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This year started for me with a discussion related to federated PLM. A topic that I highlighted as one of the imminent trends of 2022. A topic relevant for PLM consultants and implementers. If you are working in a company struggling with PLM, this topic might be hard to introduce in your company.

Before going into the discussion’s topics and arguments, let’s first describe the historical context.

 

The traditional PLM frame.

Historically PLM has been framed first as a system for engineering to manage their product data. So you could call it PDM first. After that, PLM systems were introduced and used to provide access to product data, upstream and downstream. The most common usage was the relation with manufacturing, leading to EBOM and MBOM discussions.

The traditional ENOVIA PLM backbone

IT landscape simplification often led to an infrastructure of siloed solutions – PLM, ERP, CRM and later, MES. IT was driving the standardization of systems and defining interfaces between systems. System capabilities were leading, not the flow of information.

As many companies are still in this stage, I would call it PLM 1.0

PLM 1.0 systems serve mainly as a System of Record for the organization, where disciplines consolidate their data in a given context, the Bills of Information. The Bill of Information then is again the place to connect specification documents, i.e., CAD models, drawings and other documents, providing a Digital Thread.

Aras – Bills of Information creating the Digital Thread

The actual engineering work is done with specialized tools, MCAD/ECAD, CAE, Simulation, Planning tools and more. Therefore, each person could work in their discipline-specific environment and synchronize their data to the PLM system in a coordinated manner.

However, this interaction is not easy for some of the end-users. For example, the usability of CAD integrations with the PLM system is constantly debated.

Many of my implementation discussions with customers were in this context. For example, suppose your products are relatively simple, or your company is relatively small. In that case, the opinion is that the System or Record approach is overkill.

That’s why many small and medium enterprises do not see the value of a PLM backbone.

This could be true till recently. However, the threats to this approach are digitization and regulations.

Customers, partners, and regulators all expect more accurate and fast responses on specific issues, preferably instantly. In addition, sustainability regulations might push your company to implement a System of Record.

 

PLM as a business strategy

For the past fifteen years, we have discussed PLM more as a business strategy implemented with business systems and an infrastructure designed for sharing. Therefore, I choose these words carefully to avoid overhanging the expression: PLM as a business strategy.

The reason for this prudence is that, in reality, I have seen many PLM implementations fail due to the ambiguity of PLM as a system or strategy. Many enterprises have previously selected a preferred PLM Vendor solution as a starting point for their “PLM strategy”.

One of the most neglected best practices.

In reality, this means there was no strategy but a hope that with this impressive set of product demos, the company would find a way to support its business needs. Instead of people, process and then tools to implement the strategy, most of the time, it was starting with the tools trying to implement the processes and transform the people. That is not really the definition of business transformation.

In my opinion, this is happening because, at the management level, decisions are made based on financials.

Developing a PLM-related business strategy requires management understanding and involvement at all levels of the organization.

This is often not the case; the middle management has to solve the connection between the strategy and the execution. By design, however, the middle management will not restructure the organization. By design, they will collect the inputs van the end users.

And it is clear what end users want – no disruption in their comfortable way of working.

Halfway conclusion:

Rebranding PLM as a business strategy has not really changed the way companies work. PLM systems remain a System of Record mainly for governance and traceability.

To understand the situation in your company, look at who is responsible for PLM.

  • If IT is responsible, then most likely, PLM is not considered a business strategy but more an infrastructure.
  • If engineering is responsible for PLM, then you are still in the early days of PLM, the engineering tools to be consulted by others upstream or downstream.

Only when PLM accountability is at the upper management level, it might be a business strategy (assume the upper management understands the details)

 

Connected is the game changer

Connecting all stakeholders in an engagement has been a game changer in the world. With the introduction of platforms and the smartphone as a connected device, consumers could suddenly benefit from direct responses to desired service requests (Spotify, iTunes, Uber, Amazon, Airbnb, Booking, Netflix, …).

The business change: connecting real-time all stakeholders to deliver highly rapid results.

What would be the game changer in PLM was the question? The image below describes the 2014 Accenture description of digital PLM and its potential benefits.

 

Is connected PLM a utopia?

Marc Halpern from Gartner shared in 2015 the slide below that you might have seen many times before. Digital Transformation is really moving from a coordinated to a connected technology, it seems.

The image below gives an impression of an evolution.

I have been following this concept till I was triggered by a 2017 McKinsey publication: “our insights/toward an integrated technology operating model“.

This was the first notion for me that the future should be hybrid, a combination of traditional PLM   (system of record) complemented with teams that work digitally connected; McKinsey called them pods that become product-centric (multidisciplinary team focusing on a product) instead of discipline-centric (marketing/engineering/manufacturing/service)

In 2019 I wrote the post: The PLM migration dilemma supporting the “shocking” conclusion “Don’t think about migration when moving to data-driven, connected ways of working. You need both environments.”

One of the main arguments behind this conclusion was that legacy product data and processes were not designed to ensure data accuracy and quality on such a level that it could become connected data. As a result, converting documents into reliable datasets would be a costly, impossible exercise with no real ROI.

The second argument was that the outside world, customers, regulatory bodies and other non-connected stakeholders still need documents as standardized deliverables.

The conclusion led to the image below.

Systems of Record (left) and Systems of Engagement (right)

 

Splitting PLM?

In 2021 these thoughts became more mature through various publications and players in the PLM domain.

We saw the upcoming of Systems of Engagement – I discussed OpenBOM, Colab and potentially Configit in the post: A new PLM paradigm. These systems can be characterized as connected solutions across the enterprise and value chain, focusing on a platform experience for the stakeholders.

These are all environments addressing the needs of a specific group of users as efficiently and as friendly as possible.

A System of Engagement will not fit naturally in a traditional PLM backbone; the System of Record.

Erik Herzog with SAAB Aerospace and Yousef Houshmand at that time with Daimler published that year papers related to “Federated PLM” or “The end of monolithic PLM.”. They acknowledged a company needs to focus on more than a single PLM solution. The presentation from Erik Herzog at the PLM Roadmap/PDT conference was interesting because Erik talked about the Systems of Engagement and the Systems of Record. He proposed using OSLC as the standard to connect these two types of PLM.

It was a clear example of an attempt to combine the two kinds of PLM.

And here comes my question: Do we need to split PLM?

When I look at PLM implementations in the field, almost all are implemented as a System of Record, an information backbone proved by a single vendor PLM. The various disciplines deliver their content through interfaces to the backbone (Coordinated approach).

However, there is low usability or support for multidisciplinary collaboration; the PLM backbone is not designed for that.

Due to concepts of Model-Based Systems Engineering (MBSE) and Model-Based Definition (MBD), there are now solutions on the market that allow different disciplines to work jointly related to connected datasets that can be manipulated using modeling software  (1D, 2D, 3D, 4D,…).

These environments, often a mix of software and hardware tools, are the Systems of Engagement and provide speedy results with high quality in the virtual world. Digital Twins are running on Systems of Engagements, not on Systems of Records.

Systems of Engagement do not need to come from the same vendor, as they serve different purposes. But how to explain this to your management, who wants simplicity. I can imagine the IT organization has a better understanding of this concept as, at the end of 2015, Gartner introduced the concept of the bimodal approach.

Their definition:

Mode 1 is optimized for areas that are more well-understood. It focuses on exploiting what is known. This includes renovating the legacy environment so it is fit for a digital world. Mode 2 is exploratory, potentially experimenting to solve new problems. Mode 2 is optimized for areas of uncertainty. Mode 2 often works on initiatives that begin with a hypothesis that is tested and adapted during a process involving short iterations.

No Conclusion – but a question this time:

At the management level, unfortunately, there is most of the time still the “Single PLM”-mindset due to a lack of understanding of the business. Clearly splitting your PLM seems the way forward. IT could be ready for this, but will the business realize this opportunity?

What are your thoughts?

 

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:

 

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.

This is not always on the agenda of C-level people who try to avoid technical details (because they don’t understand them – read this great article: Technical Leadership: A Chronic Weakness in Engineering Enterprises.

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

 

After two quiet weeks of spending time with my family in slow motion, it is time to start the year.

First of all, I wish you all a happy, healthy, and positive outcome for 2022, as we need energy and positivism together. Then, of course, a good start is always cleaning up your desk and only leaving the relevant things for work on the desk.

Still, I have some books at arm’s length, either physical or on my e-reader, that I want to share with you – first, the non-obvious ones:

The Innovators Dilemma

A must-read book was written by Clayton Christensen explaining how new technologies can overthrow established big companies within a very short period. The term Disruptive Innovation comes up here. Companies need to remain aware of what is happening outside and ready to adapt to your business. There are many examples even recently where big established brands are gone or diminished in a short period.

In his book, he wrote about DEC (Digital Equipment Company)  market leader in minicomputers, not having seen the threat of the PC. Or later Blockbuster (from video rental to streaming), Kodak (from analog photography to digital imaging) or as a double example NOKIA (from paper to market leader in mobile phones killed by the smartphone).

The book always inspired me to be alert for new technologies, how simple they might look like, as simplicity is the answer at the end. I wrote about in 2012: The Innovator’s Dilemma and PLM, where I believed cloud, search-based applications and Facebook-like environments could disrupt the PLM world. None of this happened as a disruption; these technologies are now, most of the time, integrated by the major vendors whose businesses are not really disrupted. Newcomers still have a hard time to concur marketspace.

In 2015 I wrote again about this book, The Innovator’s dilemma and Generation change. – image above. At that time, understanding disruption will not happen in the PLM domain. Instead, I predict there will be a more evolutionary process, which I would later call: From Coordinated to Connected.

The future ways of working address the new skills needed for the future. You need to become a digital native, as COVID-19 pushed many organizations to do so. But digital native alone does not bring success. We need new ways of working which are more difficult to implement.

Sapiens

The book Sapiens by Yuval Harari made me realize the importance of storytelling in the domain of PLM and business transformation. In short, Yuval Harari explains why the human race became so dominant because we were able to align large groups around an abstract theme. The abstract theme can be related to religion, the power of a race or nation, the value of money, or even a brand’s image.

The myth (read: simplified and abstract story) hides complexity and inconsistencies. It allows everyone to get motivated to work towards one common goal. A Yuval says: “Fiction is far more powerful because reality is too complex”.

Too often, I have seen well-analyzed PLM projects that were “killed” by management because it was considered too complex. I wrote about this in 2019  PLM – measurable or a myth? claiming that the real benefits of PLM are hard to predict, and we should not look isolated only to PLM.

My 2020 follow-up post The PLM ROI Myth, eludes to that topic. However, even if you have a soundproof business case at the management level, still the myth might be decisive to justify the investment.

That’s why PLM vendors are always working on their myths: the most cost-effective solution, the most visionary solution, the solution most used by your peers and many other messages to influence your emotions, not your factual thinking. So just read the myths on their websites.

If you have no time to read the book, look at the above 2015 Ted to grasp the concept and use it with a PLM -twisted mind.

Re-use your CAD

In 2015, I read this book during a summer holiday (meanwhile, there is a second edition). Although it was not a PLM book, it was helping me to understand the transition effort from a classical document-driven enterprise towards a model-based enterprise.

Jennifer Herron‘s book helps companies to understand how to break down the (information) wall between engineering and manufacturing.

At that time, I contacted Jennifer to see if others like her and Action Engineering could explain Model-Based Definition comprehensively, for example, in Europe- with no success.

As the Model-Based Enterprise becomes more and more the apparent future for companies that want to be competitive or benefit from the various Digital Twin concepts. For that reason, I contacted Jennifer again last year in my post: PLM and Model-Based Definition.

As you can read, the world has improved, there is a new version of the book, and there is more and more information to share about the benefits of a model-based approach.

I am still referencing Action Engineering and their OSCAR learning environment for my customers. Unfortunately, many small and medium enterprises do not have the resources and skills to implement a model-based environment.

Instead, these companies stay on their customers’ lowest denominator: the 2D Drawing. For me, a model-based definition is one of the first steps to master if your company wants to provide digital continuity of design and engineering information towards manufacturing and operations. Digital twins do not run on documents; they require model-based environments.

The book is still on my desk, and all the time, I am working on finding the best PLM practices related to a Model-Based enterprise.

It is a learning journey to deal with a data-driven, model-based environment, not only for PLM but also for CM experts, as you might have seen from my recent dialogue with CM experts: The future of Configuration Management.

Products2019

This book was an interesting novelty published by John Stark in 2020. John is known for his academic and educational books related to PLM. However, during the early days of the COVID-pandemic, John decided to write a novel. The novel describes the learning journey of Jane from Somerset, who, as part of her MBA studies, is performing a research project for the Josef Mayer Maschinenfabrik. Her mission is to report to the newly appointed CEO what happens with the company’s products all along the lifecycle.

Although it is not directly a PLM book, the book illustrates the complexity of PLM. It Is about people and culture; many different processes, often disconnected. Everyone has their focus on their particular discipline in the center of importance. If you believe PLM is all about the best technology only, read this book and learn how many other aspects are also relevant.

I wrote about the book in 2020: Products2019 – a must-read if you are new to PLM if you want to read more details. An important point to pick up from this book is that it is not about PLM but about doing business.

PLM is not a magical product. Instead, it is a strategy to support and improve your business.

System Lifecycle Management

Another book, published a little later and motivated by the extra time we all got during the COVID-19 pandemic, was Martin Eigner‘s book System Lifecycle Management.

A 281-page journey from the early days of data management towards what Martin calls System Lifecycle Management (SysLM). He was one of the first to talk about System Lifecycle Management instead of PLM.

I always enjoyed Martin’s presentations at various PLM conferences where we met. In many ways, we share similar ideas. However, during his time as a professor at the University of Kaiserslautern (2003-2017), he explored new concepts with his students.

I briefly mentioned the book in my series The road to model-based and connected PLM (Part 5) when discussing SLM or SysLM. His academic research and analysis make this book very valuable. It takes you in a very structured way through the times that mechatronics becomes important, next the time that systems (hardware and software) become important.

We discussed in 2015 the applicability of the bimodal approach for PLM. However, as many enterprises are locked in their highly customized PDM/PLM environments, their legacy blocks the introduction of modern model-based and connected approaches.

Where John Stark’s book might miss the PLM details, Martin’s book brings you everything in detail and with all its references.

It is an interesting book if you want to catch up with what has happened in the past 20 years.

More Books …..

More books on my desk have helped me understand the past or that helped me shape the future. As this is a blog post, I will not discuss more books this time reaching my 1500 words.

Still books worthwhile to read – click on their images to learn more:

I discussed this book two times last year. An introduction in PLM and Modularity and a discussion with the authors and some readers of the book: The Modular Way – a follow-up discussion

x

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A book I read this summer contributed to a better understanding of sustainability. I mentioned this book in my presentation for the Swedish CATIA Forum in October last year – slide 29 of The Challenges of model-based and traditional plm. So you could see it as an introduction to System Thinking from an economic point of view.

System Thinking becomes crucial for a sustainable future, as I addressed in my post PLM and Sustainability.

Sustainability is my area of interest at the PLM Green Global Alliance, an international community of professionals working with Product Lifecycle Management (PLM) enabling technologies and collaborating for a more sustainable decarbonized circular economy.

Conclusion

There is a lot to learn. Tell us something about your PLM bookshelf – which books would you recommend. In the upcoming posts, I will further focus on PLM education. So stay tuned and keep on 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

  1. 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.
  2. 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.
  3. 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.
  4. 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
  5. 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.
  6. 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?
  7. 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.

 

 

 

 

In March 2018, I started a series of blog posts related to model-based approaches. The first post was:  Model-Based – an introduction.  The reactions to these series of posts can be summarized in two bullets:

  • Readers believed that the term model-based was focusing on the 3D CAD model. A logical association as PLM is often associated with 3D CAD-model data management (actually PDM), and in many companies, the 3D CAD model is (yet) not a major information carrier/
  • Readers were telling me that a model-based approach is too far from their day-to-day life. I have to agree here. I was active in some advanced projects where the product’s behavior depends on a combination of hardware and software. However, most companies still work in a document-driven, siloed discipline manner merging all deliverables in a BOM.

More than 3 years later, I feel that model-based approaches have become more and more visible for companies. One of the primary reasons is that companies start to collaborate in the cloud and realize the differences between a coordinated and a connected manner.

Initiatives as Industry 4.0 or concepts like the Digital Twin demand a model-based approach. This post is a follow-up to my recent post, The Future of PLM.

History has shown that it is difficult for companies to change engineering concepts. So let’s first look back at how concepts slowly changed.

The age of paper drawings

In the sixties of the previous century, the drawing board was the primary “tool” to specify a mechanical product. The drawing on its own was often a masterpiece drawn on special paper, with perspectives, details, cross-sections.

All these details were needed to transfer the part or assembly information to manufacturing. The drawing set should contain all information as there were no computers.

Making a prototype was, depending on the complexity of the product, the interpretation of the drawings and manufacturability of a product, not always that easy.  After a first release, further modifications to the product definition were often marked on the manufacturing drawings using a red pencil. Terms like blueprint and redlining come from the age of paper drawings.

There are still people talking nostalgically about these days as creating and interpreting drawings was an important skill. However, the inefficiencies with this approach were significant.

  • First, updating drawings because there was redlining in manufacturing was often not done – too much work.
  • Second, drawing reuse was almost impossible; you had to start from scratch.
  • Third, and most importantly, you needed to be very skilled in interpreting a drawing set. In particular, when dealing with suppliers that might not have the same skillset and the knowledge of which drawing version was actual.

However, paper was and still is the cheapest neutral format to distribute designs. The last time I saw companies still working with paper drawings was at the end of the previous century.

Curious to learn if they are now extinct?

The age of electronic drawings (CAD)

With the introduction of AutoCAD and personal computers around 1982, more companies started to look into drafting with the computer. There was already the IBM drafting system in 1965, but it was Autodesk that pushed the 2D drafting business with their slogan:

“80 percent of the functionality for 20 percent of the price (Autodesk 1982)”

A little later, I started to work for an Autodesk distributor/reseller. People would come to the showroom to see how a computer drawing could be plotted in the finest quality at the end. But, of course, the original draftsman did not like the computer as the screen was too small.

However, the enormous value came from making changes, the easy way of sharing drawings and the ease of reuse. The picture on the left is me in 1989, demonstrating AutoCAD with a custom-defined tablet and PS/2 computer.

The introduction of electronic drawings was not a disruption, more optimization of the previous ways of working.

The exchange with suppliers and manufacturing could still be based on plotted drawings – the most neutral format. And thanks to the filename, there was better control of versions between all stakeholders.

Aren’t we all happy?

The introduction of mainstream 3D CAD

In 1995,  3D CAD became available for the mid-market, thanks to SolidWorks, Solid Edge and a little later Inventor. Before that working with 3D CAD was only possible for companies that could afford expensive graphic stations, provided by IBM, Silicon Graphics, DEC and SUN. Where are they nowadays? The PC is an example of disruptive innovation, purely based on technology. See Clayton Christensen’s famous book: The Innovator’s Dilemma.

The introduction of 3D CAD on PCs in the mid-market did not lead directly to new ways of working. Designing a product in 3D was much more efficient if you mastered the skills. 3D brought a better understanding of the product dimensions and shape, reducing the number of interpretation errors.

Still, (electronic) drawings were the contractual deliverable when interacting with suppliers and manufacturing.  As students were more and more trained with the 3D CAD tools, the traditional art of the draftsman disappeared.

3D CAD introduced some new topics to solve.

  • First of all, a 3D CAD Assembly in the system was a collection of separate files, subassemblies, parts, and drawings that relate to each other with a specific version. So how to ensure the final assembly drawings were based on the correct part revisions? Companies were solving this by either using intelligent filenames (with revisions) or by using a PDM system where the database of the PDM system managed all the relations and their status.
  • The second point was that the 3D CAD assembly also introduced a new feature, the product structure, or the “Bill of Materials”. This logical structure of the assembly up resembled a lot of the Bill of Material of the product. You could even browse deeper levels, which was not the case in the traditional Bill of Material on a drawing.

Note: The concept of EBOM and MBOM was not known in most companies. People were talking about the BOM as a one-level definition of parts or subassemblies in the assembly. See my Where is the MBOM? Post from July 2008 when this topic was still under discussion.

  • The third point that would have a more significant impact later is that parts and assemblies could be reused in other products. This introduced the complexity of configuration management. For example, a 3D CAD part or assembly file could contain several configurations where only one configuration would be valid for the given product. Managing this in the 3D CAD system lead to higher productivity of the designer, however downstream when it came to data management with PDM systems, it became a nightmare.

I experienced these issues a lot when discussing with companies and implementers, mainly the implementation of SmarTeam combined with SolidWorks and Inventor. Where to manage the configuration constraints? In the PDM system or inside the 3D CAD system.

These environments were not friends (image above), and even if they came from the same vendor, it felt like discussing with tribes.

The third point also covered another topic. So far, CAD had been the first step for the detailed design of a product. However, companies now had an existing Bill of Material in the system thanks to the PDM systems. It could be a Bill of Material of a sub-assembly that is used in many other products.

Configuring a product no longer started from CAD; it started from a Product or Bill of Material structure. Sales and Engineers identified the changes needed on the BoM, keeping as much as possible released information untouched. This led to a new best practice.

The item-centric approach

Around 2005, five years after introducing the term Product Lifecycle Management, slowly, a new approach became the standard. Product Lifecycle Management was initially introduced to connect engineering and manufacturing, driven by the automotive and aerospace industry.

It was with PLM that concepts as EBOM and MBOM became visible.

In particular, the EBOM was closely linked to engineering practices, i.e., modularity and reuse. The EBOM and its related information represented the product as it was specified. It is essential to realize that the parts in the EBOM could be generic specified purchase parts to be resolved when producing the product or that the EBOM contained Make-parts specified by drawings.

At that time, the EBOM was often used as the foundation for the ERP system – see image above. The BOM was restructured and organized according to the manufacturing process specifying materials and resources needed in the ERP system. Therefore, although it was an item-like structure, this BOM (the MBOM) always had a close relation to the Bill of Process.

For companies with a single manufacturing site, the notion of EBOM and MBOM was not that big, as the ERP system would be the source of the MBOM. However, the complexity came when companies have several manufacturing sites. That was when a generic MBOM in the PLM system made more sense to centralize all product information in a single system.

The EBOM-MBOM approach has become more and more a standard practice since 2010. As a result, even small and medium-sized enterprises realized a need to manage the EBOM and the MBOM.

There were two disadvantages introduced with this EBOM-MBOM approach.

  • First, the EBOM and the MBOM as information structures require a lot of administrative maintenance if information needs to be always correct (and that is the CM target).  Some try to simplify this by keeping the EBOM part the same as the MBOM part, meaning the EBOM specification already targets a single supplier or manufacturer.
  • The second disadvantage of making every item in the BOM behave like a part creates inefficiencies in modern environments. Products are a mix of hardware(parts) and software(models/behavior). This BOM-centric view does not provide the proper infrastructure for a data-driven approach as part specifications are still done in drawings. We need 3D annotated models related to all kinds of other behavior and physical models to specify a product that contains hard-and software.

A new paradigm is needed to manage this mix efficiently, the enabling foundation for Industry 4.0 and efficient Digital Twins; there is a need for a model-based approach based on connected data elements.

More next week.

Conclusion

The age of paper drawings 1960 – now dead
The age of electronic drawings 1982 – potentially dead in 2030
The mainstream 3D CAD 1995 – to be evolving through MBD and MBSE to the future – not dead shortly
Item-centric approach 2005 – to be evolving to a connected model-based approach – not dead shortly

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 researchGlobal 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:

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.

Next, I will discuss with Jennifer Herron from Action Engineering the progress made in Model-Based Definition, which fits best practices for today – a better connection between engineering and manufacturing. We will also discuss why Model-Based Definition is a significant building block required for realizing the concepts of a digital enterprise, Industry 4.0 and digital twins.

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

 

 

 

For a year, we are now used to virtual events. PI PLMx 2020 in London was my last real event where I met people. When rereading my post about this event (the weekend after PI PLMx), I wrote that it was not a technology festival. Many presentations were about business change and how to engage people in an organization.

The networking discussions during the event and evenings were the most valuable parts of the conference.

And then came COVID-19. ☹

Shortly after, in April 2020, I participated in the TECHNIA Innovation Forum, which was the first virtual conference with a setup like a conference. A main stage, with live sessions, virtual booths, and many prerecorded sessions related to various PLM topics.

You can read my experience related to the conference in two posts: the weekend after PLMIF and My four picks from PLMIF. A lot of content available for 30 days. However, I was missing the social interaction, the people.

My favourite conference for 2020 was the CIMdata PLM Roadmap / PDT Fall 2020 conference in November. The PLM Roadmap/PDT conferences are not conferences for a novice audience; you have to be skilled in the domain of PLM most of the time with a strong presence from Aerospace and Defense companies.

The Fall 2020 theme: “Digital Thread—the PLM Professionals’ Path to Delivering Innovation, Efficiency, and Quality” might sound like a marketing term.

We hear so many times the words Digital Thread and Digital Twin. However, this conference was with speakers, active practitioners, from the field.  I wrote about this conference in two posts: The weekend after PLM Roadmap / PDT 2020 – Part 1 and Part 2. I enjoyed the conference; however, I was missing social interaction.

The Digital Twin

Beyond the marketing hype, there is still a lot to learn and discuss from each other. First of all, it is not about realizing a digital twin; a business need should be the driver to investigate the possibility of a digital twin.

I am preparing a longer blog post on this topic to share learnings from people in the field. For example, in November 2020, I participated in the Netherlands in a Digital Twin Conference, focusing on real-life cases.

Companies shared their vision and successes.  It was clear that we are all learning to solve pieces of the big puzzle; there are small successes. However, without marketing language, this type of event becomes extremely helpful for further discussion and follow-up.

Recently, I enjoyed the panel discussions during the PI DX Spotlight session: Digital Twin-Driven Design. The PI DX Spotlight sessions are a collection of deep dives in various themes – have a look for the upcoming schedule here.

In the Digital Twin-Driven Design session, I enjoyed the session: What does a Digital Twin mean to your Business and Defining Requirements?

The discussion was moderated by Peter Bilello, with three interesting panellists with different industrial backgrounds. (Click on the image for the details). I have to re-watch some of the Spotlight sessions (the beauty of a virtual event) to see how they fit in the planned Digital Twin post.

 

 

The Cenit/Keonys Innovation day

On March 23rd (this Tuesday), Cenit & Keonys launch their virtual Innovation Day, another event that, before COVID-19, would have been a real people event. I am mentioning this event in particular, as I was allowed to interview fifteen of their customers about their day-to-day work, PLM-related plans, and activities.

All these interviews have been recorded and processed in such a manner that within 5 to 8 minutes, you get an understanding of what people are doing.

To prepare for these interviews, I spoke with each of them before the interview. I wanted to understand the passion for their work and where our interests overlap.

I will not mention the individual interviews in this post, as I do not want to spoil the event. I talked with various startups (do they need PLM?)  and established companies that started a PLM journey. I spoke with simulation experts (the future) and dimensional management experts (listen to these interviews to understand what it means). And ultimately, I interviewed a traditional porcelain family brand using 3D printing and 3D design, and at the other end, the German CIO of the year from 2020

(if you Google a little, you will easily find the companies involved here)

The most common topics discussed were:

  • What was the business value of your PLM-related activity?
  • Did COVID-19 impact your business?
  • What about a cloud-based solution, and how do people align?
  • If relevant, what are your experiences with a Model-Based Definition?
  • What about sustainability?

I hope you will take the opportunity to register and watch these interviews as, for me, they were an excellent opportunity to be in touch with the reality in the field. As always, we keep on learning.

The Modular Way

Talking about learning. This week, I finished the book The Modular Way, written by Bjorn Eriksson & Daniel Strandhammar.  During the lockdown last year, Bjorn & Daniel, founders of the Brick Strategy, decided to write down their experiences with mainly Scandinavian companies into a coherent framework to achieve modularization.

Modularity is a popular topic in many board meetings. How often have you heard:  “We want to move from Engineering To Order to more Configure To Order”? Or another related incentive: “We need to be cleverer with our product offering and reduced the number of different parts”.

Next, the company buys a product that supports modularity, and management believes the work has been done. Of course, not. Modularity requires a thoughtful strategy.

Illustration from the book: The Modular Way

The book can be a catalyst for such companies that want to invest in modularity but do not know where and how to start. The book is not written academically. It is more a story taking you along the steps needed to define, implement, and maintain modularity. Every step has been illustrated by actual cases and their business motivation and achieved benefits where possible. I plan to come back with Bjorn and Daniel in a dedicated post related to PLM and Modularity.

Conclusion

Virtual Events are probably part of our new future. A significant advantage is the global reach of such events. Everyone can join from anywhere connected around the world. Besides the larger events, I look forward to discovering more small and targeted discussion events like PI DX Spotlights. The main challenge for all – keep it interactive and social.

Let us know your favourite virtual event !!

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  1. Jos, one could take the approach that there is an engineering transformation strategy that can be realized by implementing PLM…

  2. Jos, I agree we should break out from the monolithic approach as this typically means lock-in, risk and frustration. The…

  3. Jos, Thanks for these insights. I believe that the mature capabilities provided by advanced toolsets can also be of benefit…

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