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In this post, I want to explain why Model-Based Systems Engineering (MBSE) and Sustainability are closely connected. I would claim sustainability in our PLM domain will depend on MBSE.
Can we achieve Sustainability without MBSE? Yes, but it will be costly and slow. And as all businesses want to be efficient and agile, they should consider MBSE.
What is MBSE?
The abbreviation MBSE stands for Model-Based Systems Engineering, a specialized manner to perform Systems Engineering. Look at the Wikipedia definition in short:
MBSE is a technical approach to systems engineering that focuses on creating and exploiting domain models as the primary means of information exchange rather than on document-based information exchange.
Model-Based fits in the digital transformation scope of PLM – from a document-based approach to a data-driven, model-based one. In 2018, I focused on facets of the model-based enterprise and related to MBSE in this post: Model-Based: System Engineering (MBSE).
My conclusion in that post was:
Model-Based Systems Engineering might have been considered as a discipline for the automotive and aerospace industry only. As products become more and more complex, thanks to IoT-based applications and software, companies should consider evaluating the value of model-based systems engineering for their products/systems.
I drew this conclusion before I focused on sustainability and systems thinking. Implementing sustainability concepts, like the Circular Economy, require more complex engineering efforts, justifying a Model-Based Systems Engineering approach. Let’s have a look.
If you want to learn more about why we need MBSE, look at this excellent keynote speech lecture from Zhang Xin Guo at the Incose 2018 conference below:
The Mission / the stakeholders
A company might deliver products to the market with the best price/quality ratio and regulatory compliance, perceived and checked by the market. This approach is purely focusing on economic parameters.
There is no need for a system engineering approach as the complexity is manageable. The mission is more linear, a “job to do,” and a limited number of stakeholders are involved in this process.
… with sustainability
Once we start to include sustainability in our product’s mission, we need a systems engineering approach, as several factors will push for different considerations. The most obvious considerations are the choice of materials and the optimizing the production process (reducing carbon emissions).
However, the repairability/serviceability of the product should be considered with a more extended lifetime vision.
What about upgradeability and reusing components? Will the customer pay for these extra sustainable benefits?
Probably Yes, when your customer has a long-term vision, as the overall lifecycle costs of the product will be lower.
Probably No if none of your competitors delivers non-sustainable products much cheaper.
As long as regulations will not hurt traditional business models, there might be no significant change.
However, the change has already started. Higher energy prices will impact the production of specific resources and raise costs. In addition, energy-intensive manufacturing processes will lead to more expensive materials. Combined with raising carbon taxes, this will be a significant driver for companies to reconsider their product offering and manufacturing processes.
The more expensive it becomes to create new products, the more attractive repairable and upgradable products will become. And this brings us to the concept of the circular economy, which is one of the pillars of sustainability.
In short, looking at the diagram – the vertical flow from renewables and finite materials from part to product to product in service leads ultimately to wasted resources if there are no feedback loops. This is the traditional product delivery process that most companies are using.
You can click on the image to the left to zoom in on the details.
The renewable loop on the left side of the diagram is the usage of renewables during production and the use of the product. The more we use renewables instead of fossil fuels, the more sustainable this loop will be. This is the area where engineers should use simulations to find the optimal manufacturing processes and product behavior. Again click on the image to zoom in on the details.
The right side of the loop, related to the materials, is where we see the options for repairable, serviceable, upgradeable, and even further refurbishment and recycling to avoid leakage of precious materials. This is where mechanical engineers should dominate the activities. Focussing on each of the loops and how to enable them in the product. Click on the image to see the relevant loops.
Looking at the circular economy diagram, it is clear that we are no longer talking about a linear process – it has become the implementation of a system. Systems Engineering or MBSE?
The benefits of MBSE
Developing products with the circular economy in mind is no longer a “job to do,” a simple linear exercise. Instead, if we walk down the systems engineering V-shape, there are a lot of modeling exercises to perform before we reach the final solution.
To illustrate the benefits of MBSE, let’s walk through the following scenario.
A well-known company sells lighting projects for stadiums and public infrastructure. Their current business model is based on reliable lighting equipment with a competitive price and range of products.
Most of the time, their contracts have clauses about performance/cost and maintenance. The company sells the products when they win the deal and deliver spare parts when needed.
Their current product design is quite linear – without systems engineering.
Now this company has decided to change its business model towards Product As A Service, or in their terminology LaaS (Lightening as a Service). For a certain amount per month, they will provide lighting to their customers, a stadium, a city, and a road infrastructure.
To implement this business model, this is how they used a Model-Based Systems Engineering approach.
Modeling the Mission
Example of a business model
Before even delivering any products, the process starts with describing and analyzing the business model needed for Lightening as a Service.
Then, with modeling estimates about the material costs, there are exercises about the resources required to maintain the service, the potential market, and the possible price range.
It is the first step of using a model to define the mission of the service. After that, the model can be updated, adjusted, and used for a better go-to-market approach when the solution becomes more mature.
Part of the business modeling is also the intention to deliver serviceable and upgradeable products. As the company now owns the entire lifecycle, this is the cheapest way to guarantee a continuous or improved service over time.
Modeling the Functions
Example of a function diagram
Providing Lighting as a Service also means you must be in touch with your installations in real time. Power consumption needs to be measured and analyzed in real-time for (predictive) maintenance, and the light-providing service should be as cheap as possible during operation.
Therefore LED technology is the most reliable, and connectivity functions need to be implemented in the solution. The functional design ensures installation, maintenance and service can be done in a connected manner (cheapest in operation – beneficial for the business).
Modeling the Logical components
As an owner of the solution, the design of the logical components of the lighting solution is also crucial. How to address various lighting demands efficiently? Modularity is one of the first topics to address. With modular components, it is possible to build customer-specific solutions with a reduced engineering effort. However, the work needs to be done by generically designing the solutions and focusing on the interfaces.
Example of a logical diagram
Such a design starts with a logical process and flow diagrams combined with behavior modeling. Without already having a physical definition, we can analyze the components’ behavior within an electrical scheme. Decisions on whether specific scenarios will be covered by hardware or software can be analyzed here. The company can define the lower-level requirements for the physical component by using virtual trade-offs on the logical models.
At this stage, we have used business modeling, functional modeling and logical modeling to understand our solution’s behavior.
Modeling the Physical product
The final stage of the solution design is to implement the logical components into a physical solution. The placement of components and interfaces between the components becomes essential. For the physical design, there are still a lot of sustainability requirements to verify:
- Repairability and serviceability – are the components reachable and replaceable? Reducing the lifecycle costs of the solution
- Upgradeability – are there components that can behave differently due to software choices, or are there components that can be replaced with improved functionality. Reducing the cost of creating entirely new solutions.
- Reuse & recyclable – are the materials used in the solution recyclable or reusable, reducing the cost of new materials or reducing the cost of dumping waste.
- RoHS/ REACH compliance
The image below from Zhang Xin Guo’s presentation nicely demonstrates the iterative steps before reaching a physical product
Before committing to a hardware implementation, the virtual product can be analyzed, behavior can be simulated, and it carbon impact can be calculated for the various potential variants.
The manufacturing process and energy usage during operation are also a part of the carbon impact calculation. The best performing virtual solution, including its simulations models, can be chosen for the realization to ensure the most environmentally friendly solution.
The digital twin for follow-up
Once the solution has been realized, the company still has a virtual model of the solution. By connecting the physical product’s observed and measured behavior, the virtual side’s modeling can be improved or used to identify improvement candidates – maintenance or upgrades. At this stage, the virtual twin is the actual twin of the physical solution. Without going deeper into the digital twin at this stage, I hope you also realize MBSE is a starting point for implementing digital twins serving sustainability outcomes.
The image below, published by Boeing, illustrates the power of the connected virtual and physical world and the various types of modeling that help to assess the optimal solution.
Conclusion
For sustainability, it all starts with the design. The design decisions for the product contribute for 80 % to the carbon footprint of the solution. Afterward, optimization is possible within smaller margins. MBSE is the recommended approach to get a trustworthy understanding and follow-up of the product’s environmental impact.
What do you think can we create sustainable products without MBSE?
This year started for me with a discussion related to federated PLM. A topic that I highlighted as one of the imminent trends of 2022. A topic relevant for PLM consultants and implementers. If you are working in a company struggling with PLM, this topic might be hard to introduce in your company.
Before going into the discussion’s topics and arguments, let’s first describe the historical context.
The traditional PLM frame.
Historically PLM has been framed first as a system for engineering to manage their product data. So you could call it PDM first. After that, PLM systems were introduced and used to provide access to product data, upstream and downstream. The most common usage was the relation with manufacturing, leading to EBOM and MBOM discussions.
The traditional ENOVIA PLM backbone
IT landscape simplification often led to an infrastructure of siloed solutions – PLM, ERP, CRM and later, MES. IT was driving the standardization of systems and defining interfaces between systems. System capabilities were leading, not the flow of information.
As many companies are still in this stage, I would call it PLM 1.0
PLM 1.0 systems serve mainly as a System of Record for the organization, where disciplines consolidate their data in a given context, the Bills of Information. The Bill of Information then is again the place to connect specification documents, i.e., CAD models, drawings and other documents, providing a Digital Thread.
Aras – Bills of Information creating the Digital Thread
The actual engineering work is done with specialized tools, MCAD/ECAD, CAE, Simulation, Planning tools and more. Therefore, each person could work in their discipline-specific environment and synchronize their data to the PLM system in a coordinated manner.
However, this interaction is not easy for some of the end-users. For example, the usability of CAD integrations with the PLM system is constantly debated.
Many of my implementation discussions with customers were in this context. For example, suppose your products are relatively simple, or your company is relatively small. In that case, the opinion is that the System or Record approach is overkill.
That’s why many small and medium enterprises do not see the value of a PLM backbone.
This could be true till recently. However, the threats to this approach are digitization and regulations.
Customers, partners, and regulators all expect more accurate and fast responses on specific issues, preferably instantly. In addition, sustainability regulations might push your company to implement a System of Record.
PLM as a business strategy
For the past fifteen years, we have discussed PLM more as a business strategy implemented with business systems and an infrastructure designed for sharing. Therefore, I choose these words carefully to avoid overhanging the expression: PLM as a business strategy.
The reason for this prudence is that, in reality, I have seen many PLM implementations fail due to the ambiguity of PLM as a system or strategy. Many enterprises have previously selected a preferred PLM Vendor solution as a starting point for their “PLM strategy”.
One of the most neglected best practices.
In reality, this means there was no strategy but a hope that with this impressive set of product demos, the company would find a way to support its business needs. Instead of people, process and then tools to implement the strategy, most of the time, it was starting with the tools trying to implement the processes and transform the people. That is not really the definition of business transformation.
In my opinion, this is happening because, at the management level, decisions are made based on financials.
Developing a PLM-related business strategy requires management understanding and involvement at all levels of the organization.
This is often not the case; the middle management has to solve the connection between the strategy and the execution. By design, however, the middle management will not restructure the organization. By design, they will collect the inputs van the end users.
And it is clear what end users want – no disruption in their comfortable way of working.
Halfway conclusion:
Rebranding PLM as a business strategy has not really changed the way companies work. PLM systems remain a System of Record mainly for governance and traceability.
To understand the situation in your company, look at who is responsible for PLM.
- If IT is responsible, then most likely, PLM is not considered a business strategy but more an infrastructure.
- If engineering is responsible for PLM, then you are still in the early days of PLM, the engineering tools to be consulted by others upstream or downstream.
Only when PLM accountability is at the upper management level, it might be a business strategy (assume the upper management understands the details)
Connected is the game changer
Connecting all stakeholders in an engagement has been a game changer in the world. With the introduction of platforms and the smartphone as a connected device, consumers could suddenly benefit from direct responses to desired service requests (Spotify, iTunes, Uber, Amazon, Airbnb, Booking, Netflix, …).
The business change: connecting real-time all stakeholders to deliver highly rapid results.
What would be the game changer in PLM was the question? The image below describes the 2014 Accenture description of digital PLM and its potential benefits.
Is connected PLM a utopia?
Marc Halpern from Gartner shared in 2015 the slide below that you might have seen many times before. Digital Transformation is really moving from a coordinated to a connected technology, it seems.
The image below gives an impression of an evolution.
I have been following this concept till I was triggered by a 2017 McKinsey publication: “our insights/toward an integrated technology operating model“.
This was the first notion for me that the future should be hybrid, a combination of traditional PLM (system of record) complemented with teams that work digitally connected; McKinsey called them pods that become product-centric (multidisciplinary team focusing on a product) instead of discipline-centric (marketing/engineering/manufacturing/service)
In 2019 I wrote the post: The PLM migration dilemma supporting the “shocking” conclusion “Don’t think about migration when moving to data-driven, connected ways of working. You need both environments.”
One of the main arguments behind this conclusion was that legacy product data and processes were not designed to ensure data accuracy and quality on such a level that it could become connected data. As a result, converting documents into reliable datasets would be a costly, impossible exercise with no real ROI.
The second argument was that the outside world, customers, regulatory bodies and other non-connected stakeholders still need documents as standardized deliverables.
The conclusion led to the image below.
Systems of Record (left) and Systems of Engagement (right)
Splitting PLM?
In 2021 these thoughts became more mature through various publications and players in the PLM domain.
We saw the upcoming of Systems of Engagement – I discussed OpenBOM, Colab and potentially Configit in the post: A new PLM paradigm. These systems can be characterized as connected solutions across the enterprise and value chain, focusing on a platform experience for the stakeholders.
These are all environments addressing the needs of a specific group of users as efficiently and as friendly as possible.
A System of Engagement will not fit naturally in a traditional PLM backbone; the System of Record.
Erik Herzog with SAAB Aerospace and Yousef Houshmand at that time with Daimler published that year papers related to “Federated PLM” or “The end of monolithic PLM.”. They acknowledged a company needs to focus on more than a single PLM solution. The presentation from Erik Herzog at the PLM Roadmap/PDT conference was interesting because Erik talked about the Systems of Engagement and the Systems of Record. He proposed using OSLC as the standard to connect these two types of PLM.
It was a clear example of an attempt to combine the two kinds of PLM.
And here comes my question: Do we need to split PLM?
When I look at PLM implementations in the field, almost all are implemented as a System of Record, an information backbone proved by a single vendor PLM. The various disciplines deliver their content through interfaces to the backbone (Coordinated approach).
However, there is low usability or support for multidisciplinary collaboration; the PLM backbone is not designed for that.
Due to concepts of Model-Based Systems Engineering (MBSE) and Model-Based Definition (MBD), there are now solutions on the market that allow different disciplines to work jointly related to connected datasets that can be manipulated using modeling software (1D, 2D, 3D, 4D,…).
These environments, often a mix of software and hardware tools, are the Systems of Engagement and provide speedy results with high quality in the virtual world. Digital Twins are running on Systems of Engagements, not on Systems of Records.
Systems of Engagement do not need to come from the same vendor, as they serve different purposes. But how to explain this to your management, who wants simplicity. I can imagine the IT organization has a better understanding of this concept as, at the end of 2015, Gartner introduced the concept of the bimodal approach.
Their definition:
Mode 1 is optimized for areas that are more well-understood. It focuses on exploiting what is known. This includes renovating the legacy environment so it is fit for a digital world. Mode 2 is exploratory, potentially experimenting to solve new problems. Mode 2 is optimized for areas of uncertainty. Mode 2 often works on initiatives that begin with a hypothesis that is tested and adapted during a process involving short iterations.
No Conclusion – but a question this time:
At the management level, unfortunately, there is most of the time still the “Single PLM”-mindset due to a lack of understanding of the business. Clearly splitting your PLM seems the way forward. IT could be ready for this, but will the business realize this opportunity?
What are your thoughts?
In my previous post, “My PLM Bookshelf,” on LinkedIn, I shared some of the books that influenced my thinking related to PLM. As you can see in the LinkedIn comments, other people added their recommendations for PLM-related books to get inspired or more knowledgeable.
Where reading a book is a personal activity, now I want to share with you how to get educated in a more interactive manner related to PLM. In this post, I talk with Peter Bilello, President & CEO of CIMdata. If you haven’t heard about CIMdata and you are active in PLM, more to learn on their website HERE. Now let us focus on Education.
CIMdata
Peter, knowing CIMdata from its research valid for the whole PLM community, I am curious to learn what is the typical kind of training CIMdata is providing to their customers.
Jos, throughout much of CIMdata’s existence, we have delivered educational content to the global PLM industry. With a core business tenant of knowledge transfer, we began offering a rich set of PLM-related tutorials at our North American and pan-European conferences starting in the earlier 1990s.
Since then, we have expanded our offering to include a comprehensive set of assessment-based certificate programs in a broader PLM sense. For example, systems engineering and digital transformation-related topics. In total, we offer more than 30 half-day classes. All of which can be delivered in-person as a custom configuration for a specific client and through public virtual-live or in-person classes. We have certificated more than 1,000 PLM professionals since the introduction in 2009 of this PLM Leadership offering.
Based on our experience, we recommend that an organization’s professional education strategy and plans address the organization’s specific processes and enabling technologies. This will help ensure that it drives the appropriate and consistent operations of its processes and technologies.
For that purpose, we expanded our consulting offering to include a comprehensive and strategic digital skills transformation framework. This framework provides an organization with a roadmap that can define the skills an organization’s employees need to possess to ensure a successful digital transformation.
In turn, this framework can be used as an efficient tool for the organization’s HR department to define its training and job progression programs that align with its overall transformation.
The success of training
We are both promoting the importance of education to our customers. Can you share with us an example where Education really made a difference? Can we talk about ROI in the context of training?
Jos, I fully agree. Over the years, we have learned that education and training are often minimized (i.e., sub-optimized). This is unfortunate and has usually led to failed or partially successful implementations.
In our view, both education and training are needed, along with strong organizational change management (OCM) and a quality assurance program during and after the implementation.
In our terms, education deals with the “WHY” and training with the “HOW”. Why do we need to change? Why do we need to do things differently? And then “HOW” to use new tools within the new processes.
We have seen far too many failed implementations where sub-optimized decisions were made due to a lack of understanding (i.e., a clear lack of education). We have also witnessed training and education being done too early or too late.
This leads to a reduced Return on Investment (ROI).
Therefore a well-defined skills transformation framework is critical for any company that wants to grow and thrive in the digital world. Finally, a skills transformation framework needs to be tied directly to an organization’s digital implementation roadmap and structure, state of the process, and technology maturity to maximize success.
Training for every size of the company?
When CIMdata conducts PLM training, is there a difference, for example, when working with a big global enterprise or a small and medium enterprise?
You might think the complexity might be similar; however, the amount of internal knowledge might differ. So how are you dealing with that?
We basically find that the amount of training/education required mostly depends on the implementation scope. Meaning the scope of the proposed digital transformation and the current maturity level of the impacted user community.
It is important to measure the current maturity and establish appropriate metrics to measure the success of the training (e.g., are people, once trained, using the tools correctly).
CIMdata has created a three-part PLM maturity model that allows an organization to understand its current PLM-related organizational, process, and technology maturity.
The three-part PLM maturity model
The PLM maturity model provides an important baseline for identifying and/or developing the appropriate courses for execution.
This also allows us, when we are supporting the definition of a digital skills transformation framework, to understand how the level of internal knowledge might differ within and between departments, sites, and disciplines. All of which help define an organization-specific action plan, no matter its size.
Where is CIMdata training different?
Most of the time, PLM implementers offer training too for their prospects or customers. So, where is CIMdata training different?
For this, it is important to differentiate between education and training. So, CIMdata provides education (the why) and training and education strategy development and planning.
We don’t provide training on how to use a specific software tool. We believe that is best left to the systems integrator or software provider.
While some implementation partners can develop training plans and educational strategies, they often fall short in helping an organization to effectively transform its user community. Here we believe training specialists are better suited.
Digital Transformation and PLM
One of my favorite topics is the impact of digitization in the area of product development. CIMdata introduced the Product Innovation Platform concept to differentiate from traditional PDM/PLM. Who needs to get educated to understand such a transformation, and what does CIMdata contribute to this understanding.
We often start with describing the difference between digitalization and digitization. This is crucial to be understood by an organization’s management team. In addition, management must understand that digitalization is an enterprise initiative.
It isn’t just about product development, sales, or enabling a new service experience. It is about maximizing a company’s ROI in applying and leveraging digital as needed throughout the organization. The only way an organization can do this successfully is by taking an end-to-end approach.
The Product Innovation Platform is focused on end-to-end product lifecycle management. Therefore, it must work within the context of other enterprise processes that are focused on the business’s resources (i.e., people, facilities, and finances) and on its transactions (e.g., purchasing, paying, and hiring).
As a result, an organization must understand the interdependencies among these domains. If they don’t, they will ultimately sub-optimize their investment. It is these and other important topics that CIMdata describes and communicates in its education offering.
The Product Innovation Platform in a digital enterprise
More than Education?
As a former teacher, I know that a one-time education, a good book or slide deck, is not enough to get educated. How does CIMdata provide a learning path or coaching path to their customers?
Jos, I fully agree. Sustainability of a change and/or improved way of working (i.e., long-term sustainability) is key to true and maximized ROI. Here I am referring to the sustainability of the transformation, which can take years.
With this, organizational change management (OCM) is required. OCM must be an integral part of a digital transformation program and be embedded into a program’s strategy, execution, and long-term usage. That means training, education, communication, and reward systems all have to be managed and executed on an ongoing basis.
For example, OCM must be executed alongside an organization’s digital skills transformation program. Our OCM services focus on strategic planning and execution support. We have found that most companies understand the importance of OCM, often don’t fully follow through on it.
A model-based future?
During the CIMdata Roadmap & PDT conferences, we have often discussed the importance of Model-Based Systems Engineering methodology as a foundation of a model-based enterprise. What do you see? Is it only the big Aerospace and Defense companies that can afford this learning journey, or should other industries also invest? And if yes, how to start.
Jos, here I need to step back for a minute. All companies have to deal with increasing complexity for their organization, supply chain, products, and more.
So, to optimize its business, an organization must understand and employ systems thinking and system optimization concepts. Unfortunately, most people think of MBSE as an engineering discipline. This is unfortunate because engineering is only one of the systems of systems that an organization needs to optimize across its end-to-end value streams.
The reality is all companies can benefit from MBSE. As long as they consider optimization across their specific disciplines, in the context of their products and services and where they exist within their value chain.
The MBSE is not just for Aerospace and Defense companies. Still, a lot can be learned from what has already been done. Also, leading automotive companies are implementing and using MBSE to design and optimize semi- and high-automated vehicles (i.e., systems of systems).
The starting point is understanding your systems of systems environment and where bottlenecks exist.
There should be no doubt, education is needed on MBSE and how MBSE supports the organization’s Model-Based Enterprise requirements.
Published work from the CIMdata administrated A&D PLM Action Group can be helpful. Also, various MBE and systems engineering maturity models, such as one that CIMdata utilizes in its consulting work.
Want to learn more?
Thanks, Peter, for sharing your insights. Are there any specific links you want to provide to get educated on the topics discussed? Perhaps some books to read or conferences to visit?
x
Jos, as you already mentioned:
x
- the CIMdata Roadmap & PDT conferences have provided a wealth of insight into this market for more than 25 years.
[Jos: Search for my blog posts starting with the text: “The weekend after ….”] - In addition, there are several blogs, like yours, that are worth following, and websites, like CIMdata’s pages for education or other resources which are filled with downloadable reading material.
- Additionally, there are many user conferences from PLM solution providers and third-party conferences, such as those hosted by the MarketKey organization in the UK.
These conferences have taken place in Europe and North America for several years. Information exchange and formal training and education are offered in many events. Additionally, they provide an excellent opportunity for networking and professional collaboration.
What I learned
Talking with Peter made me again aware of a few things. First, it is important to differentiate between education and training. Where education is a continuous process, training is an activity that must take place at the right time. Unfortunately, we often mix those two terms and believe that people are educated after having followed a training.
Secondly, investing in education is as crucial as investing in hard- or software. As Peter mentioned:
We often start with describing the difference between digitalization and digitization. This is crucial to be understood by an organization’s management team. In addition, management must understand that digitalization is an enterprise initiative.
System Thinking is not just an engineering term; it will be a mandate for managing a company, a product and even a planet into the future
Conclusion
This time a quote from Albert Einstein, supporting my PLM coaching intentions:
“Education is not the learning of facts
but the training of the mind to think.”
In March 2018, I started a series of blog posts related to model-based approaches. The first post was: Model-Based – an introduction. The reactions to these series of posts can be summarized in two bullets:
- Readers believed that the term model-based was focusing on the 3D CAD model. A logical association as PLM is often associated with 3D CAD-model data management (actually PDM), and in many companies, the 3D CAD model is (yet) not a major information carrier/
- Readers were telling me that a model-based approach is too far from their day-to-day life. I have to agree here. I was active in some advanced projects where the product’s behavior depends on a combination of hardware and software. However, most companies still work in a document-driven, siloed discipline manner merging all deliverables in a BOM.
More than 3 years later, I feel that model-based approaches have become more and more visible for companies. One of the primary reasons is that companies start to collaborate in the cloud and realize the differences between a coordinated and a connected manner.
Initiatives as Industry 4.0 or concepts like the Digital Twin demand a model-based approach. This post is a follow-up to my recent post, The Future of PLM.
History has shown that it is difficult for companies to change engineering concepts. So let’s first look back at how concepts slowly changed.
The age of paper drawings
In the sixties of the previous century, the drawing board was the primary “tool” to specify a mechanical product. The drawing on its own was often a masterpiece drawn on special paper, with perspectives, details, cross-sections.
All these details were needed to transfer the part or assembly information to manufacturing. The drawing set should contain all information as there were no computers.
Making a prototype was, depending on the complexity of the product, the interpretation of the drawings and manufacturability of a product, not always that easy. After a first release, further modifications to the product definition were often marked on the manufacturing drawings using a red pencil. Terms like blueprint and redlining come from the age of paper drawings.
There are still people talking nostalgically about these days as creating and interpreting drawings was an important skill. However, the inefficiencies with this approach were significant.
- First, updating drawings because there was redlining in manufacturing was often not done – too much work.
- Second, drawing reuse was almost impossible; you had to start from scratch.
- Third, and most importantly, you needed to be very skilled in interpreting a drawing set. In particular, when dealing with suppliers that might not have the same skillset and the knowledge of which drawing version was actual.
However, paper was and still is the cheapest neutral format to distribute designs. The last time I saw companies still working with paper drawings was at the end of the previous century.
Curious to learn if they are now extinct?
The age of electronic drawings (CAD)
With the introduction of AutoCAD and personal computers around 1982, more companies started to look into drafting with the computer. There was already the IBM drafting system in 1965, but it was Autodesk that pushed the 2D drafting business with their slogan:
“80 percent of the functionality for 20 percent of the price (Autodesk 1982)”
A little later, I started to work for an Autodesk distributor/reseller. People would come to the showroom to see how a computer drawing could be plotted in the finest quality at the end. But, of course, the original draftsman did not like the computer as the screen was too small.
However, the enormous value came from making changes, the easy way of sharing drawings and the ease of reuse. The picture on the left is me in 1989, demonstrating AutoCAD with a custom-defined tablet and PS/2 computer.
The introduction of electronic drawings was not a disruption, more optimization of the previous ways of working.
The exchange with suppliers and manufacturing could still be based on plotted drawings – the most neutral format. And thanks to the filename, there was better control of versions between all stakeholders.
Aren’t we all happy?
The introduction of mainstream 3D CAD
In 1995, 3D CAD became available for the mid-market, thanks to SolidWorks, Solid Edge and a little later Inventor. Before that working with 3D CAD was only possible for companies that could afford expensive graphic stations, provided by IBM, Silicon Graphics, DEC and SUN. Where are they nowadays? The PC is an example of disruptive innovation, purely based on technology. See Clayton Christensen’s famous book: The Innovator’s Dilemma.
The introduction of 3D CAD on PCs in the mid-market did not lead directly to new ways of working. Designing a product in 3D was much more efficient if you mastered the skills. 3D brought a better understanding of the product dimensions and shape, reducing the number of interpretation errors.
Still, (electronic) drawings were the contractual deliverable when interacting with suppliers and manufacturing. As students were more and more trained with the 3D CAD tools, the traditional art of the draftsman disappeared.
3D CAD introduced some new topics to solve.
- First of all, a 3D CAD Assembly in the system was a collection of separate files, subassemblies, parts, and drawings that relate to each other with a specific version. So how to ensure the final assembly drawings were based on the correct part revisions? Companies were solving this by either using intelligent filenames (with revisions) or by using a PDM system where the database of the PDM system managed all the relations and their status.
- The second point was that the 3D CAD assembly also introduced a new feature, the product structure, or the “Bill of Materials”. This logical structure of the assembly up resembled a lot of the Bill of Material of the product. You could even browse deeper levels, which was not the case in the traditional Bill of Material on a drawing.
Note: The concept of EBOM and MBOM was not known in most companies. People were talking about the BOM as a one-level definition of parts or subassemblies in the assembly. See my Where is the MBOM? Post from July 2008 when this topic was still under discussion.
- The third point that would have a more significant impact later is that parts and assemblies could be reused in other products. This introduced the complexity of configuration management. For example, a 3D CAD part or assembly file could contain several configurations where only one configuration would be valid for the given product. Managing this in the 3D CAD system lead to higher productivity of the designer, however downstream when it came to data management with PDM systems, it became a nightmare.
I experienced these issues a lot when discussing with companies and implementers, mainly the implementation of SmarTeam combined with SolidWorks and Inventor. Where to manage the configuration constraints? In the PDM system or inside the 3D CAD system.
These environments were not friends (image above), and even if they came from the same vendor, it felt like discussing with tribes.
The third point also covered another topic. So far, CAD had been the first step for the detailed design of a product. However, companies now had an existing Bill of Material in the system thanks to the PDM systems. It could be a Bill of Material of a sub-assembly that is used in many other products.
Configuring a product no longer started from CAD; it started from a Product or Bill of Material structure. Sales and Engineers identified the changes needed on the BoM, keeping as much as possible released information untouched. This led to a new best practice.
The item-centric approach
Around 2005, five years after introducing the term Product Lifecycle Management, slowly, a new approach became the standard. Product Lifecycle Management was initially introduced to connect engineering and manufacturing, driven by the automotive and aerospace industry.
It was with PLM that concepts as EBOM and MBOM became visible.
In particular, the EBOM was closely linked to engineering practices, i.e., modularity and reuse. The EBOM and its related information represented the product as it was specified. It is essential to realize that the parts in the EBOM could be generic specified purchase parts to be resolved when producing the product or that the EBOM contained Make-parts specified by drawings.
At that time, the EBOM was often used as the foundation for the ERP system – see image above. The BOM was restructured and organized according to the manufacturing process specifying materials and resources needed in the ERP system. Therefore, although it was an item-like structure, this BOM (the MBOM) always had a close relation to the Bill of Process.
For companies with a single manufacturing site, the notion of EBOM and MBOM was not that big, as the ERP system would be the source of the MBOM. However, the complexity came when companies have several manufacturing sites. That was when a generic MBOM in the PLM system made more sense to centralize all product information in a single system.
The EBOM-MBOM approach has become more and more a standard practice since 2010. As a result, even small and medium-sized enterprises realized a need to manage the EBOM and the MBOM.
There were two disadvantages introduced with this EBOM-MBOM approach.
- First, the EBOM and the MBOM as information structures require a lot of administrative maintenance if information needs to be always correct (and that is the CM target). Some try to simplify this by keeping the EBOM part the same as the MBOM part, meaning the EBOM specification already targets a single supplier or manufacturer.
- The second disadvantage of making every item in the BOM behave like a part creates inefficiencies in modern environments. Products are a mix of hardware(parts) and software(models/behavior). This BOM-centric view does not provide the proper infrastructure for a data-driven approach as part specifications are still done in drawings. We need 3D annotated models related to all kinds of other behavior and physical models to specify a product that contains hard-and software.
A new paradigm is needed to manage this mix efficiently, the enabling foundation for Industry 4.0 and efficient Digital Twins; there is a need for a model-based approach based on connected data elements.
More next week.
Conclusion
| The age of paper drawings | 1960 – now dead |
| The age of electronic drawings | 1982 – potentially dead in 2030 |
| The mainstream 3D CAD | 1995 – to be evolving through MBD and MBSE to the future – not dead shortly |
| Item-centric approach | 2005 – to be evolving to a connected model-based approach – not dead shortly |
One of my favorite conferences is the PLM Road Map & PDT conference. Probably because in the pre-COVID days, it was the best PLM conference to network with peers focusing on PLM practices, standards, and sustainability topics. Now the conference is virtual, and hopefully, after the pandemic, we will meet again in the conference space to elaborate on our experiences further.
Last year’s fall conference was special because we had three days filled with a generic PLM update and several A&D (Aerospace & Defense) working groups updates, reporting their progress and findings. Sessions related to the Multiview BOM research, Global Collaboration, and several aspects of Model-Based practices: Model-Based Definition, Model-Based Engineering & Model-Based Systems engineering.
All topics that I will elaborate on soon. You can refresh your memory through these two links:
- The weekend after PLM Roadmap / PDT 2020 – part 1
- The next weekend after PLM Roadmap / PDT 2020 – part 2
This year, it was a two-day conference with approximately 200 attendees discussing how emerging technologies can disrupt the current PLM landscape and reshape the PLM Value Equation. During the first day of the conference, we focused on technology.
On the second day, we looked in addition to the impact new technology has on people and organizations.
Today’s Emerging Trends & Disrupters
Peter Bilello, CIMdata’s President & CEO, kicked off the conference by providing CIMdata observations of the market. An increasing number of technology capabilities, like cloud, additive manufacturing, platforms, digital thread, and digital twin, all with the potential of realizing a connected vision. Meanwhile, companies evolve at their own pace, illustrating that the gap between the leaders and followers becomes bigger and bigger.
Where is your company? Can you afford to be a follower? Is your PLM ready for the future? Probably not, Peter states.
Next, Peter walked us through some technology trends and their applicability for a future PLM, like topological data analytics (TDA), the Graph Database, Low-Code/No-Code platforms, Additive Manufacturing, DevOps, and Agile ways of working during product development. All capabilities should be related to new ways of working and updated individual skills.
I fully agreed with Peter’s final slide – we have to actively rethink and reshape PLM – not by calling it different but by learning, experimenting, and discussing in the field.
Digital Transformation Supporting Army Modernization
An interesting viewpoint related to modern PLM came from Dr. Raj Iyer, Chief Information Officer for IT Reform from the US Army. Rai walked us through some of the US Army’s challenges, and he gave us some fantastic statements to think about. Although an Army cannot be compared with a commercial business, its target remains to be always ahead of the competition and be aware of the competition.
Where we would say “data is the new oil”, Rai Iyer said: “Data is the ammunition of the future fight – as fights will more and more take place in cyberspace.”
The US Army is using a lot of modern technology – as the image below shows. The big difference here with regular businesses is that it is not about ROI but about winning fights.
Also, for the US Army, the cloud becomes the platform of the future. Due to the wide range of assets, the US Army has to manage, the importance of product data standards is evident. – Rai mentioned their contribution and adherence to the ISO 10303 STEP standard crucial for interoperability. It was an exciting insight into the US Army’s current and future challenges. Their primary mission remains to stay ahead of the competition.
Joining up Engineering Data without losing the M in PLM
Nigel Shaw’s (Eurostep) presentation was somehow philosophical but precisely to the point what is the current dilemma in the PLM domain. Through an analogy of the internet, explaining that we live in a world of HTTP(s) linking, we create new ways of connecting information. The link becomes an essential artifact in our information model.
Where it is apparent links are crucial for managing engineering data, Nigel pointed out some of the significant challenges of this approach, as you can see from his (compiled) image below.
I will not discuss this topic further here as I am planning to come back to this topic when explaining the challenges of the future of PLM.
As Nigel said, they have a debate with one of their customers to replace the existing PLM tools or enhance the existing PLM tools. The challenge of moving from coordinated information towards connected data is a topic that we as a community should study.
Integration is about more than Model Format.
This was the presentation I have been waiting for. Mark Williams from Boeing had built the story together with Adrian Burton from Airbus. Nigel Shaw, in the previous session, already pointed to the challenge of managing linked information. Mark elaborated further about the model-based approach for system definition.
All content was related to the understanding that we need a model-based information infrastructure for the future because storing information in documents (the coordinated approach) is no longer viable for complex systems. Mark ‘slide below says it all.
Mark stressed the importance of managing model information in context, and it has become a challenge.
Mark mentioned that 20 years ago, the IDC (International Data Corporation) measured Boeing’s performance and estimated that each employee spent 2 ½ hours per day. In 2018, the IDC estimated that this number has grown to 30 % of the employee’s time and could go up to 50 % when adding the effort of reusing and duplicating data.
The consequence of this would be that a full-service enterprise, having engineering, manufacturing and services connected, probably loses 70 % of its information because they cannot find it—an impressive number asking for “clever” ways to find the correct information in context.
It is not about just a full indexed search of the data, as some technology geeks might think. It is also about describing and standardizing metadata that describes the models. In that context, Mark walked through a list of existing standards, all with their pros and cons, ending up with the recommendation to use the ISO 10303-243 – MoSSEC standard.
MoSSEC standing for Modelling and Simulation information in a collaborative Systems Engineering Context to manage and connect the relationships between models.
MoSSEC and its implication for future digital enterprises are interesting, considering the importance of a model-based future. I am curious how PLM Vendors and tools will support and enable the standard for future interoperability and collaboration.
Additive Manufacturing
– not as simple as paper printing – yet
Andreas Graichen from Siemens Energy closed the day, coming back to the new technologies’ topic: Additive Manufacturing or in common language 3D Printing. Andreas shared their Additive Manufacturing experiences, matching the famous Gartner Hype Cycle. His image shows that real work needs to be done to understand the technology and its use cases after the first excitement of the hype is over.
Material knowledge was one of the important topics to study when applying additive manufacturing. It is probably a new area for most companies to understand the material behaviors and properties in an Additive Manufacturing process.
The ultimate goal for Siemens Energy is to reach an “autonomous” workshop anywhere in the world where gas turbines could order their spare parts by themselves through digital warehouses. It is a grand vision, and Andreas confirmed that the scalability of Additive Manufacturing is still a challenge.
For rapid prototyping or small series of spare parts, Additive Manufacturing might be the right solution. The success of your Additive Manufacturing process depends a lot on how your company’s management has realistic expectations and the budget available to explore this direction.
Conclusion
Day 1 was enjoyable and educational, starting and ending with a focus on disruptive technologies. The middle part related to data the data management concepts needed for a digital enterprise were the most exciting topics to follow up in my opinion.
Next week I will follow up with reviewing day 2 and share my conclusions. The PLM Road Map & PDT Spring 2021 conference confirmed that there is work to do to understand the future (of PLM).
Last summer, I wrote a series of blog posts grouped by the theme “Learning from the past to understand the future”. These posts took you through the early days of drawings and numbering practices towards what we currently consider the best practice: PLM BOM-centric backbone for product lifecycle information.
You can find an overview and links to these posts on the page Learning from the past.
If you have read these posts, or if you have gone yourself through this journey, you will realize that all steps were more or less done evolutionarily. There were no disruptions. Affordable 3D CAD systems, new internet paradigms (interactive internet), global connectivity and mobile devices all introduced new capabilities for the mainstream. As described in these posts, the new capabilities sometimes created friction with old practices. Probably the most popular topics are the whole Form-Fit-Function interpretation and the discussion related to meaningful part numbers.
What is changing?
In the last five to ten years, a lot of new technology has come into our lives. The majority of these technologies are related to dealing with data. Digital transformation in the PLM domain means moving from a file-based/document-centric approach to a data-driven approach.
A Bill of Material on the drawing has become an Excel-like table in a PLM system. However, an Excel file is still used to represent a Bill of Material in companies that have not implemented PLM.
Another example, the specification document has become a collection of individual requirements in a system. Each requirement is a data object with its own status and content. The specification becomes a report combining all valid requirement objects.
Related to CAD, the 2D drawing is no longer the deliverable as a document; the 3D CAD model with its annotated views becomes the information carrier for engineering and manufacturing.
And most important of all, traditional PLM methodologies have been based on a mechanical design and release process. Meanwhile, modern products are systems where the majority of capabilities are defined by software. Software has an entirely different configuration and lifecycle approach conflicting with a mechanical approach, which is too rigid for software.
The last two aspects, from 2D drawings to 3D Models and Mechanical products towards Systems (hardware and software), require new data management methods. In this environment, we need to learn to manage simulation models, behavior models, physics models and 3D models as connected as possible.
I wrote about these changes three years ago: Model-Based – an introduction, which led to a lot of misunderstanding (too advanced – too hypothetical).
I plan to revisit these topics in the upcoming months again to see what has changed over the past three years.
What will I discuss in the upcoming weeks?
My first focus is on participating and contributing to the upcoming PLM Roadmap & PDS spring 2021 conference. Here speakers will discuss the need for reshaping the PLM Value Equation due to new emerging technologies. A topic that contributes perfectly to the future of PLM series.
My contribution will focus on the fact that technology alone cannot disrupt the PLM domain. We also have to deal with legacy data and legacy ways of working.
Another post will focus on the difference between the digital thread and the digital thread. Yes, it looks like I am writing twice the same words. However, you will see based on its interpretation, one definition is hanging on the past, the other is targeting the future. Again here, the differentiation is crucial if the need for a maintainable Digital Twin is required.
Model-Based Systems Engineering (MBSE) in all its aspects needs to be discussed too. MBSE is crucial for defining complex products. Model-Based Systems Engineering is seen as a discipline to design products. Understanding data management related to MBSE will be the foundation for understanding data management in a Model-Based Enterprise. For example, how to deal with configuration management in the future?
Writing Learning from the past was an easy job as explaining with hindsight is so much easier if you have lived it through. I am curious and excited about the outcome of “The Future of PLM”. Writing about the future means you have digested the information coming to you, knowing that nobody has a clear blueprint for the future of PLM.
There are people and organizations are working on this topic more academically, for example read this post from Lionel Grealou related to the Place of PLM in the Digital Future. The challenge is that an academic future might be disrupted by unpredictable events, like COVID, or disruptive technologies combined with an opportunity to succeed. Therefore I believe, it will be a learning journey for all of us where we need to learn to give technology a business purpose. Business first – then technology.
No Conclusion
Normally I close my post with a conclusion. At this moment. there is no conclusion as the journey has just started. I look forward to debating and learning with practitioners in the field. Work together on methodology and concepts that work in a digital enterprise. Join me on this journey. I will start sharing my thoughts in the upcoming months
After the first episode of “The PLM Doctor is IN“, this time a question from Helena Gutierrez. Helena is one of the founders of SharePLM, a young and dynamic company focusing on providing education services based on your company’s needs, instead of leaving it to function-feature training.
I might come back on this topic later this year in the context of PLM and complementary domains/services.
Now sit back and enjoy.
Note: Due to a technical mistake Helena’s mimic might give you a “CNN-like” impression as the recording of her doctor visit was too short to cover the full response.
PLM and Startups – is this a good match?
Relevant links discussed in this video
Marc Halpern (Gartner): The PLM maturity table
VirtualDutchman: Digital PLM requires a Model-Based Enterprise
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.
Last week I shared my plans for 2021 related to my blog, virtualdutchman.com. Those of you who follow my blog might have noticed my posts are never short as I try to discuss or explain a topic from various aspects. This sometimes requires additional research from my side. The findings will provide benefits for all of us. We keep on learning.
At the end of the post, I asked you to participate in a survey to provide feedback on the proposed topics. So far, only one percent of my readers have responded to this short survey. The last time I shared a short survey in 2018, the response was much more significant.
Perhaps you are tired of the many surveys; perhaps you did not make it to the end. Please make an effort this time. Here is on more time the survey
The results so far
To understand the topics below, please make sure you have read the previous blog post to understand each paragraph’s context.
PLM understanding
For PLM-related topics that I proposed, Product Configuration Management, Supplier Collaboration Management, and Digital Twin Management got the most traction. I started preparing for them, combined with a few new suggested topics that I will further explore. You can click on the images below to read the details.
PLM Deep dive
From the suggested topics for a PLM deep-dive, it is interesting to see most respondents want to learn more about Product Portfolio Management and Systems Engineering within PLM. Traditional topics like Enterprise/Engineering Change Management, BOM Management, or PLM implementation methodologies have been considered less relevant.
The PLM Doctor is in
Several questions were coming in for the “PLM Doctor,” and I started planning the first episodes. The formula: A single question and an answer through a video recording – max. 2 – 3 minutes. Suitable for fast consumers of information.
PLM and Sustainability
Here we can see the majority is observing what is happening. Only a few persons reported interest in sustainability and probably not disconnected; they work for a company that takes sustainability seriously.
PLM and digitization
When discussing PLM’s digitization, I believe one of the fundamental changes that we need to implement (and learn to master) is a more Model-Based approach for each phase of the product life cycle. Also, most respondents have a notion of what model-based means and want to apply these practices to engineering and manufacturing.
Your feedback
I think you all have heard this statement before about Lies and Statistics. Especially with social media, there are billions of people digging for statistics to support their theories. Don’t worry about my situation; I would like to make my statement based on some larger numbers, so please take the survey here if you haven’t done so.
Conclusion
I am curious about your detailed inputs, and the next blog post will be the first of the 2021 series.
It Is 2021, and after two weeks’ time-out and reflection, it is time to look forward. Many people have said that 2020 was a “lost year,” and they are looking forward to a fresh restart, back to the new normal. For me, 2020 was the contrary of a lost year. It was a year where I had to change my ways of working. Communication has changed, digitization has progressed, and new trends have become apparent.
If you are interested in some of the details, watch the conversation I had with Rob Ferrone from QuickRelease, just before Christmas: Two Santas looking back to 2020.
It was an experiment with video, and you can see there is a lot to learn for me. I agree with Ilan Madjar’s comment that it is hard to watch two people talking for 20 minutes. I prefer written text that I can read at my own pace, short videos (max 5 min), or long podcasts that I can listen to, when cycling or walking around.
So let me share with you some of the plans I have for 2021, and I am eager to learn from you where we can align.
PLM understanding
I plan a series of blog posts where I want to share PLM-related topics that are not necessarily directly implemented in a PLM-system or considered in PLM-implementations as they require inputs from multiple sources. Topics in this context are: Configuration Management, Product Configuration Management, Product Information Management, Supplier Collaboration Management, Digital Twin Management, and probably more.
For these posts, I will discuss the topic with a subject matter expert, potentially a vendor or a consultant in that specific domain, and discuss the complementary role to traditional PLM. Besides a blog post, this topic might also be more explained in-depth in a podcast.
The PLM Doctor is in
Most of you might have seen Lucy from the Charley Brown cartoon as the doctor giving advice for 5¢. As an experiment, I want to set up a similar approach, however, for free.
These are my conditions:
- Only one question at a time.
- The question and answer will be published in a 2- 3 minute video.
- The question is about solving a pain.
If you have such a question related to PLM, please contact me through a personal message on LinkedIn, and I will follow-up.
PLM and Sustainability
A year ago, I started with Rich McFall, the PLM Green Global Alliance. Our purpose to bring people together, who want to learn and share PLM-related practices, solutions, ideas contributing to a greener and more sustainable planet.
We do not want to compete or overlap with more significant global or local organizations, like the Ellen McArthur Foundation or the European Green Deal.
We want to bring people together to dive into the niche of PLM and its related practices. We announced the group on LinkedIn; however, to ensure a persistent referential for all information and interactions, we have launched the website plmgreenaliance.com.
Here I will moderate and focus on PLM and Sustainability topics. I am looking forward to interacting with many of you.
PLM and digitization
For the last two years, I have been speaking and writing about the gap between current PLM-practices, based on shareable documents and files and the potential future based on shareable data, the Model-Based Enterprise.
Last year I wrote a series of posts giving insights on how we reached the current PLM-practices. Discovering sometimes inconsistencies and issues due to old habits or technology changes. I grouped these posts on a single blog page with the title: Learning from the past.
This year I will create a collection of posts focusing on the transition towards a Model-Based Enterprise. Probably the summary page will be called: Working towards the future currently in private mode.
Your feedback
I am always curious about your feedback – to understand in which kind of environment your PLM activities take place. Which topics are unclear? What am I missing in my experience?
Therefore, I created a small anonymous survey for those who want to be interacting with me. On purpose, the link is at the bottom of the post, so when you answer the survey, you get my double appreciation, first for reaching the end of this post and second for answering the survey.
Take the survey here.
Conclusion
Most of us will have a challenging year ahead of us. Sharing and discussing challenges and experiences will help us all to be better in what we are doing. I look forward to our 2021 journey.
Image courtesy of http://www.blagues-et-dessins.com
Last week I shared my first review of the PLM Roadmap / PDT Fall 2020 conference, organized by CIMdata and Eurostep. Having digested now most of the content in detail, I can state this was the best conference of 2020. In my first post, the topics I shared were mainly the consultant’s view of digital thread and digital twin concepts.
This time, I want to focus on the content presented by the various Aerospace & Defense working groups who shared their findings, lessons-learned (so far) on topics like the Multi-view BOM, Supply Chain Collaboration, MBSE Data interoperability.
These sessions were nicely wrapped with presentations from Alberto Ferrari (Raytheon), discussing the digital thread between PLM and Simulation Lifecycle Management and Jeff Plant (Boeing) sharing their Model-Based Engineering strategy.
I believe these insights are crucial, although there might be people in the field that will question if this research is essential. Is not there an easier way to achieve to have the same results?
Nicely formulated by Ilan Madjar as a comment to my first post:
Ilan makes a good point about simplifying the ideas to the masses to make it work. The majority of companies probably do not have the bandwidth to invest and understand the future benefits of a digital thread or digital twins.
This does not mean that these topics should not be studied. If your business is in a small, simple eco-system and wants to work in a connected mode, you can choose a vendor and a few custom interfaces.
However, suppose you work in a global industry with an extensive network of partners, suppliers, and customers.
In that case, you cannot rely on ad-hoc interfaces or a single vendor. You need to invest in standards; you need to study common best practices to drive methodology, standards, and vendors to align.
This process of standardization is so crucial if you want to have a sustainable, connected enterprise. In the end, the push from these companies will lead to standards, allowing the smaller companies to ad-here or connect to.
The future is about Connected through Standards, as discussed in part 1 and further in this post. Let’s go!
Global Collaboration – Defining a baseline for data exchange processes and standards
Katheryn Bell (Pratt & Whitney Canada) presented the progress of the A&D Global Collaboration workgroup. As you can see from the project timeline, they have reached the phase to look towards the future.
Katheryn mentioned the need to standardize terminology as the first point of attention. I am fully aligned with that point; without a standardized terminology framework, people will have a misunderstanding in communication.
This happens even more in the smaller businesses that just pick sometimes (buzz) terms without a full understanding.
Several years ago, I talked with a PLM-implementer telling me that their implementation focus was on systems engineering. After some more explanations, it appeared they were making an attempt for configuration management in reality. Here the confusion was massive. Still, a standard, common terminology is crucial in our domain, even if it seems academic.
The group has been analyzing interoperability standards, standards for long-time archival and retrieval (LOTAR), but also has been studying the ISO 44001 standard related to Collaborative business relationship management systems
In the Q&A session, Katheryn explained that the biggest problem to solve with collaboration was the risk of working with the wrong version of data between disciplines and suppliers.
Of course, such errors can lead to huge costs if they are discovered late (or too late). As some of the big OEMs work with thousands of suppliers, you can imagine it is not an issue easily discovered in a more ad-hoc environment.
The move to a standardized Technical Data Package based on a Model-Based Definition is one of these initiatives in this domain to reduce these types of errors.
You can find the proceedings from the Global Collaboration working group here.
Connect, Trace, and Manage Lifecycle of Models, Simulation and Linked Data: Is That Easy?
I loved Alberto Ferrari‘s (Raytheon) presentation how he described the value of a model-based digital thread, positioning it in a targeted enterprise.
Click on the image and discover how business objectives, processes and models go together supported by a federated infrastructure.
Alberto’s presentation was a kind of mind map from how I imagine the future, and it is a pity if you have not had the chance to see his session.
Alberto also focused on the importance of various simulation capabilities combined with simulation lifecycle management. For Alberto, they are essential to implement digital twins. Besides focusing on standards, Alberto pleas for a semantic integration, open service architecture with the importance of DevSecOps.
Enough food for thought; as Alberto mentioned, he presented the corporate vision, not the current state.
More A&D Action Groups
There were two more interesting specialized sessions where teams from the A&D action groups provided a status update.
Brandon Sapp (Boeing) and Ian Parent (Pratt & Whitney) shared the activities and progress on Minimum Model-Based Definition (MBD) for Type Design Certification.
As Brandon mentioned, MBD is already a widely used capability; however, MBD is still maturing and evolving. I believe that is also one of the reasons why MBD is not yet accepted in mainstream PLM. Smaller organizations will wait; however, can your company afford to wait?
More information about their progress can be found here.
Mark Williams (Boeing) reported from the A&D Model-Based Systems Engineering action group their first findings related to MBSE Data Interoperability, focusing on an Architecture Model Exchange Solution. A topic interesting to follow as the promise of MBSE is that it is about connected information shared in models. As Mark explained, data exchange standards for requirements and behavior models are mature, readily available in the tools, and easily adopted. Exchanging architecture models has proven to be very difficult. I will not dive into more details, respecting the audience of this blog.
For those interested in their progress, more information can be found here
Model-Based Engineering @ Boeing
In this conference, the participation of Boeing was significant through the various action groups. As the cherry on the cake, there was Jeff Plant‘s session, giving an overview of what is happening at Boeing. Jeff is Boeing’s director of engineering practices, processes, and tools.
In his introduction, Jeff mentioned that Boeing has more than 160.000 employees in over 65 countries. They are working with more than 12.000 suppliers globally. These suppliers can be manufacturing, service or technology partnerships. Therefore you can imagine, and as discussed by others during the conference, streamlined collaboration and traceability are crucial.
The now-famous MBE Diamond symbol illustrates the model-based information flows in the virtual world and the physical world based on the systems engineering approach. Like Katheryn Bell did in her session related to Global Collaboration, Jeff started explaining the importance of a common language and taxonomy needed if you want to standardize processes.
Zoom in on the Boeing MBE Taxonomy, you will discover the clarity it brings for the company.
I was not aware of the ISO 23247 standard concerning the Digital Twin framework for manufacturing, aiming to apply industry standards to the model-based definition of products and process planning. A standard certainly to follow as it brings standardization on top of existing standards.
As Jeff noted: A practical standard for implementation in a company of any size. In my opinion, mandatory for a sustainable, connected infrastructure.
Jeff presented the slide below, showing their standardization internally around federated platforms.
This slide resembles a lot the future platform vision I have been sharing since 2017 when discussing PLM’s future at PLM conferences, when explaining the differences between Coordinated and Connected – see also my presentation here on Slideshare.
You can zoom in on the picture to see the similarities. For me, the differences were interesting to observe. In Jeff’s diagram, the product lifecycle at the top indicates the platform of (central) interest during each lifecycle stage, suggesting a linear process again.
In reality, the flow of information through feedback loops will be there too.
The second exciting detail is that these federated architectures should be based on strong interoperability standards. Jeff is urging other companies, academics and vendors to invest and come to industry standards for Model-Based System Engineering practices. The time is now to act on this domain.
It reminded me again of Marc Halpern’s message mentioned in my previous post (part 1) that we should be worried about vendor alliances offering an integrated end-to-end data flow based on their solutions. This would lead to an immense vendor-lock in if these interfaces are not based on strong industry standards.
Therefore, don’t watch from the sideline; it is the voice (and effort) of the companies that can drive standards.
Finally, during the Q&A part, Jeff made an interesting point explaining Boeing is making a serious investment, as you can see from their participation in all the action groups. They have made the long-term business case.
The team is confident that the business case for such an investment is firm and stable, however in such long-term investment without direct results, these projects might come under pressure when the business is under pressure.
The virtual fireside chat
The conference ended with a virtual fireside chat from which I picked up an interesting point that Marc Halpern was bringing in. Marc mentioned a survey Gartner has done with companies in fast-moving industries related to the benefits of PLM. Companies reported improvements in accuracy and product development. They did not see so much a reduced time to market or cost reduction. After analysis, Gartner believes the real issue is related to collaboration processes and supply chain practices. Here lead times did not change, nor the number of changes.
Marc believes that this topic will be really showing benefits in the future with cloud and connected suppliers. This reminded me of an article published by McKinsey called The case for digital reinvention. In this article, the authors indicated that only 2 % of the companies interview were investing in a digital supply chain. At the same time, the expected benefits in this area would have the most significant ROI.
The good news, there is consistency, and we know where to focus for early results.
Conclusion
It was a great conference as here we could see digital transformation in action (groups). Where vendor solutions often provide a sneaky preview of the future, we saw people working on creating the right foundations based on standards. My appreciation goes to all the active members in the CIMdata A&D action groups as they provide the groundwork for all of us – sooner or later.
Jos Voskuil's Weblog 
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