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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.

 

Last week I wrote about the recent PLM Road Map & PDT Spring 2021 conference day 1, focusing mainly on technology. There were also interesting sessions related to exploring future methodologies for a digital enterprise. Now on Day 2, we started with two sessions related to people and methodology, indispensable when discussing PLM topics.

Designing and Keeping Great Teams

This keynote speech from Noshir Contractor, Professor of Behavioral Sciences in the McCormick School of Engineering & Applied Science, intrigued me as the subtitle states: Lessons from Preparing for Mars. What Can PLM Professionals Learn from This?

You might ask yourself, is a PLM implementation as difficult and as complex as a mission to Mars? I hoped, so I followed with great interest Noshir’s presentation.

Noshir started by mentioning that many disruptive technologies have emerged in recent years, like Teams, Slack, Yammer and many more.

The interesting question he asked in the context of PLM is:

As the domain of PLM is all about trying to optimize effective collaboration, this is a fair question

Structural Signatures

Noshir shared with us that it is not the most crucial point to look at people’s individual skills but more about who they know.
Measure who they work with is more important than who they are.

Based on this statement, Noshir showed some network patterns of different types of networks.

Click on the image to see the enlarged picture.

It is clear from these patterns how organizations communicate internally and/or externally. It would be an interesting exercise to perform in a company and to see if the analysis matches the perceived reality.

Noshir’s research was used by NASA to analyze and predict the right teams for a mission to Mars.

Noshir went further by proposing what PLM can learn from teams that are going into space. And here, I was not sure about the parallel. Is a PLM project comparable to a mission to Mars? I hope not! I have always advocated that a PLM implementation is a journey. Still, I never imagined that it could be a journey into the remote unknown.

Noshir explained that they had built tools based on their scientific model to describe and predict how teams could evolve over time. He believes that society can also benefit from these learnings. Many inventions from the past were driven by innovations coming from space programs.

I believe Noshir’s approach related to team analysis is much more critical for organizations with a mission. How do you build multidisciplinary teams?

The proposed methodology is probably best for a holocracy based organization. Holocrazy is an interesting concept for companies to get their employees committed, however, it also demands a type of involvement that not every person can deliver.  For me, coming back to PLM, as a strategy to enable collaboration, the effectiveness of collaboration depends very much on the organizational culture and created structure.

DISRUPTION – EXTINCTION or still EVOLUTION?

We talk a lot about disruption because disruption is a painful process that you do not like to happen to yourself or your company. In the context of this conference’s theme, I discussed the awareness that disruptive technologies will be changing the PLM Value equation.

However, disruptive technologies are not alone sufficient. In PLM, we have to deal with legacy data, legacy processes, legacy organization structures, and often legacy people.

A disruption like the switch from mini-computers to PCs (killed DEC) or from Symbian to iOS (killed Nokia) is therefore not likely to happen that fast. Still, there is a need to take benefit from these new disruptive technologies.

My presentation was focusing on describing the path of evolution and focus areas for the PLM community. Doing nothing means extinction; experimenting and learning towards the future will provide an evolutionary way.

Starting from acknowledging that there is an incompatibility between data produced most of the time now and the data needed in the future, I explained my theme: From Coordinated to Connected. As a PLM community, we should spend more time together in focus groups, conferences on describing and verifying methodology and best practices.

Nigel Shaw (EuroStep) and Mark Williams (Boeing) hinted in this direction during this conference  (see day 1). Erik Herzog (SAAB Aeronautics) brought this topic to last year’s conference (see day 3). Outside this conference, I have comparable touchpoints with Martijn Dullaert when discussing Configuration Management in the future in relation to PLM.

In addition, this decade will probably be the most disruptive decade we have known in humanity due to external forces that push companies to change. Sustainability regulations from governments (the Paris agreement),  the implementation of circular economy concepts combined with the positive and high Total Share Holder return will push companies to adapt themselves more radical than before.

What is clear is that disruptive technologies and concepts, like Industry 4.0, Digital Thread and Digital Twin, can serve a purpose when implemented efficiently, ensuring the business becomes sustainable.

Due to the lack of end-to-end experience, we need focus groups and conferences to share progress and lessons learned. And we do not need to hear the isolated vendor success stories here as a reference, as often they are siloed again and leading to proprietary environments.

You can see my full presentation on SlideShare: DISRUPTION – EXTINCTION or still EVOLUTION?

 

Building a profitable Digital T(win) business

Beatrice Gasser,  Technical, Innovation, and Sustainable Development Director from the Egis group, gave an exciting presentation related to the vision and implementation of digital twins in the construction industry.

The Egis group both serves as a consultancy firm as well as an asset management organization. You can see a wide variety of activities on their website or have a look at their perspectives

Historically the construction industry has been lagging behind having low productivity due to fragmentation, risk aversion and recently, more and more due to the lack of digital talent. In addition, some of the construction companies make their money from claims inside of having a smooth and profitable business model.

Without innovation in the construction industry, companies working the traditional way would lose market share and investor-focused attention, as we can see from the BCG diagram I discussed in my session.

The digital twin of construction is an ideal concept for the future. It can be built in the design phase to align all stakeholders, validate and integrate solutions and simulate the building operational scenarios at almost zero materials cost. Egis estimates that by using a digital twin during construction, the engineering and construction costs of a building can be reduced between 15 and 25 %

More importantly, the digital twin can also be used to first simulate operations and optimize energy consumption. The connected digital twin of an existing building can serve as a new common data environment for future building stakeholders. This could be the asset owner, service companies, and even the regulatory authorities needing to validate the building’s safety and environmental impact.

Beatrice ended with five principles essential to establish a digital twin, i.e

I think the construction industry has a vast potential to disrupt itself. Faster than the traditional manufacturing industries due to their current needs to work in a best-connected manner.

Next, there is almost no legacy data to deal with for these companies. Every new construction or building is a unique project on its own. The key differentiators will be experience and efficient ways of working.

It is about the belief, the guts and the skilled people that can make it work – all for a more efficient and sustainable future.

 

 

Leveraging PLM and Cloud Technology for Market Success

Stan Przybylinski, Vice President of CIMdata, reported their global survey related to the cloud, completed in early 2021.  Also, Stan typified Industry 4.0 as a connected vision and cloud and digital thread as enablers to implementing this vision.

The companies interviewed showed a lot of goodwill to make progress – click on the image to see the details. CIMdata is also working with PLM Vendors to learn and describe better the areas of beneft. I remain curious about who comes with a realization and business case that is future-proof. This will define our new PLM Value Equation.

 

Conclusion

These were two exciting days with enough mentioning of disruptive technologies. Our challenge in the PLM domain will be to give them a purpose. A purpose is likely driven by external factors related to the need for a sustainable future.  Efficiency and effectiveness must come from learning to work in connected environments (digital twin, digital thread, industry 4.0, Model-Based (Systems) Engineering.

Note: You might have seen the image below already – a nice link between sustainability and the mission to Mars

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

 

 

 

Another episode of “The PLM Doctor is IN“. This time a question from Rob Ferrone. Rob is one of the founders of QuickRelease, a passionate, no-nonsense PDM/PLM consultancy company focusing on process improvement.

Now sit back and enjoy.

PLM and Digital Plumbing
What’s inside the digital plumber’s toolbox?

Relevant topic discussed in this video

Inside this video you see a slide from Marc Halpern (Gartner), depicting the digital thread during the last PLM Roadmap – PDT conference – fall 2020. This conference is THE place for more serious content and I am happy to announce my participation and anxiety for the next upcoming PLM Roadmap – PDT conference on May 19-20.

The theme: DISRUPTION—the PLM Professionals’ Exploration of Emerging Technologies that Will Reshape the PLM Value Equation.

Looking forward to seeing you there.

Conclusion

I hope you enjoyed the answer and look forward to your questions and comments. Let me know if you want to be an actor in one of the episodes.
The main rule: A single open question that is puzzling you related to PLM.

This time in the series of complementary practices to PLM, I am happy to discuss product modularity. In my previous post related to Virtual Events, I mentioned I had finished reading the book “The Modular Way”, written by Björn Eriksson & Daniel Strandhammar, founders of the consulting company Brick Strategy.

The first time I got aware of Brick Strategy was precisely a year ago during the Technia Innovation Forum, the first virtual event I attended since COVID-19. Daniel’s presentation at that event was one of the four highlights that I shared about the conference. See My four picks from PLMIF.

As I wrote in my last post:

Modularity is a popular topic in many board meetings. How often have you heard: “We want to move from Engineering To Order (ETO) to more Configure To Order (CTO)”? 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.

I am now happy to have a dialogue with Daniel to learn and understand Brick Strategy’s view on PLM and Modularization. Are these topics connected? Can one live without the other? Stay tuned till the end if you still have questions for a pleasant surprise.

The Modular Way


Daniel, first of all, can you give us some background and intentions of the book “The Modular Way”?

 

Let me start by putting the book in perspective. In today’s globalized business, competition among industrial companies has become increasingly challenging with rapidly evolving technology, quickly changing customer behavior, and accelerated product lifecycles. Many companies struggle with low profitability.

To survive, companies need to master product customizations, launch great products quickly, and be cost-efficient – all at the same time. Modularization is a good solution for industrial companies with ambitions to improve their competitiveness significantly.

The aim of modularization is to create a module system. It is a collection of pre-defined modules with standardized interfaces. From this, you can build products to cater to individual customer needs while keeping costs low. The main difference from traditional product development is that you develop a set of building blocks or modules rather than specific products.

The Modular Way explains the concept of modularization and the ”how-to.” It is a comprehensive and practical guidebook, providing you with inspiration, a framework, and essential details to succeed with your journey. The book is based on our experience and insights from some of the world’s leading companies.

Björn and I have long thought about writing a book to share our combined modularization experience and learnings. Until recently, we have been fully busy supporting our client companies, but the halted activities during the peak of the COVID-19 pandemic gave us the perfect opportunity.

PLM and Modularity


Did you have PLM in mind when writing the book?

 

Yes, definitely. We believe that modularization and a modular way of working make product lifecycle management more efficient. Then we talk foremost about the processes, roles, product structure, decision making etc. Companies often need minor adjustments to their IT systems to support and sustain the new way of working.

Companies benefit the most from modularization when the contents, or foremost the products, are well structured for configuration in streamlined processes.

Many times, this means “thinking ahead” and preparing your products for more configuration and less engineering in the sales process, i.e., go from ETO to CTO.

Modularity for Everybody?

It seems like the modularity concept is prevalent in the Scandinavian countries, with famous examples of Scania, LEGO, IKEA, and Electrolux mentioned in your book. These examples come from different industries. Does it mean that all companies could pursue modularity, or are there some constraints?

We believe that companies designing and manufacturing products fulfilling different customer needs within a defined scope could benefit from modularization. Off-the-shelf content, commonality and reuse increase efficiency. However, the focus, approach and benefits are different among different types of companies.

We have, for example, seen low-volume companies expecting the same benefits as high-volume consumer companies. This is unfortunately not the case.

Companies can improve their ability and reduce the efforts to configure products to individual needs, i.e., customization. And when it comes to cost and efficiency improvements, high-volume companies can reduce product and operational costs.

Image:

Low-volume companies can shorten lead time and increase efficiency in R&D and product maintenance. Project solution companies can shorten the delivery time through reduced engineering efforts.

 

As an example, Electrolux managed to reduce part costs by 20 percent. Half of the reduction came from volume effects and the rest from design for manufacturing and assembly.

All in all, Electrolux has estimated its operating cost savings at approximately SEK 4bn per year with full effect, or around 3.5 percentage points of total costs, compared to doing nothing from 2010–2017. Note: SEK 4 bn is approximate Euro 400 Mio

 

Where to start?

Thanks to your answer, I understand my company will benefit from modularity. To whom should I talk in my company to get started? And if you would recommend an executive sponsor in my company, who would recommend leading this initiative.

Defining a modular system, and implementing a modular way of working, is a business-strategic undertaking. It is complex and has enterprise-wide implications that will affect most parts of the organization. Therefore, your management team needs to be aligned, engaged, and prioritize the initiative.

The implementation requires a cross-functional team to ensure that you do it from a market and value chain perspective. Modularization is not something that your engineering or IT organization can solve on its own.

We recommend that the CTO or CEO owns the initiative as it requires horizontal coordination and agreement.

Modularity and Digital Transformation

 The experiences you are sharing started before digital transformation became a buzzword and practice in many companies. In particular, in the PLM domain, companies are still implementing past practices. Is modularization applicable for the current (coordinated) and for the (connected) future? And if yes, is there a difference?

Modularization means that your products have a uniform design based on common concepts and standardized interfaces. To the market, the end products are unique, and your processes are consistent. Thus, modularization plays a role independently of where you are on the digital transformation journey.

Digital transformation will continue for quite some time. Costs can be driven down even further through digitalization, enabling companies to address the connection of all value chain elements to streamline processes and accelerate speed to market. Digitalization will enhance the customer experience by connecting all relevant parts of the value chain and provide seamless interactions.

Industry 4.0 is an essential part of digitalization, and many companies are planning further investments. However, before considering investing in robotics and digital equipment for the production system, your products need to be well prepared.

image

The more complex products you have, the less efficient and costlier the production is, even with advanced production lines. Applying modularization means that your products have a uniform design based on common concepts and standardized interfaces. To the market, the end products are unique, and your production process is consistent. Thus, modularization increases the value of Industry 4.0. 

Want to learn more?

First of all, I recommend people who are new to modularity to read the book as a starting point as it is written for a broad audience. Now I want to learn more. What can you recommend?

As you say,  we also encourage you to read the book, reflect on it, and adapt the knowledge to your unique situation. We know that it could be challenging to take the next steps, so you are welcome to contact us for advice.

Please visit our website www.brickstrategy.com for more.

For readers of the book, we plan to organize a virtual meeting in May 2021 -the date and time to be confirmed with the audience. Duration approx. 1 hour.
Björn Eriksson and Daniel Strandhammar will answer questions from participants in the meeting. Also, we are curious about your comments/feedback.

To allow time for a proper discussion, we will invite a maximum of 4 guests. Therefore be fast to apply for this virtual meeting by sending an email to tacit@planet.nl or info@brickstrategy.com with your contact details
before May 7th.

I will moderate and record the meeting. We will publish the recording in a short post, allowing everyone to benefit from the discussion. Stay tuned if you are interested, and be fast to apply if you have a question to ask.

What I learned

  • Modularization is a strategy that applies to almost every business and increases the competitiveness of a company.
  • Modularization is not a technical decision to be executed by R&D and Engineering. It requires an effort from all stakeholders in the company. Therefore, it should be led by a CEO or CTO.
  • For future products, modularization is even more important to fulfill one of the promises of Industry 4.0: batch-size 1 (manufacturing a unique product for a single customer with the cost and effort as if it were done in a serial production mode)
  • Although we talk a lot about modularization in PLM implementations, it is a people and processes first activity. Then the PLM infrastructure has to support modularization. Do not buy a PLM system to start modularization. Think first!

Conclusion

Modularization is a popular topic at board meetings as it is easy to explain the business benefits. People in engineering and marketing often miss the time and skills to translate modularization into a framework that aligns all stakeholders. After reading the book “The Modular Way,” you will not have solved this issue. There are many, more academic books related to modularization. With this book, you will be better aware of where to start and how to focus.

There is another interesting virtual event in May: the CIMdata PLM Road Map & PDT Spring 2021conference. The theme:

DISRUPTION—the PLM Professionals’ Exploration of Emerging Technologies that Will Reshape the PLM Value Equation.

I look forward to seeing you at this conference and discuss and learn together the changes we have to make – DISRUPTION or EXTINCTION or EVOLUTION. More on this topic soon.

After the series about “Learning from the past,” it is time to start looking towards the future.  I learned from several discussions that I am probably working most of the time with advanced companies. I believe this would motivate companies that lag behind even to look into the future even more.

If you look into the future for your company, you need new or better business outcomes. That should be the driver for your company. A company does not need PLM or a Digital Twin. A company might want to reduce its time to market, improve collaboration between all stakeholders. These objectives can be realized by different ways of working and an IT-infrastructure to allow these processes to become digital and connected.

That is the “game”. Coming back to the future of PLM.  We do not need a discussion about definitions; I leave this to the academics and vendors. We will see the same applies to the concept of a Digital Twin.

My statement: The digital twin is not new. Everybody can have their own digital twin as long as you interpret the definition differently. Does this sound like the PLM definition?

The definition

I like to follow the Gartner definition:

A digital twin is a digital representation of a real-world entity or system. The implementation of a digital twin is an encapsulated software object or model that mirrors a unique physical object, process, organization, person, or other abstraction. Data from multiple digital twins can be aggregated for a composite view across a number of real-world entities, such as a power plant or a city, and their related processes.

As you see, not a narrow definition. Now we will look at the different types of interpretations.

Single-purpose siloed Digital Twins

  1. Simple – data only

One of the most straightforward applications of a digital twin is, for example, my Garmin Connect environment. When cycling, my device registers performance parameters (speed, cadence, power, heartbeat, location). After every trip, I can analyze my performance. I can see changes in my overall performance; compare my performance with others in my category (weight, age, sex).

Based on that, I can decide if I want to improve my performance. My personal business goal is to maintain and improve my overall performance, knowing I cannot stop aging by upgrading my body.

On November 4th, 2020, I am participating in the (almost virtual) Digital Twin conference organized by Bits&Chips in the Netherlands. In the context of human performance, I look forward to Natal van Riel’s presentation: Towards the metabolic digital twin – for sure, this direction is not simple. Natal is a full professor at the Technical University in Eindhoven, the “smart city” in the Netherlands

  1. Medium – data and operating models

Many connected devices in the world use the same principle. An airplane engine, an industrial robot, a wind turbine, a medical device, and a train carriage; all track the performance based on this connection between physical and virtual, based on some sort of digital connectivity.

The business case here is also monitoring performance, predict maintenance, and upgrade the product when needed.

This is the domain of Asset Lifecycle Management, a practice that exists for decades. Based on financial and performance models, the optimal balance between maintaining and overhaul has to be found. Repairs are disruptive and can be extremely costly. A manufacturing site that cannot produce can costs millions per day. Connecting data between the physical and the virtual model allows us to have real-time insights and be proactive. It becomes a digital twin.

  1. Advanced – data and connected 3D model

The ditial twin we see the most in marketing videos is a virtual twin, using a 3D-representation for understanding and navigation.  The 3D-representation provides a Virtual Reality (VR) environment with connected data. When pointing at the virtual components, information might appear, or some animation takes place.

Building such a virtual representation is a significant effort; therefore, there needs to be a serious business case.

The simplest business case is to use the virtual twin for training purposes. A flight simulator provides a virtual environment and behavior as-if you are flying in the physical airplane – the behavior model behind the simulator should match as good as possible the real behavior. However, as it is a model, it will never be 100 % reality and requires updates when new findings or product changes appear.

A virtual model of a platform or plant can be used for training on Standard Operating Procedures (SOPs). In the physical world, there is no place or time to conduct such training. Here the complexity might be lower. There is a 3D Model; however, serious updates can only be expected after a major maintenance or overhaul activity.

These practices are not new either and are used in places where the physical training cannot be done.

More challenging is the Augmented Reality (AR) use case. Here the virtual model, most of the time, a lightweight 3D Model, connects to real-time data coming from other sources. For example, AR can be used when an engineer has to service a machine. The AR-environment might project actual data from the machine, indicate service points and service procedures.

The positive side of the business case is clear for such an opportunity, ensuring service engineers always work with the right information in a real-time context. The main obstacle for implementing AR, in reality, is the access to data, the presentation of the data and keeping the data in the AR-environment matching the reality.

And although there are 3D Models in use, they are, to my knowledge, always created in siloes, not yet connected to their design sources.Have a look at the Digital Twin conference from Bits&Chips, as mentioned before.

Several of the cases mentioned above will be discussed here. The conference’s target is to share real cases concluded by Q & A sessions, crucial for a virtual event.

Connected Virtual Twins along the product lifecycle

So far, we have been discussing the virtual twin concept, where we connect a product/system/person in the physical world to a virtual model. Now let us zoom in on the virtual twins relevant for the early parts of the product lifecycle, the manufacturing twin, and the development twin. This image from Siemens illustrates the concept:

On slides they imagine a complete integrated framework, which is the future vision. Let us first zoom in on the individual connected twins.

The digital production twin

This is the area of virtual manufacturing and creating a virtual model of the manufacturing plant. Virtual manufacturing planning is not a new topic. DELMIA (Dassault Systèmes) and Tecnomatix (Siemens) are already for a long time offering virtual manufacturing planning solutions.

At that time, the business case was based on the fact that the definition of a manufacturing plant and process done virtually allows you to optimize the plant before investing in physical assets.

Saving money as there is no costly prototype phase to optimize production. In a virtual world, you can perform many trade-off studies without extra costs. That was the past (and for many companies still the current situation).

With the need to be more flexible in manufacturing to address individual customer orders without increasing the overhead of delivering these customer-specific solutions, there is a need for a configurable plant that can produce these individual products (batch size 1).

This is where the virtual plant model comes into the picture again. Instead of having a virtual model to define the ultimate physical plant, now the virtual model remains an active model to propose and configure the production process for each of these individual products in the physical plant.

This is partly what Industry 4.0 is about. Using a model-based approach to configure the plant and its assets in a connected manner. The digital production twin drives the execution of the physical plant. The factory has to change from a static factory to a dynamic “smart” factory.

In the domain of Industry 4.0, companies are reporting progress. However, to my experience, the main challenge is still that the product source data is not yet built in a model-based, configurable manner. Therefore, requiring manual rework. This is the area of Model-Based Definition, and I have been writing about this aspect several times. Latest post: Model-Based: Connecting Engineering and Manufacturing

The business case for this type of digital twin, of course, is to be able to customer-specific products with extremely competitive speed and reduced cost compared to standard. It could be your company’s survival strategy. As it is hard to predict the future, as we see from COVID-19, it is still crucial to anticipate the future, instead of waiting.

The digital development twin

Before a product gets manufactured, there is a product development process. In the past, this was pure mechanical with some electronic components. Nowadays, many companies are actually manufacturing systems as the software controlling the product plays a significant role. In this context, the model-based systems engineering approach is the upcoming approach to defining and testing a system virtually before committing to the physical world.

Model-Based Systems Engineering can define a single complex product and perform all kinds of analysis on the system even before there is a physical system in place.  I will explain more about model-based systems engineering in future posts. In this context, I want to stress that having a model-based system engineering environment combined with modularity (do not confuse it with model-based) is a solid foundation for dealing with unique custom products. Solutions can be configured and validated against their requirements already during the engineering phase.

The business case for the digital development twin is easy to make. Shorter time to market, improved and validated quality, and reduced engineering hours and costs compared to traditional ways of working. To achieve these results,  for sure, you need to change your ways of working and the tools you are using. So it won’t be that easy!

For those interested in Industry 4.0 and the Model-Based System Engineering approach, join me at the upcoming PLM Road Map 2020 and PDT 2020 conference on 17-18-19 November. As you can see from the agenda, a lot of attention to the Digital Twin and Model-Based approaches.

Three digital half-days with hopefully a lot to learn and stay with our feet on the ground.  In particular, I am looking forward to Marc Halpern’s keynote speech: Digital Thread: Be Careful What you Wish For, It Just Might Come True

Conclusion

It has been very noisy on the internet related to product features and technologies, probably due to COVIC-19 and therefore disrupted interactions between all of us – vendors, implementers and companies trying to adjust their future. The Digital Twin concept is an excellent framing for a concept that everyone can relate to. Choose your business case and then look for the best matching twin.

In the series learning from the past to understand the future, we have almost reached the current state of PLM before digitization became visible. In the last post, I introduced the value of having the MBOM preparation inside a PLM-system, so manufacturing engineering can benefit from early visibility and richer product context when preparing the manufacturing process.

Does everyone need an MBOM?

It is essential to realize that you do not need an EBOM and a separate MBOM in case of an Engineering To Order primary process. The target of ETO is to deliver a unique customer product with no time to lose. Therefore, engineering can design with a manufacturing process in mind.

The need for an MBOM comes when:

  • You are selling a specific product over a more extended period of time. The engineering definition, in that case, needs to be as little as possible dependent on supplier-specific parts.
  • You are delivering your portfolio based on modules. Modules need to be as long as possible stable, therefore independent of where they are manufactured and supplier-specific parts. The better you can define your modules, the more customers you can reach over time.
  • You are having multiple manufacturing locations around the world, allowing you to source locally and manufacture based on local plant-specific resources. I described these options in the previous post

The challenge for all companies that want to move from ETO to BTO/CTO is the fact that they need to change their methodology – building for the future while supporting the past. This is typically something to be analyzed per company on how to deal with the existing legacy and installed base.

Configurable EBOM and MBOM

In some previous posts, I mentioned that it is efficient to have a configurable EBOM. This means that various options and variants are managed in the same EBOM-structure that can be filtered based on configuration parameters (date effectivity/version identifier/time baseline). A configurable EBOM is often called a 150 % EBOM

The MBOM can also be configurable as a manufacturing plant might have almost common manufacturing steps for different product variants. By using the same process and filtered MBOM, you will manufacture the specific product version. In that case, we can talk about a 120 % MBOM

Note: the freedom of configuration in the EBOM is generally higher than the options in the configurable MBOM.

The real business change for EBOM/MBOM

So far, we have discussed the EBOM/MBOM methodology. It is essential to realize this methodology only brings value when the organization will be adapted to benefit from the new possibilities.

One of the recurring errors in PLM implementations is that users of the system get an extended job scope, without giving them the extra time to perform these activities. Meanwhile, other persons downstream might benefit from these activities. However, they will not complain. I realized that already in 2009, I mentioned such a case: Where is my PLM ROI, Mr. Voskuil?

Now let us look at the recommended business changes when implementing an EBOM/MBOM-strategy

  1. Working in a single, shared environment for engineering and manufacturing preparation is the first step to take.

Working in a PLM-system is not a problem for engineers who are used to the complexity of a PDM-system. For manufacturing engineers, a PLM-environment will be completely new. Manufacturing engineers might prepare their bill of process first in Excel and ultimately enter the complete details in their ERP-system. ERP-systems are not known for their user-friendliness. However, their interfaces are often so rigid that it is not difficult to master the process. Excel, on the other side, is extremely flexible but not connected to anything else.

And now, this new PLM-system requires people to work in a more user-friendly environment with limited freedom. This is a significant shift in working methodology. This means manufacturing engineers need to be trained and supported  over several months. Changing habits and keep people motivated takes energy and time. In reality, where is the budget for these activities?  See my 2016 post: PLM and Cultural Change Management – too expensive?

  1. From sequential to concurrent

Once your manufacturing engineers are able to work in a PLM-environment, they are able to start the manufacturing definition before the engineering definition is released. Manufacturing engineers can participate in design reviews having the information in their environment available. They can validate critical manufacturing steps and discuss with engineers potential changes that will reduce the complexity or cost for manufacturing. As these changes will be done before the product is released, the cost of change is much lower. After all, having engineering and manufacturing working partially in parallel will reduce time to market.

Reducing time to market by concurrent engineering

One of the leading business drivers for many companies is introducing products or enhancements to the market. Bringing engineering and manufacturing preparation together also means that the PLM-system can no longer be an engineering tool under the responsibility of the engineering department.

The responsibility for PLM needs to be at a level higher in the organization to ensure well-balanced choices. A higher level in the organization automatically means more attention for business benefits and less attention for functions and features.

From technology to methodology – interface issues?

The whole EBOM/MBOM-discussion often has become a discussion related to a PLM-system and an ERP-system. Next, the discussion diverted to how these two systems could work together, changing the mindset to the complexity of interfaces instead of focusing on the logical flow of information.

In an earlier PI Event in München 2016, I lead a focus group related to the PLM and ERP interaction. The discussion was not about technology, all about focusing on what is the logical flow of information. From initial creation towards formal usage in a product definition (EBOM/MBOM).

What became clear from this workshop and other customer engagements is that people are often locked in their siloed way of thinking. Proposed information flows are based on system capabilities, not on the ideal flow of information. This is often the reason why a PLM/ERP-interface becomes complicated and expensive. System integrators do not want to push for organizational change, they prefer to develop an interface that adheres to the current customer expectations.

SAP has always been promoting that they do not need an interface between engineering and manufacturing as their data management starts from the EBOM. They forgot to mention that they have a difficult time (and almost no intention) to manage the early ideation and design phase. As a Dutch SAP country manager once told me: “Engineers are resources that do not want to be managed.” This remark says all about the mindset of ERP.

After overlooking successful PLM-implementations, I can tell the PLM-ERP interface has never been a technical issue once the methodology is transparent. A company needs to agree on logical data flow from ideation through engineering towards design is the foundation.

It is not about owning data and where to store it in a single system. It is about federated data sets that exist in different systems and that are complementary but connected, requiring data governance and master data management.

The SAP-Siemens partnership

In the context of the previous paragraph, the messaging around the recently announced partnership between SAP and Siemens made me curious. Almost everyone has shared an opinion about the partnership. There is a lot of speculation, and many questions were imaginarily answered by as many blog posts in the field. Last week Stan Przybylinski shared CIMdata’s interpretations in a webinar Putting the SAP-Siemens Partnership In Context, which was, in my opinion, the most in-depth analysis I have seen.

For what it is worth, my analysis:

  • First of all, the partnership is a merger of slide decks at this moment, aiming to show to a potential customer that in the SAP/Siemens-combination, you find everything you need. A merger of slides does not mean everything works together.

  • It is a merger of two different worlds. You can call SAP a real data platform with connected data, where Siemens offering is based on the Teamcenter backbone providing a foundation for a coordinated approach. In the coordinated approach, the data flexibility is lower. For that reason, Mendix is crucial to make Siemens portfolio behave like a connected platform too.
    You can read my doubts about having a coordinated and connected system working together (see image above). It was my #1 identified challenge for this decade: PLM 2020 – PLM the next decade (before COVID-19 became a pandemic and illustrated we need to work connected)
  • The fact that SAP will sell TC PLM and Siemens will sell SAP PPM seems like loser’s statement, meaning our SAP PLM is probably not good enough, or our TC PPM capabilities are not good enough. In reality, I believe they both should remain, and the partnership should work on logical data flows with data residing in two locations – the federated approach. This is how platforms reside next to each other instead of the single black hole.

  • The fact that standard interfaces will be developed between the two systems is a subtle sales argument with relatively low value. As I wrote in the “from technology to methodology”-paragraph, the challenges are in the organizational change within companies. Technology is not the issue, although system integrators also need to make a living.
  • What I believe makes sense is that both SAP and Siemens, have to realize their Industry 4.0 end-to-end capabilities. It is a German vision now for several years and it is an excellent vision to strive for. Now it is time to build the two platforms working together. This will be a significant technical challenge mainly for Siemens as its foundation is based on a coordinated backbone.
  • The biggest challenge, not only for this partnership, is the organizational change within companies that want to build an end-to-end connected solution. In particular, in companies with a vast legacy, the targeted industries by the partnership, the chasm between coordinated legacy data and intended connected data is enormous. Technology will not fix it, perhaps smoothen the pain a little.

 

Conclusion

With this post, we have reached the foundation of the item-centric approach for PLM, where the EBOM and MBOM are managed in a real-time context. Organizational change is the biggest inhibitor to move forward. The SAP-Siemens partnership is a sales/marketing approach to create a simplified view for the future at C-level discussions.
Let us watch carefully what happens in reality.

Next time potentially the dimension of change management and configuration management in an item-centric approach.
Or perhaps Martijn Dullaart will show us the way before, following up on his tricky poll question

 

Two weeks ago, I wrote about the PLM Innovation Forum, a virtual conference organized by TECHNIA, where I described some of my experiences with the event and the different ways of interaction in a virtual conference.

The content remains available till May 31st, so I had time to stroll through the rich content offered. In particular, if you are already familiar with the Dassault Systèmes & TECHNIA offerings, the content is extremely rich.

From the “auditorium“, I selected four presentations that have a logical relation to each other. I believe they will help you understand some of the aspects of PLM independent of the PLM vendor. Let’s start.

Value-Driven Implementation

In this session, Johannes Storvik, you can identify three parts. In the first part, Johannes talks about how to select the best PLM-approach, discussing the various options from custom, standardized, or even fully Out-Of-The-Box, comparing these options with building types. An interesting comparison, however, there is a risk with this approach.

Many companies are now stating they only need a collection of Commercial of the Shelf (COTS) systems and prefer only OOTB. The challenge with this approach is that you start from the tools, constraining the business from the start.

I would state start from your business goals, and ultimately they will lead to requirements for the tools. And then, if available, you find solutions that require no or minor adaptation. Starting from the business is crucial, and Johannes elaborates more on that.

The second part discussing PLM benefits, and if you are looking for confirmation PLM brings value, have a look at the topics, areas, and numbers mentioned. Most benefits and areas are quite traditional, related to a coordinated organization (if you follow my coordinated to connected typology).

The last part, connecting the dots from business to enablers, a Benefits Dependency Network, is a methodology that I recommend. Originally developed by Cranfield School of Management, it allows you to connect your PLM-needs to the company’s business needs and strategies. You can read more about this methodology in this HBR article: A tool to map your next digital initiative.

Benefits Dependency Network: note the potential storyline you can build

My experience from this methodology is that it allows you to extract one, two perhaps three storylines. These storylines then help you to explain why the PLM enablers are needed connecting to a business case into one understandable storyline, suitable for all levels in the company

With Johannes, we went from PLM-characteristics towards connecting PLM to the business and exec management, making PLM implicit visible at the management level. Now the next step.

Industrialization of the Construction Industry

The theme of this session might be misleading. Arto Tolonen, from the LETHO group, has a long history in PLM as a practitioner and at the University of Oulu, where he specialized in Product Data Management and Product Portfolio Management.

The last part of his presentation is dealing with transformational thinking for the construction industry from a one-off construction towards thinking in repeatable processes, using PLM practices. With his dry humor, he asks:
“Why are all buildings prototypes ?” and more.

For many years, I have been preaching PLM practices to be valuable for other industries too. See this 2013 post: PLM for all industries?  The most common challenge was to respond to the question:  “What does your tool do?”   PLM practices only become valuable if you think in repeatable processes.

The exciting part is when Arto talks about the disconnect between the exec level in an organization and reality in the field. Understanding how products are performing, and how each product contributes to the profit of the company, is usually blurred with subjective information. Your company’s love baby might be the worst performer but never dropped from the product portfolio for sentimental reasons.

Arto explains the importance of (digital) portfolio management, connecting the economic data with the technical data. And by doing so, use portfolio management to drive the development of new offerings based on market needs and numbers. Or to decommission products.

I am fully aligned with Arto and believe that a digital transformation should include a connected product portfolio management environment, driving new development projects. Product Portfolio management is not the same as BOM-management.

The portfolio items are facing the outside world, your customers. How the products are built, is defined in the inside world of BOMs and design data.

Now combining product portfolio management with product management makes a lot of more sense if you are going to use it to support the modularization of your products. Based on solution platforms, you can design your products to become modular, leading to a lot of business benefits.

With Arto, we discovered the need to have digital portfolio management connecting business performance and product development. Another implicit reason for PLM to your business explained with humor. Now the next step.

Modularization

Closely related to product portfolio management is the topic of modularization.  If you want to optimize your offering with a great variety of choices for your customers, without spending more time to develop an individual solution, you need to implement modularization for your products.

Daniel Strandhammar van Brick Strategy explains this topic in his session. So many companies I am working with a claim that they want to move from and ETO (Engineering To Order) model to a CTO (Configure To Order) model. Unfortunately, many of them keep on talking about that without making steps towards more configurable products.

Although in many PLM-infrastructures, the capabilities exist to support the modularity of a product portfolio, it requires thinking and analysis outside the tools. The tools are there to support the modularization. Still, it depends on your engineering teams to transform the company’s portfolio step by step into a more modular product.  Brick Strategy is typical such a company that can help you and coach you in a modularization process.

If you look at the benefits Daniel is mentioning related to modularization, these benefits are significant. However, as Daniel also explains per type of business, the effects of modularization might be different, still in every situation worth to invest.

It is interesting to know that many of the modularization methodologies come from Scandinavian countries. Perhaps a region, with companies like Scania (master of modularization), IKEA and others leading the ways towards modularization. Is it a surprise that LEGO is also a Scandinavian company?

Daniel continues by explaining how a roadmap for modularization could look like. If you are struggling with that point, have a look at the video. It is a crucial part of the story.

Note: There is also a presentation from Anders Malmberg fro Scania talking about their Starling project. Not particularly related to modularization, more related to how to organize significant PLM transformations.

With Daniel’s presentation, we see the relation between a product portfolio and modularization. Another implicit reason for PLM to improve your business explained. Now let’s do it.

 

Making Multi-view BOM a reality

My ultimate dream was that James Roche from CIMdata would complete the storyline. We went from business initiatives through product portfolio management and modularization through a flow of organizational topics to enhance your business outcome using PLM.

With James, I was hoping we now would get the final necessary part, the need for a multi-view BOM, and how to establish this. As I mentioned before with modularization, many companies started with a kind of ETO-approach to deliver solutions for their customers. The downside of this approach is that, when designing a product, the manufacturing process was already leading the way the BOM will be structured. Many of the companies that I work with are in this situation. There is no clear EBOM and MBOM, the situation is a kind of hybrid BOM, blocking modularity and multi-plant manufacturing.

James’s presentation unfortunate started with a 10 min technical delay, and then the next part is crucial to understand. He explains nicely what it means to have a “hybrid” single BOM and more to a multi-view EBOM/MBOM. James addressed this topic, both using an example looking at it from a technological and organizational view.

As James is the CIMdata Practice Director for Aerospace & Defense, this was the industry in focus and even example provided above is not necessarily the best solution for every A&D company. Organizational change and managing risks are crucial in such a transition, and that is where James spent even more time. It would be great, and I consider it one of my next blog options, to discuss and share best practices for other types of industries. Is there always a need for a multi-view BOM and are they all the same?

With James we concluded the PLM value story, making it my fourth pick of the PLMIF conference, giving you an end-to-end storyline why PLM is important and how it is connected to your business results.

 

Conclusion

The four presentations that I highlighted here show a storyline that is crucial to understand and pitch when you talk about the business value of PLM. It is not about technical features and functions. It is part of a business strategy, building the right portfolio, manage it in a modular manner, and use multiple BOM views to optimize the delivery of your products.

 

Note: two more weeks to see the full presentations of PLMIF – go and have a look in case you haven’t done so: http://www.plmif.org

 

 

 

Life goes on, and I hope you are all staying safe while thinking about the future. Interesting in the context of the future, there was a recent post from Lionel Grealou with the title: Towards PLM 4.0: Hyperconnected Asset Performance Management Framework.

Lionel gave a kind of evolutionary path for PLM. The path from PLM 1.0 (PDM) ending in a PLM 4.0 definition.  Read the article or click on the image to see an enlarged version to understand the logical order. Interesting to mention that PLM 4.0 is the end target, for sure there is a wishful mind-mapping with Industry 4.0.

When seeing this diagram, it reminded me of Marc Halpern’s diagram that he presented during the PDT 2015 conference. Without much fantasy, you can map your company to one of the given stages and understand what the logical next step would be. To map Lionel’s model with Marc’s model, I would state PLM 4.0 aligns with Marc’s column Collaborating.

In the discussion related to Lionel’s post, I stated two points. First, an observation that most of the companies that I know remain in PLM 1.0 or 2.0, or in Marc’s diagram, they are still trying to reach the level of Integrating.

Why is it so difficult to move to the next stage?

Oleg Shilovitsky, in a reaction to Lionel’s post, confirmed this. In Why did manufacturing stuck in PLM 1.0 and PLM 2.0? Oleg points to several integration challenges, functional and technical. His take is that new technologies might be the answer to move to PLM 3.0, as you can read from his conclusion.

What is my conclusion?

There are many promising technologies, but integration is remaining the biggest problem for manufacturing companies in adopting PLM 3.0. The companies are struggling to expand upstream and downstream. Existing vendors are careful about the changes. At the same time, very few alternatives can be seen around. Cloud structure, new data management, and cloud infrastructure can simplify many integration challenges and unlock PLM 3.0 for future business upstream and especially downstream. Just my thoughts…

Completely disconnected from Lionel’s post,  Angad Sorte from Plural Nordic AS wrote a LinkedIn post: Why PLM does not get attention from your CEO. Click on the image to see an enlarged version, that also neatly aligns with Industry 4.0. Coincidence, or do great minds think alike? Phil Collins would sing: It is in the air tonight

Angad’s post is about the historical framing of PLM as a system, an engineering tool versus a business strategy. Angrad believes once you have a clear definition, it will be easier to explain the next steps for the business. The challenge here is: Do we need, or do we have a clear definition of PLM? It is a topic that I do not want to discuss anymore due to a variety of opinions and interpretations.  An exact definition will never lead to a CEO stating, “Now I know why we need PLM.”

I believe there are enough business proof points WHY companies require a PLM-infrastructure as part of a profitable business. Depending on the organization, it might be just a collection of tools, and people do the work. Perhaps this is the practice in small enterprises?

In larger enterprises, the go-to-market strategy, the information needs, and related processes will drive the justification for PLM. But always in the context of a business transformation. Strategic consultancy firms are excellent in providing strategic roadmaps for their customers, indicating the need for a PLM-infrastructure as part of that.

Most of the time, they do not dive more in-depth as when it comes to implementation, other resources are needed.

What needs to be done in PLM 1.0 to 4.0 per level/stage is well described in all the diagrams on a high-level. The WHAT-domain is the domain of the PLM-vendors and implementers. They know what their tools and skillsets can do, and they will help the customer to implement such an environment.

The big illusion of all the evolutionary diagrams is that it gives a false impression of evolution.  Moving to the next level is not just switching on new or more technology and involve more people.

So the big question is HOW and WHEN to make progress.

HOW to make progress

In the past four years, I have learned that digital transformation in the domain of PLM is NOT an evolution. It is disruptive as the whole foundation for PLM changes. If you zoom in on the picture on the left, you will see the data model on the left, and the data model on the right is entirely different.

On the left side of the chasm, we have a coordinated environment based on data-structures (items, folders, tasks) to link documents.

On the right side of the chasm, we have a connected environment based on federated data elements and models (3D, Logical, and Simulation models).

I have been discussing this topic in the past two years at various PLM conferences and a year ago in my blog: The Challenges of a connected ecosystem for PLM

If you are interested in learning more about this topic, register for the upcoming virtual PLM Innovation Forum organized by TECHNIA. Registration is for free, and you will be able to watch the presentation, either live or recorded for 30 days.

At this moment, the detailed agenda has not been published, and I will update the link once the session is visible.  My presentation will not only focus on the HOW to execute a digital transformation, including PLM can be done, but also explain why NOW is the moment.

NOW to make progress

When the COVID19-related lockdown started, must of us thought that after the lockdown, we will be back in business as soon as possible. Now understanding the impact of the virus on our society, it is clear that we need to re-invent ourselves for a sustainable future, be more resilient.

It is now time to act and think differently as due to the lockdown, most of us have time to think.  Are you and your company looking forward to creating a better future? Or will you and your company try to do the same non-sustainable rat race of the past and being caught by the next crises.

McKinsey has been publishing several articles related to the impact of COVID19 and the article: Beyond coronavirus: The path to the next normal very insightful

As McKinsey never talks about PLM, therefore I want to guide you to think about more sustainable business.

Use a modern PLM-infrastructure, practices, and tools to remain competitive, meanwhile creating new or additional business models. Realizing concepts as digital twins, AR/VR-based business models require an internal transition in your company, the jump from coordinated to connected. Therefore, start investigating, experimenting in these new ways of working, and learn fast. This is why we created the PLM Green Alliance as a platform to share and discuss.

If you believe there is no need to be fast, I recommend you watch Rebecka Carlsson’s presentation at the PLMIF event. The title of her presentation: Exponential Tech in Sustainability. Rebecca will share insights for business development about how companies can upgrade to new business models based on the new opportunities that come with sustainability and exponential tech.

The reason I recommend her presentation because she addresses the aspect of exponential thinking nicely. Rebecka states we are “programmed” to think local-linear as mankind. Exponential thinking goes beyond our experience. Something we are not used doing until with the COVID19-virus we discovered exponential growth of the number of infections.

Finally, and this I read this morning, Jan Bosch wrote an interesting post: Why Agile Matters, talking about the fact that during the design and delivery of the product to the market, the environment and therefore the requirements might change. Read his post, unless as Jan states:

Concluding, if you’re able to perfectly predict the optimal set of requirements for a system or product years ahead of the start of production or deployment and if you’re able to accurately predict the effect of each requirement on the user, the customer and the quality attributes of the system, then you don’t need Agile.

What I like about Jan’s post is the fact that we should anticipate changing requirements. This statement combined with Rebecka’s call for being ready for exponential change, with an emerging need for sustainability, might help you discuss in your company how a modern New Product Introduction process might look like, including requirements for a sustainable future that might come in later (per current situation) or can become a practice for the future

Conclusion

Now is the disruptive moment to break with the old ways of working.  Develop plans for the new Beyond-COVID19-society.  Force yourselves to work in more sustainable modes (digital/virtual), develop sustainable products or services (a circular economy), and keep on learning. Perhaps we will meet virtually during the upcoming PLM Innovation Forum?

Note: You have reached the end of this post, which means you took the time to read it all. Now if you LIKE or DISLIKE the content, share it in a comment. Digital communication is the future. Just chasing for Likes is a skin-deep society. We need arguments.
Looking forward to your feedback.

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