
A month ago I announced to write a series of posts related to the various facets of Model-Based. As I do not want to write a book for a limited audience, I still believe blog posts are an excellent way to share knowledge and experience to a wider audience. Remember PLM is about sharing!
There are three downsides to this approach:
- you have to chunk the information into pieces; my aim is not to exceed 1000 words per post
- Isolated posts can be taken out of context (in a positive or negative way)
- you do not become rich and famous for selling your book
Model-Based ways of working are a hot topic and crucial for a modern digital enterprise. The modern digital enterprise does not exist yet to my knowledge, but the vision is there. Strategic consultancy firms are all active exploring and explaining the potential benefits – I have mentioned McKinsey / Accenture / Capgemini before.
In the domain of PLM, there is a bigger challenge as here we are suffering from the fact that the word “Model” immediately gets associated with a 3D Model. In addition to the 3D CAD Model, there is still a lot of useful legacy data that does not match with the concepts of a digital enterprise. I wrote and spoke about this topic a year ago. Among others at PI 2017 Berlin and you can check this presentation on SlideShare: How digital transformation affects PLM
Back to the various aspects of Model-Based
My first post: Model-Based – an introduction described my intentions what I wanted to explain. I got some interesting feedback and insights from my readers . Some of the people who responded understood that the crucial characteristic of the model-based enterprise is to use models to master a complex environment. Business Models, Mathematical Models, System Models are all part of a model-based enterprise, and none of them have a necessary relation to the 3D CAD model.
Why Model-Based?
Because this is an approach to master complex environments ! If you are studying the concepts for a digital enterprise model, it is complex. Artificial intelligence, predictive actions all need a model to deliver. The interaction and response related to my first blog post did not show any problems – only a positive mindset to further explore. For example, if you read this blog post from Contact, you will see the message came across very well: Model-Based in Model-Based Systems Engineering – what’s up ?
Where the confusion started
My second post: Why Model-Based? The 3D CAD Model was related to model-based, focusing on the various aspects related to the 3D CAD model, without going into all the details. In particular, in the PLM world, there is a lot of discussion around Model-Based Design or Model-Based Definition, where new concepts are discussed to connect engineering and manufacturing in an efficient and modern data-driven way. Lifecycle Insights, Action Engineering, Engineering.com, PTC, Tech-Clarity and many more companies are publishing information related to the model-based engineering phase.
Here is was surprised by Oleg’s blog with his post Model-Based Confusion in 3D CAD and PLM.
If you read his post, you get the impression that the model-based approach is just a marketing issue instead of a significant change towards a digital enterprise. I quote:
Here is the thing… I don’t see much difference between saying PLM-CAD integration sharing data and information for downstream processes and “model-driven” data sharing. It might be a terminology thing, but data is managed by CAD-PLM tools today and accessed by people and other services. This is how things are working today. If model-driven is an approach to replace 2D drawings, I can see it. However, 2D replacement is something that I’ve heard 20 years ago. However, 2D drawings are still massively used by manufacturing companies despite some promises made by CAD vendors long time ago.
I was surprised by the simplicity of this quote. As if CAD vendors are responsible for new ways of working. In particular, automotive and aerospace companies are pushing for a model-based connection between engineering and manufacturing to increase quality, time to market and reduced handling costs. The model-based definition is not just a marketing issue as you can read from benefits reported by Jennifer Herron (Re-use your CAD – the model-based CAD handbook – describing practices and benefits already in 2013) or Tech-Clarity (The How-To Guide for adopting model-based definition – describing practices and benefits – sponsored by SolidWorks)
Oleg’s post unleashed several reactions of people who shared his opinion (read the comments here). They are all confused, t is all about marketing / let’s not change / too complex. Responses you usually hear from a generation that does not feel and understand the new approaches of a digital enterprise. If you are in the field working with multiple customers trying to understand the benefits of model-based definition, you would not worry about terminology – you would try to understand it and make it work.
Model-Based – just marketing?
In his post, Oleg refers to CIMdata’ s explanation of the various aspects of model-based in the context of PLM. Instead of referring to the meaning of the various acronyms, Peter Bilello (CIMdata) presented at the latest PDT conference (Oct 2017 – Gothenburg) an excellent story related to the various aspects of the model-based aspects, actually the whole conference was dedicated to the various aspects of a Model-Based Enterprise illustrates that it is not a vendor marketing issue. You can read my comments from the vendor-neutral conference here: The weekend after PDT Europe 2017 Part 1 and Part 2.
There were some dialogues on LinkedIn this weekend, and I promised to publish this post first before continuing on the other aspects of a model-based enterprise. Just today Oleg published a secondary post related to this topic: Model-Based marketing in CAD and PLM, where again the tone and blame is to the PLM/CAD vendors, as you can see from his conclusion:
I can see “mode-based” as a new and very interesting wave of marketing in 3D CAD and PLM. However, it is not pure marketing and it has some rational. The rational part of model-based approach is to have information model combined from 3D design and all connected data element. Such model can be used as a foundation for design, engineering, manufacturing, support, maintenance. Pretty much everything we do. It is hard to create such model and it is hard to combine a functional solution from existing packages and products. You should think how to combine multiple CAD systems, PLM platforms and many other things together. It requires standards. It requires from people to change. And it requires changing of status quo. New approaches in data management can change siloed world of 3D CAD and PLM. It is hard, but nothing to do with slides that will bring shiny words “model-base”. Without changing of technology and people, it will remain as a history of marketing
Again it shows the narrow mindset on the future of a model-based enterprise. When it comes to standards I recommend you to register and watch CIMdata’s educational webinar called: Model-Based Enterprise and Standards – you need to register. John MacKrell CIMdata’s chairman gives an excellent overview and status of model-based enterprise initiative. After having studied and digested all the links in this post, I challenge you to make your mind up. The picture below comes from John’s presentation, an illustration where we are with model-based definition currently

Conclusion
The challenge of modern businesses is that too often we conclude too fast on complex issues or we frame new developments because they do not fit our purpose. You know it from politics. Be aware it is also valid in the world of PLM. Innovation and a path to a modern digital enterprise do not come easy – you need to invest and learn all the aspects. To be continued (and I do not have all the answers either)


At the time 3D CAD was introduced for the mid-market, the main reason why 3D CAD was introduced was to provide a better understanding of the designed product. Visualization and creating cross-sections of the design became easy although the “old” generation of 2D draftsmen had to a challenge to transform their way of working. This lead often to 3D CAD models setup with the mindset to generate 2D Manufacturing drawings, not taking real benefits from the 3D CAD Model. Let’s first focus on Model-Based Definition.
According to an eBook, sponsored by SolidWorks and published by Tech-Clarity: “
A parametric model, combined with business rules can be accessed and controlled by other applications in a digital enterprise. In this way, without the intervention of individuals a set of product variants can be managed and not only from the design point of view. Geometry and manufacturing parameters are also connected and accessible. This is one of the concepts where Industry 4.0 is focusing on: intelligent and flexible manufacturing by exchanging parameters


This is however in big contrast with reality in the field. In February this year I moderated a focus group related to PLM and the Model-Based approach and the main conclusion from the audience was that everyone was looking at it, and only a few started practicing. Therefore, I promised to provide some step-by-step education related to model-based as like PLM we need to get a grip on what it means and how it impacts your company. As I am not an academic person, it will be a little bit like model-based for dummies, however as model-based in all aspects is not yet a wide-spread common practice, we are all learning.
Just designing a product in 3D and then generating 2D drawings for manufacturing is not really game-changing and bringing big benefits. 3D Models provide a better understanding of the product, mechanical simulations allow the engineer to discover clashes and/or conflicts and this approach will contribute to a better understanding of the form & fit of a product. Old generations of designers know how to read a 2D drawing and in their mind understand the 3D Model.
A model-based enterprise has to rely on data, so the 3D Model should rely on parameters that allow other applications to read them. These parameters can contribute to simulation analysis and product optimization or they can contribute to manufacturing. In both cases the parameters provide data continuity between the various disciplines, eliminating the need to create new representations in different formats. I will come back in a future post to the requirements for the 3D CAD model in the context of the model-based enterprise, where I will zoom in on Model-Based Definition and the concepts of Industry 4.0.
The mathematical model of a product allows companies to analyze and optimize the behavior of a product. When companies design a product they often start from a conceptual model and by running simulations they can optimize the product and define low-level requirements within a range that optimizes the product performance. The relation between design and simulation in a virtual model is crucial to be as efficient as possible. In the current ways of working, often design and simulation are not integrated and therefore the amount of simulations is relative low, as time-to-market is the key driver to introduce a new product.
There is still a debate if the Digital Twin is part of PLM or should be connected to PLM. A digital twin can be based on a set of parameters that represent the product performance in the field. There is no need to have a 3D representation, despite the fact that many marketing videos always show a virtual image to visualize the twin.
For me “Keep process and organizational silos ….. “ is exactly the current state of classical PLM, where PLM concepts are implemented to provide data continuity within a siloed organization. When you can stay close to the existing processes the implementation becomes easier. Less business change needed and mainly a focus on efficiency gains by creating access to information.
And if you know SAP, they go even further. Their mantra is that when using SAP PLM, you even do not need to integrate with ERP. You can still have long discussions with companies when it comes to PLM and ERP integrations. The main complexity is not the technical interface but the agreement who is responsible for which data sets during the product lifecycle. This should be clarified even before you start talking about a technical implementation. SAP claims that this effort is not needed in their environment, however they just shift the problem more towards the CAD-side. Engineers do not feel comfortable with SAP PLM when engineering is driving the success of the company. It is like the Swiss knife; every tool is there but do you want to use it for your daily work?
What is really needed for the 21st century is to break down the organizational silos as current ways of working are becoming less and less applicable to a modern enterprise. The usage of software has the major impact on how we can work in the future. Software does not follow the linear product process. Software comes with incremental deliveries all the time and yes the software requires still hardware to perform. Modern enterprises try to become agile, being able to react quickly to trends and innovation options to bring higher and different value to their customers. Related to product innovation this means that the linear, sequential go-to-market process is too slow, requires too much data manipulation by non-value added activities.
All leading companies in the industry are learning to work in a more agile mode with multidisciplinary teams that work like startups. Find an incremental benefit, rapidly develop test and interact with the market and deliver it. These teams require real-time data coming from all stakeholders, therefore the need for data continuity. But also the need for data quality as there is no time to validate data all the time – too expensive – too slow.
When talking with companies in the real world, they are not driven by technology – they are driven by processes. They do not like to break down the silos as it creates discomfort and the need for business transformation. And there is no clear answer at this moment. What is clear that leading companies invest in business change first before looking into the technology.

I consider Model-Based practices as one of the essential needs for future PLM as this approach reduces the amount of derived information related to a product/ system. And it provides a digital continuity. In the last PDT conference in Gothenburg, this topic was shared on a quite extensive matter. Have a read to freshen up your memory here: The weekend after PDT Europe – 


Susanne Lauda, Director, Global Advanced Manufacturing Technology, AGCO Corporation, provided an overview related to AGCO’s new PLM journey and how they were benefiting from a digital thread towards manufacturing. It felt like a smooth vendor demo as everything looked nice and reasonable. It was all about the WHAT. However, two points that brought the extra:
Perhaps an ambiguous title this time as it can be interpreted in various ways. I think that all these interpretations are one of the most significant problems with PLM. Ambiguity everywhere. Its definition, its value and as you might have noticed from the past two blog posts the required skill-set for PLM consultants.
In the past twenty years, companies have implemented PLM systems, where the primary focus was on the P (Product) only from Product Lifecycle Management. PLM systems have been implemented as an engineering tool, as an evolution of (Product Data Management).




We agreed on the fact that traditional consultancy practices related to PLM ranking and selection processes are out of time. The Forester Wave publication was the cause of our discussion. For two reasons:
Also, make a 5-10 years cost evaluation of your solution and take the risk of raising subscription fees into account. No vendor will drop the price unless forced by the outside world. The initial benefits will be paid back later because of the other business model.

I believe we still need consultants to help companies to tell and coach them towards new ways of working related to the current digitization. Twenty years old concepts won’t work anymore. Consultants need a digital mindset and think holistic. Fitting technology and tools will be there in the future.
In my earlier post;
I agree with Oleg and Joe. PLM ranking does not make sense for companies to select a PLM solution. They are more an internal PLM show, useful for the organizing consultancy companies to conduct, but at the end, it is a discussion about who has the biggest and most effective button. Companies need to sell themselves and differentiate.
ses, a strategy is future-oriented and not about consolidating the current status quo. Therefore I believe a PLM implementation is always done in the context of a business transformation, which is most of the time not only related to PLM – it is about People, Processes and then the tools.


Happy New Year to all of you. A new year comes traditionally with good intentions for the upcoming year. I would like to share my PLM intentions for this year with you and look forward to your opinion. I shared some of my 2017 thoughts in my earlier post: 
To my understanding we are still in the early phases of discovering the ideal architecture and practices for a digital enterprise. PLM Vendors and technology companies show us the impressive potential as-if the future already exists already now. Have a reality check from Marc Halpern (Gartner) in this article on engineering.com –
Although my curiosity is focused on future PLM, there is still a journey to go for companies that have just started with PLM. Before even thinking of a digital enterprise, there is first a need to understand and implement PLM as an infrastructure outside the engineering department.
How to convince management that these changes are needed and do not happen without their firm support? It is easier to do nothing and push for small incremental changes. But will this be fast enough? Probably not as you can read from research done by strategic consultancy firms. There is a lot of valuable information available if you invest time in research. But spending time is a challenge for management.

Digital transformation is one of the buzz words pointing to the transition process. Companies need to go through a change to become flexible for the future and deliver products or solutions for the individual customer. Currently companies invest in digital transformation, most of the time in areas that bring direct visibility to the outside world or their own management, not necessarily delivering profitable results as a recent article from McKinsey illustrated:
Software vendors in various domains are all contributing to support a modern digital product innovation management future. But where to start? Is it the product innovation platform? Is it about federated solutions? Model-Based? Graph-databases? There are even people who want to define the future of PLM. We can keep throwing pieces of the puzzle on the table, but all these pieces will not lead to a single solved puzzle. There will be different approaches based on your industry and your customers. Therefore, continuous learning and investing time to understand the digital future is crucial. This year’s PDT Europe conference was an excellent event to learn and discuss the themes around a model-based lifecycle enterprise. You can read my reviews here: The weekend after PDT Europe 2017
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