemens Energy is to create an Industrial Metaverse for its solutions as the benefits are significant.
Is this target too ambitious, like GE’s 2014 Industrial Transformation with Predix? Time will tell. And I am sure you will soon hear more from Siemens Energy; therefore, I will keep it short. An interesting and ambitious program to follow. Sure you will read about them in the near future.
Accelerating Digitalization at Stora Enso
Stora Enso is a Finish company, a leading global provider of renewable solutions in packaging, biomaterials, wooden construction and paper. Their director of Innovation Services, Kaisa Suutari, shared Stora Enso’s digital transformation program that started six years ago with a 10 million/year budget (some people started dreaming too). Great to have a budget but then where to start?
In a very systematic manner using an ideas funnel and always starting from the business need, they spend the budget in two paths, shown in the image below.
Their interesting approach was in the upper path, which Kaisa focused on. Instead of starting with an analysis of how the problem could be addressed, they start by doing and then analyze the outcome and improve.
I am a great fan of this approach as it will significantly reduce the time to maturity. However, how much time is often wasted in conducting the perfect analysis?
Their Digi Fund process is a fast process to quickly go from idea to concept, to POC and to pilot, the left side of the funnel. After a successful pilot, an implementation process starts small and scales up.
There were so many positive takeaways from this session. Start with an MVP (Minimal Viable Product) to create value from the start. Next, celebrate failure when it happens, as this is the moment you learn. Finally, continue to create measurable value created by people – the picture below says it all.
It was the second time I was impressed by Stora Enso’s innovative approach. During the PI PLMX 2020 London, Samuli Savo, Chief Digital Officer at Stora Enso, gave us insights into their innovation process. At that time, the focus was a little bit more on open innovation with startups. See my post: The weekend after PI PLMx London 2020. An interesting approach for other businesses to make their digital transformation business-driven and fun for the people
A day-one summary
There was Kyle Hall, who talked about MoSSEC and the importance of this standard in a connected enterprise. MoSSEC (Modelling and Simulation information in a collaborative Systems Engineering Context) is the published ISO standard (ISO 10303-243) for improving the decision-making process for complex products. Standards are a regular topic for this conference, more about MoSSEC here.
There was Robert Rencher, Sr. Systems Engineer, Associate Technical Fellow at Boeing, talking about the progress that the A&D action group is making related to Digital Thread, Digital Twins. Sometimes asking more questions than answers as they try to make sense of the marketing definition and what it means for their businesses. You can find their latest report here.
There was Samrat Chatterjee, Business Process Manager PLM at the ABB Process Automation division. Their businesses are already quite data-driven; however, by embedding PLM into the organization’s fabric, they aim to improve effectiveness, manage a broad portfolio, and be more modular and efficient.
The day was closed with a CEO Spotlight, Peter Bilello. This time the CEOs were not coming from the big PLM vendors but from complementary companies with their unique value in the PLM domain. Henrik Reif Andersen, co-founder of Configit; Dr. Mattias Johansson, CEO of Eurostep; Helena Gutierrez, co-founder of Share PLM; Javier Garcia, CEO of The Reuse Company and Karl Wachtel, CEO, XPLM discussed their various perspectives on the PLM domain.
Conclusion
Already so much to say; sorry, I reached the 1500 words target; you should have been there. Combined with the networking dinner after day one, it was a great start to the conference. Are you curious about day 2 – stay tuned, and your curiosity will be rewarded.
Thanks to Ewa Hutmacher, Sumanth Madala and Ashish Kulkarni, who shared their pictures of the event on LinkedIn. Clicking on their names will lead you to the relevant posts.
While preparing my presentation for the Dutch Model-Based Definition solutions event, I had some reflections and experiences discussing Model-Based Definition. Particularly in traditional industries. In the Aerospace & Defense, and Automotive industry, Model-Based Definition has become the standard. However, other industries have big challenges in adopting this approach. In this post, I want to share my observations and bring clarifications about the importance.
What is a Model-Based Definition?
The Wiki-definition for Model-Based Definition is not bad:
Model-based definition (MBD), sometimes called digital product definition (DPD), is the practice of using 3D models (such as solid models, 3D PMI and associated metadata) within 3D CAD software to define (provide specifications for) individual components and product assemblies. The types of information included are geometric dimensioning and tolerancing (GD&T), component level materials, assembly level bills of materials, engineering configurations, design intent, etc.
By contrast, other methodologies have historically required the accompanying use of 2D engineering drawings to provide such details.
When I started to write about Model-Based definition in 2016, the concept of a connected enterprise was not discussed. MBD mainly enhanced data sharing between engineering, manufacturing, and suppliers at that time. The 3D PMI is a data package for information exchange between these stakeholders.
The main difference is that the 3D Model is the main information carrier, connected to 2D manufacturing views and other relevant data, all connected in this package.
MBD – the benefits
There is no need to write a blog post related to the benefits of MBD. With some research, you find enough reasons. The most important benefits of MBD are:
- the information is and human-readable and machine-readable. Allowing the implementation of Smart Manufacturing / Industry 4.0 concepts
- the information relies on processes and data and is no longer dependent on human interpretation. This leads to better quality and error-fixing late in the process.
- MBD information is a building block for the digital enterprise. If you cannot master this concept, forget the benefits of MBSE and Virtual Twins. These concepts don’t run on documents.
To help you discover the benefits of MBD described by others – have a look here:
- What is MBD, and what are its benefits?
- MBD Efficiencies for Small Manufacturers
- 5 reasons to use MBD
- 10 reasons why everyone is moving away from traditional 2D drawings
MBD as a stepping stone to the future
When you are able to implement model-based definition practices in your organization and connect with your eco-system, you are learning what it means to work in a connected matter. Where the scope is limited, you already discover that working in a connected manner is not the same as mandating everyone to work with the same systems or tools. Instead, it is about new ways of working (skills & people), combined with exchange standards (which to follow).
Where MBD is part of the bigger model-based enterprise, the same principles apply for connecting upstream information (Model-Based Systems Engineering) and downstream information(IoT-based operation and service models).
Oleg Shilovitsky addresses the same need from a data point of view in his recent blog: PLM Strategy For Post COVID Time. He makes an important point about the Digital Thread:
Digital Thread is one of my favorite topics because it is leading directly to the topic of connected data and services in global manufacturing networks.
I agree with that statement as the digital thread is like MBD, another steppingstone to organize information in a connected manner, even beyond the scope of engineering-manufacturing interaction. However, Digital Thread is an intermediate step toward a full data-driven and model-based enterprise.
To master all these new ways is working, it is crucial for the management of manufacturing companies, both OEM and their suppliers, to initiate learning programs. Not as a Proof of Concept but as a real-life, growing activity.
Why MBD is not yet a common practice?
If you look at the success of MBD in Aerospace & Defense and Automotive, one of the main reasons was the push from the OEMs to align their suppliers. They even dictated CAD systems and versions to enable smooth and efficient collaboration.
In other industries, there we not so many giant OEMs that could dictate their supply chain. Often also, the OEM was not even ready for MBD. Therefore, the excuse was often we cannot push our suppliers to work different, let’s remain working as best as possible (the old way and some automation)
Besides the technical changes, MBD also had a business impact. Where the traditional 2D-Drawing was the contractual and leading information carrier, now the annotated 3D Model has to become the contractual agreement. This is much more complex than browsing through (paper) documents; now, you need an application to open up the content and select the right view(s) or datasets.
In the interaction between engineering and manufacturing, you could hear statements like:
you can use the 3D Model for your NC programming, but be aware the 2D drawing is leading. We cannot guarantee consistency between them.
In particular, this is a business change affecting the relationship between an OEM and its suppliers. And we know business changes do not happen overnight.
Smaller suppliers might even refuse to work on a Model-Based definition, as it is considered an extra overhead they do not benefit from.
In particular, when working with various OEMs that might have their own preferred MBD package content based on their preferred usage. There are standards; however, OEMs often push for their preferred proprietary format.
It is about an orchestrated change.
Implementing MBD in your company, like PLM, is challenging because people need to be aligned and trained on new ways of working. In particular, this creates resistance at the end-user level.
Similar to the introduction of mainstream CAD (AutoCAD in the eighties) and mainstream 3D CAD (Solidworks in the late nineties), it requires new processes, trained people, and matching tools.
I am aware of learning materials coming from the US, not so much about European or Asian thought leaders. Feel free to add other relevant resources for the readers in this post’s comments. Have a look and talk with:
Action Engineering with their OSCAR initiative: Bringing MBD Within Reach. I spoke with Jennifer Herron, founder of Action Engineering, a year ago about MBD and OSCAR in my blog post: PLM and Model-Based Definition.
Another interesting company to follow is Capvidia. Read their blog post to start with is MBD model-based definition in the 21st century.
The future
What you will discover from these two companies is that they focus on the connected flow of information between companies while anticipating that each stakeholder might have their preferred (traditional) PLM environment. It is about data federation.
The future of a connected enterprise is even more complex. So I was excited to see and download Yousef Hooshmand’s paper: ”From a Monolithic PLM Landscape to a Federated Domain and Data Mesh”.
Yousef and some of his colleagues report about their PLM modernization project @Mercedes-Benz AG, aiming at transforming a monolithic PLM landscape into a federated Domain and Data Mesh.
This paper provides a lot of structured thinking related to the concepts I try to explain to my audience in everyday language. See my The road to model-based and connected PLM thoughts.
This paper has much more depth and is a must-read and must-discuss writing for those interested – perhaps an opportunity for new startups and a threat to traditional PLM vendors.
Conclusion
Vellum drawings are almost gone now – we have electronic 2D Drawings. The model-based definition has confirmed the benefits of improving the interaction between engineering, manufacturing & suppliers. Still, many industries are struggling with this approach due to process & people changes needed. If you are not able or willing to implement a model-based definition approach, be worried about the future. The eco-systems will only run efficiently (and survive) when their information exchange is based on data and models. Start learning now.
p.s. just out of curiosity:
If you are model-based advocate support this post with a 
Image http://www.mdux.net
As promised in my early November post – The road to model-based and connected PLM (part 9 – CM), I come back with more thoughts and ideas related to the future of configuration management. Moving from document-driven ways of working to a data-driven and model-based approach fundamentally changes how you can communicate and work efficiently.
Let’s be clear: configuration management’s target is first of all about risk management. Ensuring your company’s business remains sustainable, efficient, and profitable.
By providing the appropriate change processes and guidance, configuration management either avoids costly mistakes and iterations during all phases of a product lifecycle or guarantees the quality of the product and information to ensure safety.
Companies that have not implemented CM practices probably have not observed these issues. Or they have not realized that the root cause of these issues is a lack of CM.
Similar to what is said in smaller companies related to PLM, CM is often seen as an overhead, as employees believe they thoroughly understand their products. In addition, CM is seen as a hurdle to innovation because of the standardization of practices. So yes, they think it is normal that there are sometimes problems. That’s life.
I already wrote about this topic in 2010 PLM, CM and ALM – not sexy 😦 – where ALM means Asset Lifecycle Management – my focus at that time.
Hear it from the experts
To shape the discussion related to the future of Configuration Management, I had a vivid discussion with three thought leaders in this field: Lisa Fenwick, Martijn Dullaart and Maxime Gravel. A short introduction of the three of them:
Lisa Fenwick, VP Product Development at CMstat, a leading company in Configuration Management and Data Management software solutions and consulting services for aviation, aerospace & defense, marine, and other high-tech industries. She has over 25 years of experience with CM and Deliverables Management, including both government and commercial environments.
Ms. Fenwick has achieved CMPIC SME, CMPIC CM Assessor, and CMII-C certifications. Her experience includes implementing CM software products, CM-related consulting and training, and participation in the SAE and IEEE standards development groups
Martijn Dullaart is the Lead Architect for Enterprise Configuration Management at ASML (Our Dutch national pride) and chairperson of the Industry 4.0 committee of the Institute Process Excellence (IPX) Congress. Martijn has his own blog mdux.net, and you might have seen him recently during the PLM Roadmap & PDT Fall conference in November – his thoughts about the CM future can be found on his blog here
Maxime Gravel, Manager Model-Based Engineering at Moog Inc., a worldwide designer, manufacturer, and integrator of advanced motion control products. Max has been the director of the model-based enterprise at the Institute for Process Excellence (IPX) and Head of Configuration and Change Management at Gulfstream Aerospace which certified the first aircraft in a 3D Model-Based Environment.
What we discussed:
We had an almost one-hour discussion related to the following points:
- The need for Enterprise Configuration Management – why and how
- The needed change from document-driven to model-based – the impact on methodology and tools
- The “neural network” of data – connecting CM to all other business domains, a similar view as from the PLM domain,
I kept from our discussion the importance of planning – as seen in the CMstat image on the left.
To plan which data you need to manage and how you will manage the data. How often are you doing this in your company’s projects?
Next, all participants stressed the importance of education and training on this topic – get educated. Configuration Management is not a topic that is taught at schools. Early next year, I will come back on education as the benefits of education are often underestimated. Not everything can be learned by “googling.”
Conclusion
The journey towards a model-based and data-driven future is not a quick one to be realized by new technologies. However, it is interesting to learn that the future of connected data (the “neural network”) allows organizations to implement both CM and PLM in a similar manner, using graph databases and automation. When executed at the enterprise level, the result will be that CM and PLM become natural practices instead of other siloed system-related disciplines.
Most of the methodology is there; the implementation to make it smooth and embedded in organizations will be the topics to learn. Join us in discussing and learning!
My previous post introducing the concept of connected platforms created some positive feedback and some interesting questions. For example, the question from Maxime Gravel:
Thank you, Jos, for the great blog. Where do you see Change Management tool fit in this new Platform ecosystem?
is one of the questions I try to understand too. You can see my short comment in the comments here. However, while discussing with other experts in the CM-domain, we should paint the path forward. Because if we cannot solve this type of question, the value of connected platforms will be disputable.
It is essential to realize that a digital transformation in the PLM domain is challenging. No company or vendor has the perfect blueprint available to provide an end-to-end answer for a connected enterprise. In addition, I assume it will take 10 – 20 years till we will be familiar with the concepts.
It takes a generation to move from drawings to 3D CAD. It will take another generation to move from a document-driven, linear process to data-driven, real-time collaboration in an iterative manner. Perhaps we can move faster, as the Automotive, Aerospace & Defense, and Industrial Equipment industries are not the most innovative industries at this time. Other industries or startups might lead us faster into the future.
Although I prefer discussing methodology, I believe before moving into that area, I need to clarify some more technical points before moving forward. My apologies for writing it in such a simple manner. This information should be accessible for the majority of readers.
What means data-driven?
I often mention a data-driven environment, but what do I mean precisely by that. For me, a data-driven environment means that all information is stored in a dataset that contains a single aspect of information in a standardized manner, so it becomes accessible by outside tools.
A document is not a dataset, as often it includes a collection of datasets. Most of the time, the information it is exposed to is not standardized in such a manner a tool can read and interpret the exact content. We will see that a dataset needs an identifier, a classification, and a status.
An identifier to be able to create a connection between other datasets – traceability or, in modern words, a digital thread.
A classification as the classification identifier will determine the type of information the dataset contains and potential a set of mandatory attributes
A status to understand if the dataset is stable or still in work.
Examples of a data-driven approach – the item
The most common dataset in the PLM world is probably the item (or part) in a Bill of Material. The identifier is the item number (ID + revision if revisions are used). Next, the classification will tell you the type of part it is.
Part classification can be a topic on its own, and every industry has its taxonomy.
Finally, the status is used to identify if the dataset is shareable in the context of other information (released, in work, obsolete), allowing tools to expose only relevant information.
In a data-driven manner, a part can occur in several Bill of Materials – an example of a single definition consumed in other places.
When the part information changes, the accountable person has to analyze the relations to the part, which is easy in a data-driven environment. It is normal to find this functionality in a PDM or ERP system.
When the part would change in a document-driven environment, the effort is much higher.
First, all documents need to be identified where this part occurs. Then the impact of change needs to be managed in document versions, which will lead to other related changes if you want to keep the information correct.
Examples of a data-driven approach – the requirement
Another example illustrating the benefits of a data-driven approach is implementing requirements management, where requirements become individual datasets. Often a product specification can contain hundreds of requirements, addressing the needs of different stakeholders.
In addition, several combinations of requirements need to be handled by other disciplines, mechanical, electrical, software, quality and legal, for example.
As requirements need to be analyzed and ranked, a specification document would never be frozen. Trade-off analysis might lead to dropping or changing a single requirement. It is almost impossible to manage this all in a document, although many companies use Excel. The disadvantages of Excel are known, in particular in a dynamic environment.
The advantage of managing requirements as datasets is that they can be grouped. So, for example, they can be pushed to a supplier (as a specification).
Or requirements could be linked to test criteria and test cases, without the need to manage documents and make sure you work with them last updated document.
As you will see, also requirements need to have an Identifier (to manage digital relations), a classification (to allow grouping) and a status (in work / released /dropped)
Data-driven and Models – the 3D CAD model
3D PDF Model
When I launched my series related to the model-based approach in 2018, the first comments I got came from people who believed that model-based equals the usage of 3D CAD models – see Model-based – the confusion. 3D Models are indeed an essential part of a model-based infrastructure, as the 3D model provides an unambiguous definition of the physical product. Just look at how most vendors depict the aspects of a virtual product using 3D (wireframe) models.
Although we use a 3D representation at each product lifecycle stage, most companies do not have a digital continuity for the 3D representation. Design models are often too heavy for visualization and field services support. The connection between engineering and manufacturing is usually based on drawings instead of annotated models.
I wrote about modern PLM and Model-Based Definition, supported by Jennifer Herron from Action Engineering – read the post PLM and Model-Based Definition here.
If your company wants to master a data-driven approach, this is one of the most accessible learning areas. You will discover that connecting engineering and manufacturing requires new technology, new ways of working and much more coordination between stakeholders.
Implementing Model-Based Definition is not an easy process. However, it is probably one of the best steps to get your digital transformation moving. The benefits of connected information between engineering and manufacturing have been discussed in the blog post PLM and Model-Based Definition
Essential to realize all these exciting capabilities linked to Industry 4.0 require a data-driven, model-based connection between engineering and manufacturing.
If this is not the case, the projected game-changers will not occur as they become too costly.
Data-driven and mathematical models
To manage complexity, we have learned that we have to describe the behavior in models to make logical decisions. This can be done in an abstract model, purely based on mathematical equations and relations. For example, suppose you look at climate models, weather models or COVID infections models.
In that case, we see they all lead to discussions from so-called experts that believe a model should be 100 % correct and any exception shows the model is wrong.
It is not that the model is wrong; the expectations are false.
For less complex systems and products, we also use models in the engineering domain. For example, logical models and behavior models are all descriptive models that allow people to analyze the behavior of a product.
For example, how software code impacts the product’s behavior. Usually, we speak about systems when software is involved, as the software will interact with the outside world.
There can be many models related to a product, and if you want to get an impression, look at this page from the SEBoK wiki: Types of Models. The current challenge is to keep the relations between these models by sharing parameters.
The sharable parameters then again should be datasets in a data-driven environment. Using standardized diagrams, like SysML or UML, enables the used objects in the diagram to become datasets.
I will not dive further into the modeling details as I want to remain at a high level.
Essential to realize digital models should connect to a data-driven infrastructure by sharing relevant datasets.
What does data-driven imply?
I want to conclude this time with some statements to elaborate on further in upcoming posts and discussions
- Data-driven does not imply there needs to be a single environment, a single database that contains all information. Like I mentioned in my previous post, it will be about managing connected datasets in a federated manner. It is not anymore about owned the data; it is about access to reliable data.
- Data-driven does not mean we do not need any documents anymore. Read electronic files for documents. Likely, document sets will still be the interface to non-connected entities, suppliers, and regulatory bodies. These document sets can be considered a configuration baseline.
- Data-driven means that we need to manage data in a much more granular manner. We have to look different at data ownership. It becomes more data accountability per role as the data can be used and consumed throughout the product lifecycle.
- Data-driven means that you need to have an enterprise architecture, data governance and a master data management (MDM) approach. So far, the traditional PLM vendors have not been active in the MDM domain as they believe their proprietary data model is leading. Read also this interesting McKinsey article: How enterprise architects need to evolve to survive in a digital world
- A model-based approach with connected datasets seems to be the way forward. Managing data in documents will become inefficient as they cannot contribute to any digital accelerator, like applying algorithms. Artificial Intelligence relies on direct access to qualified data.
- I don’t believe in Low-Code platforms that provide ad-hoc solutions on demand. The ultimate result after several years might be again a new type of spaghetti. On the other hand, standardized interfaces and protocols will probably deliver higher, long-term benefits. Remember: Low code: A promising trend or a Pandora’s Box?
- Configuration Management requires a new approach. The current methodology is very much based on hardware products with labor-intensive change management. However, the world of software products has different configuration management and change procedure. Therefore, we need to merge them in a single framework. Unfortunately, this cannot be the BOM framework due to the dynamics in software changes. An interesting starting point for discussion can be found here: Configuration management of industrial products in PDM/PLM
Conclusion
Again, a long post, slowly moving into the future with many questions and points to discuss. Each of the seven points above could be a topic for another blog post, a further discussion and debate.
After my summer holiday break in August, I will follow up. I hope you will join me in this journey by commenting and contributing with your experiences and knowledge.
Another episode of “The PLM Doctor is IN“. This time a question from Ilan Madjar, partner and co-founder of XLM Solutions. Ilan is my co-moderator at the PLM Global Green Alliance for sustainability topics.
All these activities resulted in the following question(s) related to the Digital Twin. Now sit back and enjoy.
PLM and the Digital Twin
Is it a new concept? How to implement and certify the result?
Relevant topics discussed in this video
- An article about the introduction of the Digital Twin concept by Michael Grieves: The history and creation of the digital twin concept discussing Michael Grieves
- A presentation from Don Farr explaining the digital value chain with the “famous” Boeing diamond model – PDF HERE
- My Slideshare presentation discussing the difference between Coordinated and Connected PLM
- My Slideshare presentation from the Digital Twin conference Eindhoven Nov 2020: Digital Twins do not run on documents
Conclusion
I hope you enjoyed the answer and look forward to your questions and comments. Let me know if you want to be an actor in one of the episodes.
The main rule: A (single) open question that is puzzling you related to PLM.
After the first article discussing “The Future of PLM,” now again a post in the category of PLM and complementary practices/domains a topic that is already for a long time on the radar: Model-Based Definition, I am glad to catch up with Jennifer Herron, founder of Action Engineering, who is one of the thought leaders related to Model-Based Definition (MBD) and Model-Based Enterprise (MBE).
In 2016 I spoke with Jennifer after reading her book: “Re-Use Your CAD – The Model-Based CAD Handbook”. At that time, the discussion was initiated through two articles on Engineering.com. Action Engineering introduced OSCAR seven years later as the next step towards learning and understanding the benefits of Model-Based Definition.
Therefore, it is a perfect moment to catch up with Jennifer. Let’s start.
Model-Based Definition
Jennifer, first of all, can you bring some clarity in terminology. When I discussed the various model-based approaches, the first response I got was that model-based is all about 3D Models and that a lot of the TLA’s are just marketing terminology.
Can you clarify which parts of the model-based enterprise you focus on and with the proper TLA’s?
Model-Based means many things to many different viewpoints and systems of interest. All these perspectives lead us down many rabbit holes, and we are often left confused when first exposed to the big concepts of model-based.
At Action Engineering, we focus on Model-Based Definition (MBD), which uses and re-uses 3D data (CAD models) in design, fabrication, and inspection.
There are other model-based approaches, and the use of the word “model” is always a challenge to define within the proper context.
For MBD, a model is 3D CAD data that comes in both native and neutral formats
Another model-based approach is Model-Based Systems Engineering (MBSE). The term “model” in this context is a formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later lifecycle phases.
<Jos> I will come back on Model-Based Systems Engineering in future posts
Sometimes MBSE is about designing widgets, and often it is about representing the entire system and the business operations. For MBD, we often focus our education on the ASME Y14.47 definition that MBD is an annotated model and associated data elements that define the product without a drawing.
Model-Based Definition for Everybody?
I believe it took many years till 3D CAD design became a commodity; however, I still see the disconnected 2D drawing used to specify a product or part for manufacturing or suppliers. What are the benefits of model-based definition?
Are there companies that will not benefit from the model-based definition?
There’s no question that the manufacturing industry is addicted to their drawings. There are many reasons why, and yet mostly the problem is lack of awareness of how 3D CAD data can make design, fabrication, and inspection work easier.
For most, the person doing an inspection in the shipping and receiving department doesn’t have exposure to 3D data, and the only thing they have is a tabulated ERP database and maybe a drawing to read. If you plop down a 3D viewable that they can spin and zoom, they may not know how that relates to their job or what you want them to do differently.
Today’s approach of engineering championing MBD alone doesn’t work. To evolve information from the 2D drawing onto the 3D CAD model without engaging the stakeholders (machinists, assembly technicians, and inspectors) never yields a return on investment.
Organizations that succeed in transitioning to MBD are considering and incorporating all departments that touch the drawing today.
Incorporating all departments requires a vision from the management. Can you give some examples of companies that have transitioned to MBD, and what were the benefits they noticed?
I’ll give you an example of a small company with no First Article Inspection (FAI) regulatory requirements and a huge company with very rigorous FAI requirements.
Note: click on the images below to enjoy the details.
The small company instituted a system of CAD modeling discipline that allowed them to push 3D viewable information directly to the factory floor. The assembly technicians instantly understood engineering’s requirements faster and better.
The positive MBD messages for these use cases are 3D navigation, CAD Re-Use, and better control of their revisions on the factory floor.
The large company has added inspection requirements directly onto their engineering and created a Bill of Characteristics (BOC) for the suppliers and internal manufacturers. They are removing engineering ambiguity, resulting in direct digital information exchange between engineering, manufacturing, and quality siloes.
These practices have reduced error and reduced time to market.
The positive MBD messages for these use cases are unambiguous requirements capture by Engineering, Quality Traceability, and Model-Based PMI (Product and Manufacturing Information).
Model-Based Definition and PLM?
How do you see the relation between Model-Based Definition and PLM? Is a PLM system a complication or aid to implement a Model-Based Definition? And do you see a difference between the old and new PLM Vendors?
Model-Based Definition data is complex and rich in connected information, and we want it to be. With that amount of connected data, a data management system (beyond upload/download of documents) must keep all that data straight.
Depending on the size and function of an organization, a PLM may not be needed. However, a way to manage changes and collaboration amongst those using 3D data is necessary. Sometimes that results in a less sophisticated Product Data Management (PDM) system. Large organizations often require PLM.
There is significant resistance to doing MBD and PLM implementations simultaneously because PLM is always over budget and behind schedule. However, doing just MBD or just PLM without the other doesn’t work either. I think you should be brave and do both at once.
I think we can debate why PLM is always over budget and behind schedule. I hear the same about ERP implementations. Perhaps it has to deal with the fact that enterprise applications have to satisfy many users?
I believe that working with model versions and file versions can get mixed in larger organizations, so there is a need for PDM or PLM. Have you seen successful implementations of both interacting together?
Yes, the only successful MBD implementations are those that already have a matured PDM/PLM (scaled best to the individual business).
Model-Based Definition and Digital Transformation
In the previous question, we already touched on the challenge of old and modern PLM. How do you see the introduction of Model-Based Definition addressing the dreams of Industry 4.0, the Digital Twin and other digital concepts?
I just gave a presentation at the ASME Digital Twin Summit discussing the importance of MBD for the Digital Twin. MBD is a foundational element that allows engineering to compare their design requirements to the quality inspection results of digital twin data.
The feedback loop between Engineering and Quality is fraught with labor-intensive efforts in most businesses today.
Leveraging the combination of MBD and Digital Twin allows automation possibilities to speed up and increase the accuracy of the engineering to inspection feedback loop. That capability helps organizations realize the vision of Industry 4.0.
And then there is OSCAR.
I noticed you announced OSCAR. First, I thought OSCAR was a virtual aid for model-based definition, and I liked the launching page HERE. Can you tell us more about what makes OSCAR unique?
One thing that is hard with MBD implementation is there is so much to know. Our MBDers at Action Engineering have been involved with MBD for many years and with many companies. We are embedded in real-life transitions from using drawings to using models.
Suppose you start down the model-based path for digital manufacturing. In that case, there are significant investments in time to learn how to get to the right set of capabilities and the right implementation plan guided by a strategic focus. OSCAR reduces that ramp-up time with educational resources and provides vetted and repeatable methods for an MBD implementation.
OSCAR combines decades of Action Engineering expertise and lessons learned into a multi-media textbook of sorts. To kickstart an individual or an organization’s MBD journey, it includes asynchronous learning, downloadable resources, and CAD examples available in Creo, NX, and SOLIDWORKS formats.
CAD users can access how-to training and downloadable resources such as the latest edition of Re-Use Your CAD (RUYC). OSCAR enables process improvement champions to make their case to start the MBD journey. We add content regularly and post what’s new. Free trials are available to check out the online platform.
Learn more about what OSCAR is here:
Want to learn more?
In this post, I believe we only touched the tip of the iceberg. There is so much to learn and understand. What would you recommend to a reader of this blog who got interested?
RUYC (Re-Use Your CAD) is an excellent place to start, but if you need more audio-visual, and want to see real-life examples of MBD in action, get a Training subscription of OSCAR to get rooted in the vocabulary and benefits of MBD with a Model-Based Enterprise. Watch the videos multiple times! That’s what they are for. We love to work with European companies and would love to support you with a kickstart coaching package to get started.
What I learned
First of all, I learned that Jennifer is a very pragmatic person. Her company (Action Engineering) and her experience are a perfect pivot point for those who want to learn and understand more about Model-Based Definition. In particular, in the US, given her strong involvement in the American Society of Mechanical Engineers (ASME).
I am still curious if European or Asian counterparts exist to introduce and explain the benefits and usage of Model-Based Definition to their customers. Feel free to comment.
Next, and an important observation too, is the fact that Jennifer also describes the tension between Model-Based Definition and PLM. Current PLM systems might be too rigid to support end-to-end scenarios, taking benefit of the Model-Based definition.
I have to agree here. PLM Vendors mainly support their own MBD (model-based definition), where the ultimate purpose is to share all product-related information using various models as the main information carriers efficiently.
We have to study and solve a topic in the PLM domain, as I described in my technical highlights from the PLM Road Map & PDT Spring 2021 conference.
There is work to do!
Conclusion
Model-Based Definition is, for me, one of the must-do steps of a company to understand the model-based future. A model-based future sometimes incorporates Model-Based Systems Engineering, a real Digital Thread and one or more Digital Twins (depending on your company’s products).
It is a must-do activity because companies must transform themselves to depend on digital processes and digital continuity of data to remain competitive. Document-driven processes relying on the interpretation of a person are not sustainable.
After the first article discussing “The Future of PLM,” now again a post in the category of PLM and complementary practices/domains a topic that is already for a long time on the radar: Model-Based Definition, I am glad to catch up with Jennifer Herron, founder of Action Engineering, who is one of the thought leaders related to Model-Based Definition (MBD) and Model-Based Enterprise (MBE).
In 2016 I spoke with Jennifer after reading her book: “Re-Use Your CAD – The Model-Based CAD Handbook”. At that time, the discussion was initiated through two articles on Engineering.com. Action Engineering introduced OSCAR seven years later as the next step towards learning and understanding the benefits of Model-Based Definition.
Therefore, it is a perfect moment to catch up with Jennifer. Let’s start.
Model-Based Definition
Jennifer, first of all, can you bring some clarity in terminology. When I discussed the various model-based approaches, the first response I got was that model-based is all about 3D Models and that a lot of the TLA’s are just marketing terminology.
Can you clarify which parts of the model-based enterprise you focus on and with the proper TLA’s?
Model-Based means many things to many different viewpoints and systems of interest. All these perspectives lead us down many rabbit holes, and we are often left confused when first exposed to the big concepts of model-based.
At Action Engineering, we focus on Model-Based Definition (MBD), which uses and re-uses 3D data (CAD models) in design, fabrication, and inspection.
There are other model-based approaches, and the use of the word “model” is always a challenge to define within the proper context.
For MBD, a model is 3D CAD data that comes in both native and neutral formats
Another model-based approach is Model-Based Systems Engineering (MBSE). The term “model” in this context is a formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later lifecycle phases.
<Jos> I will come back on Model-Based Systems Engineering in future posts
Sometimes MBSE is about designing widgets, and often it is about representing the entire system and the business operations. For MBD, we often focus our education on the ASME Y14.47 definition that MBD is an annotated model and associated data elements that define the product without a drawing.
Model-Based Definition for Everybody?
I believe it took many years till 3D CAD design became a commodity; however, I still see the disconnected 2D drawing used to specify a product or part for manufacturing or suppliers. What are the benefits of model-based definition?
Are there companies that will not benefit from the model-based definition?
There’s no question that the manufacturing industry is addicted to their drawings. There are many reasons why, and yet mostly the problem is lack of awareness of how 3D CAD data can make design, fabrication, and inspection work easier.
For most, the person doing an inspection in the shipping and receiving department doesn’t have exposure to 3D data, and the only thing they have is a tabulated ERP database and maybe a drawing to read. If you plop down a 3D viewable that they can spin and zoom, they may not know how that relates to their job or what you want them to do differently.
Today’s approach of engineering championing MBD alone doesn’t work. To evolve information from the 2D drawing onto the 3D CAD model without engaging the stakeholders (machinists, assembly technicians, and inspectors) never yields a return on investment.
Organizations that succeed in transitioning to MBD are considering and incorporating all departments that touch the drawing today.
Incorporating all departments requires a vision from the management. Can you give some examples of companies that have transitioned to MBD, and what were the benefits they noticed?
I’ll give you an example of a small company with no First Article Inspection (FAI) regulatory requirements and a huge company with very rigorous FAI requirements.
Note: click on the images below to enjoy the details.
The small company instituted a system of CAD modeling discipline that allowed them to push 3D viewable information directly to the factory floor. The assembly technicians instantly understood engineering’s requirements faster and better.
The positive MBD messages for these use cases are 3D navigation, CAD Re-Use, and better control of their revisions on the factory floor.
The large company has added inspection requirements directly onto their engineering and created a Bill of Characteristics (BOC) for the suppliers and internal manufacturers. They are removing engineering ambiguity, resulting in direct digital information exchange between engineering, manufacturing, and quality siloes.
These practices have reduced error and reduced time to market.
The positive MBD messages for these use cases are unambiguous requirements capture by Engineering, Quality Traceability, and Model-Based PMI (Product and Manufacturing Information).
Model-Based Definition and PLM?
How do you see the relation between Model-Based Definition and PLM? Is a PLM system a complication or aid to implement a Model-Based Definition? And do you see a difference between the old and new PLM Vendors?
Model-Based Definition data is complex and rich in connected information, and we want it to be. With that amount of connected data, a data management system (beyond upload/download of documents) must keep all that data straight.
Depending on the size and function of an organization, a PLM may not be needed. However, a way to manage changes and collaboration amongst those using 3D data is necessary. Sometimes that results in a less sophisticated Product Data Management (PDM) system. Large organizations often require PLM.
There is significant resistance to doing MBD and PLM implementations simultaneously because PLM is always over budget and behind schedule. However, doing just MBD or just PLM without the other doesn’t work either. I think you should be brave and do both at once.
I think we can debate why PLM is always over budget and behind schedule. I hear the same about ERP implementations. Perhaps it has to deal with the fact that enterprise applications have to satisfy many users?
I believe that working with model versions and file versions can get mixed in larger organizations, so there is a need for PDM or PLM. Have you seen successful implementations of both interacting together?
Yes, the only successful MBD implementations are those that already have a matured PDM/PLM (scaled best to the individual business).
Model-Based Definition and Digital Transformation
In the previous question, we already touched on the challenge of old and modern PLM. How do you see the introduction of Model-Based Definition addressing the dreams of Industry 4.0, the Digital Twin and other digital concepts?
I just gave a presentation at the ASME Digital Twin Summit discussing the importance of MBD for the Digital Twin. MBD is a foundational element that allows engineering to compare their design requirements to the quality inspection results of digital twin data.
The feedback loop between Engineering and Quality is fraught with labor-intensive efforts in most businesses today.
Leveraging the combination of MBD and Digital Twin allows automation possibilities to speed up and increase the accuracy of the engineering to inspection feedback loop. That capability helps organizations realize the vision of Industry 4.0.
And then there is OSCAR.
I noticed you announced OSCAR. First, I thought OSCAR was a virtual aid for model-based definition, and I liked the launching page HERE. Can you tell us more about what makes OSCAR unique?
One thing that is hard with MBD implementation is there is so much to know. Our MBDers at Action Engineering have been involved with MBD for many years and with many companies. We are embedded in real-life transitions from using drawings to using models.
Suppose you start down the model-based path for digital manufacturing. In that case, there are significant investments in time to learn how to get to the right set of capabilities and the right implementation plan guided by a strategic focus. OSCAR reduces that ramp-up time with educational resources and provides vetted and repeatable methods for an MBD implementation.
OSCAR combines decades of Action Engineering expertise and lessons learned into a multi-media textbook of sorts. To kickstart an individual or an organization’s MBD journey, it includes asynchronous learning, downloadable resources, and CAD examples available in Creo, NX, and SOLIDWORKS formats.
CAD users can access how-to training and downloadable resources such as the latest edition of Re-Use Your CAD (RUYC). OSCAR enables process improvement champions to make their case to start the MBD journey. We add content regularly and post what’s new. Free trials are available to check out the online platform.
Learn more about what OSCAR is here:
Want to learn more?
In this post, I believe we only touched the tip of the iceberg. There is so much to learn and understand. What would you recommend to a reader of this blog who got interested?
RUYC (Re-Use Your CAD) is an excellent place to start, but if you need more audio-visual, and want to see real-life examples of MBD in action, get a Training subscription of OSCAR to get rooted in the vocabulary and benefits of MBD with a Model-Based Enterprise. Watch the videos multiple times! That’s what they are for. We love to work with European companies and would love to support you with a kickstart coaching package to get started.
What I learned
First of all, I learned that Jennifer is a very pragmatic person. Her company (Action Engineering) and her experience are a perfect pivot point for those who want to learn and understand more about Model-Based Definition. In particular, in the US, given her strong involvement in the American Society of Mechanical Engineers (ASME).
I am still curious if European or Asian counterparts exist to introduce and explain the benefits and usage of Model-Based Definition to their customers. Feel free to comment.
Next, and an important observation too, is the fact that Jennifer also describes the tension between Model-Based Definition and PLM. Current PLM systems might be too rigid to support end-to-end scenarios, taking benefit of the Model-Based definition.
I have to agree here. PLM Vendors mainly support their own MBD (model-based definition), where the ultimate purpose is to share all product-related information using various models as the main information carriers efficiently.
We have to study and solve a topic in the PLM domain, as I described in my technical highlights from the PLM Road Map & PDT Spring 2021 conference.
There is work to do!
Conclusion
Model-Based Definition is, for me, one of the must-do steps of a company to understand the model-based future. A model-based future sometimes incorporates Model-Based Systems Engineering, a real Digital Thread and one or more Digital Twins (depending on your company’s products).
It is a must-do activity because companies must transform themselves to depend on digital processes and digital continuity of data to remain competitive. Document-driven processes relying on the interpretation of a person are not sustainable.
One of my favorite conferences is the PLM Road Map & PDT conference. Probably because in the pre-COVID days, it was the best PLM conference to network with peers focusing on PLM practices, standards, and sustainability topics. Now the conference is virtual, and hopefully, after the pandemic, we will meet again in the conference space to elaborate on our experiences further.
Last year’s fall conference was special because we had three days filled with a generic PLM update and several A&D (Aerospace & Defense) working groups updates, reporting their progress and findings. Sessions related to the Multiview BOM research, Global Collaboration, and several aspects of Model-Based practices: Model-Based Definition, Model-Based Engineering & Model-Based Systems engineering.
All topics that I will elaborate on soon. You can refresh your memory through these two links:
- The weekend after PLM Roadmap / PDT 2020 – part 1
- The next weekend after PLM Roadmap / PDT 2020 – part 2
This year, it was a two-day conference with approximately 200 attendees discussing how emerging technologies can disrupt the current PLM landscape and reshape the PLM Value Equation. During the first day of the conference, we focused on technology.
On the second day, we looked in addition to the impact new technology has on people and organizations.
Today’s Emerging Trends & Disrupters
Peter Bilello, CIMdata’s President & CEO, kicked off the conference by providing CIMdata observations of the market. An increasing number of technology capabilities, like cloud, additive manufacturing, platforms, digital thread, and digital twin, all with the potential of realizing a connected vision. Meanwhile, companies evolve at their own pace, illustrating that the gap between the leaders and followers becomes bigger and bigger.
Where is your company? Can you afford to be a follower? Is your PLM ready for the future? Probably not, Peter states.
Next, Peter walked us through some technology trends and their applicability for a future PLM, like topological data analytics (TDA), the Graph Database, Low-Code/No-Code platforms, Additive Manufacturing, DevOps, and Agile ways of working during product development. All capabilities should be related to new ways of working and updated individual skills.
I fully agreed with Peter’s final slide – we have to actively rethink and reshape PLM – not by calling it different but by learning, experimenting, and discussing in the field.
Digital Transformation Supporting Army Modernization
An interesting viewpoint related to modern PLM came from Dr. Raj Iyer, Chief Information Officer for IT Reform from the US Army. Rai walked us through some of the US Army’s challenges, and he gave us some fantastic statements to think about. Although an Army cannot be compared with a commercial business, its target remains to be always ahead of the competition and be aware of the competition.
Where we would say “data is the new oil”, Rai Iyer said: “Data is the ammunition of the future fight – as fights will more and more take place in cyberspace.”
The US Army is using a lot of modern technology – as the image below shows. The big difference here with regular businesses is that it is not about ROI but about winning fights.
Also, for the US Army, the cloud becomes the platform of the future. Due to the wide range of assets, the US Army has to manage, the importance of product data standards is evident. – Rai mentioned their contribution and adherence to the ISO 10303 STEP standard crucial for interoperability. It was an exciting insight into the US Army’s current and future challenges. Their primary mission remains to stay ahead of the competition.
Joining up Engineering Data without losing the M in PLM
Nigel Shaw’s (Eurostep) presentation was somehow philosophical but precisely to the point what is the current dilemma in the PLM domain. Through an analogy of the internet, explaining that we live in a world of HTTP(s) linking, we create new ways of connecting information. The link becomes an essential artifact in our information model.
Where it is apparent links are crucial for managing engineering data, Nigel pointed out some of the significant challenges of this approach, as you can see from his (compiled) image below.
I will not discuss this topic further here as I am planning to come back to this topic when explaining the challenges of the future of PLM.
As Nigel said, they have a debate with one of their customers to replace the existing PLM tools or enhance the existing PLM tools. The challenge of moving from coordinated information towards connected data is a topic that we as a community should study.
Integration is about more than Model Format.
This was the presentation I have been waiting for. Mark Williams from Boeing had built the story together with Adrian Burton from Airbus. Nigel Shaw, in the previous session, already pointed to the challenge of managing linked information. Mark elaborated further about the model-based approach for system definition.
All content was related to the understanding that we need a model-based information infrastructure for the future because storing information in documents (the coordinated approach) is no longer viable for complex systems. Mark ‘slide below says it all.
Mark stressed the importance of managing model information in context, and it has become a challenge.
Mark mentioned that 20 years ago, the IDC (International Data Corporation) measured Boeing’s performance and estimated that each employee spent 2 ½ hours per day. In 2018, the IDC estimated that this number has grown to 30 % of the employee’s time and could go up to 50 % when adding the effort of reusing and duplicating data.
The consequence of this would be that a full-service enterprise, having engineering, manufacturing and services connected, probably loses 70 % of its information because they cannot find it—an impressive number asking for “clever” ways to find the correct information in context.
It is not about just a full indexed search of the data, as some technology geeks might think. It is also about describing and standardizing metadata that describes the models. In that context, Mark walked through a list of existing standards, all with their pros and cons, ending up with the recommendation to use the ISO 10303-243 – MoSSEC standard.
MoSSEC standing for Modelling and Simulation information in a collaborative Systems Engineering Context to manage and connect the relationships between models.
MoSSEC and its implication for future digital enterprises are interesting, considering the importance of a model-based future. I am curious how PLM Vendors and tools will support and enable the standard for future interoperability and collaboration.
Additive Manufacturing
– not as simple as paper printing – yet
Andreas Graichen from Siemens Energy closed the day, coming back to the new technologies’ topic: Additive Manufacturing or in common language 3D Printing. Andreas shared their Additive Manufacturing experiences, matching the famous Gartner Hype Cycle. His image shows that real work needs to be done to understand the technology and its use cases after the first excitement of the hype is over.
Material knowledge was one of the important topics to study when applying additive manufacturing. It is probably a new area for most companies to understand the material behaviors and properties in an Additive Manufacturing process.
The ultimate goal for Siemens Energy is to reach an “autonomous” workshop anywhere in the world where gas turbines could order their spare parts by themselves through digital warehouses. It is a grand vision, and Andreas confirmed that the scalability of Additive Manufacturing is still a challenge.
For rapid prototyping or small series of spare parts, Additive Manufacturing might be the right solution. The success of your Additive Manufacturing process depends a lot on how your company’s management has realistic expectations and the budget available to explore this direction.
Conclusion
Day 1 was enjoyable and educational, starting and ending with a focus on disruptive technologies. The middle part related to data the data management concepts needed for a digital enterprise were the most exciting topics to follow up in my opinion.
Next week I will follow up with reviewing day 2 and share my conclusions. The PLM Road Map & PDT Spring 2021 conference confirmed that there is work to do to understand the future (of PLM).
Last summer, I wrote a series of blog posts grouped by the theme “Learning from the past to understand the future”. These posts took you through the early days of drawings and numbering practices towards what we currently consider the best practice: PLM BOM-centric backbone for product lifecycle information.
You can find an overview and links to these posts on the page Learning from the past.
If you have read these posts, or if you have gone yourself through this journey, you will realize that all steps were more or less done evolutionarily. There were no disruptions. Affordable 3D CAD systems, new internet paradigms (interactive internet), global connectivity and mobile devices all introduced new capabilities for the mainstream. As described in these posts, the new capabilities sometimes created friction with old practices. Probably the most popular topics are the whole Form-Fit-Function interpretation and the discussion related to meaningful part numbers.
What is changing?
In the last five to ten years, a lot of new technology has come into our lives. The majority of these technologies are related to dealing with data. Digital transformation in the PLM domain means moving from a file-based/document-centric approach to a data-driven approach.
A Bill of Material on the drawing has become an Excel-like table in a PLM system. However, an Excel file is still used to represent a Bill of Material in companies that have not implemented PLM.
Another example, the specification document has become a collection of individual requirements in a system. Each requirement is a data object with its own status and content. The specification becomes a report combining all valid requirement objects.
Related to CAD, the 2D drawing is no longer the deliverable as a document; the 3D CAD model with its annotated views becomes the information carrier for engineering and manufacturing.
And most important of all, traditional PLM methodologies have been based on a mechanical design and release process. Meanwhile, modern products are systems where the majority of capabilities are defined by software. Software has an entirely different configuration and lifecycle approach conflicting with a mechanical approach, which is too rigid for software.
The last two aspects, from 2D drawings to 3D Models and Mechanical products towards Systems (hardware and software), require new data management methods. In this environment, we need to learn to manage simulation models, behavior models, physics models and 3D models as connected as possible.
I wrote about these changes three years ago: Model-Based – an introduction, which led to a lot of misunderstanding (too advanced – too hypothetical).
I plan to revisit these topics in the upcoming months again to see what has changed over the past three years.
What will I discuss in the upcoming weeks?
My first focus is on participating and contributing to the upcoming PLM Roadmap & PDS spring 2021 conference. Here speakers will discuss the need for reshaping the PLM Value Equation due to new emerging technologies. A topic that contributes perfectly to the future of PLM series.
My contribution will focus on the fact that technology alone cannot disrupt the PLM domain. We also have to deal with legacy data and legacy ways of working.
Another post will focus on the difference between the digital thread and the digital thread. Yes, it looks like I am writing twice the same words. However, you will see based on its interpretation, one definition is hanging on the past, the other is targeting the future. Again here, the differentiation is crucial if the need for a maintainable Digital Twin is required.
Model-Based Systems Engineering (MBSE) in all its aspects needs to be discussed too. MBSE is crucial for defining complex products. Model-Based Systems Engineering is seen as a discipline to design products. Understanding data management related to MBSE will be the foundation for understanding data management in a Model-Based Enterprise. For example, how to deal with configuration management in the future?
Writing Learning from the past was an easy job as explaining with hindsight is so much easier if you have lived it through. I am curious and excited about the outcome of “The Future of PLM”. Writing about the future means you have digested the information coming to you, knowing that nobody has a clear blueprint for the future of PLM.
There are people and organizations are working on this topic more academically, for example read this post from Lionel Grealou related to the Place of PLM in the Digital Future. The challenge is that an academic future might be disrupted by unpredictable events, like COVID, or disruptive technologies combined with an opportunity to succeed. Therefore I believe, it will be a learning journey for all of us where we need to learn to give technology a business purpose. Business first – then technology.
No Conclusion
Normally I close my post with a conclusion. At this moment. there is no conclusion as the journey has just started. I look forward to debating and learning with practitioners in the field. Work together on methodology and concepts that work in a digital enterprise. Join me on this journey. I will start sharing my thoughts in the upcoming months
Jos Voskuil's Weblog 
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