Are we blocking our future?

August 26, 2018 in Blocking change, Brain, Change, Digital Enterprise, Education, Innovation, intelligence, Knowledge Management, MBD, MBE, MBM, MBSE, model-based, Observations, PLM, Social Media | Tags: , , , , , | Leave a comment

During my holiday I have read some interesting books. Some for the beauty of imagination and some to enrich my understanding of the human brain.

Why the human brain? It is the foundation and motto of my company: The Know-How to Know Now.
In 2012 I wrote a post: Our brain blocks PLM acceptance followed by a post in 2014  PLM is doomed, unless …… both based on observations and inspired by the following books (must read if you are interested in more than just PLM practices and technology):

In 2014, Digital Transformation was not so clear. We talked about disruptors, but disruption happened outside our PLM comfort zone.

Now six years later disruption or significant change in the way we develop and deliver solutions to the market has become visible in the majority of companies. To stay competitive or meaningful in a global market with changing customer demands, old ways of working no longer bring enough revenue to sustain.  The impact of software as part of the solution has significantly changed the complexity and lifecycle(s) of solutions on the market.

Most of my earlier posts in the past two years are related to these challenges.

What is blocking Model-Based Definition?

This week I had a meeting in the Netherlands with three Dutch peers all interested and involved in Model-Based Definition – either from the coaching point of view or the “victim” point of view.  We compared MBD-challenges with Joe Brouwer’s AID (Associated Information Documents) approach and found a lot of commonalities.

No matter which method you use it is about specifying unambiguously how a product should be manufactured – this is a skill and craftsmanship and not a technology. We agreed that a model-based approach where information (PMI) is stored as intelligent data elements in a Technical Data Package (TPD) will be crucial for multidisciplinary usage of a 3D Model and its associated information.

If we would store the information again as dumb text in a view, it will need human rework leading to potential parallel information out of sync, therefore creating communication and quality issues. Unfortunate as it was a short meeting, the intention is to follow-up this discussion in the Netherlands to a broader audience. I believe this is what everyone interested in learning and understanding the needs and benefits of a model-based approach (unavoidable) should do. Get connected around the table and share/discuss.

We realized that human beings indeed are often the blocking reason why new ways of working cannot be introduced. Twenty-five years ago we had the discussion moving from 2D to 3D for design. Now due to the maturity of the solutions and the education of new engineers this is no longer an issue. Now we are in the next wave using the 3D Model as the base for manufacturing definition, and again a new mindset is needed.

There are a few challenges here:

  • MBD is still in progress – standards like AP242 still needs enhancements
  • There is a lack of visibility on real reference stories to motivate others.
    (Vendor-driven stories often are too good to be true or too narrow in scope)
  • There is no education for (modern) business processes related to product development and manufacturing. Engineers with new skills are dropped in organizations with traditional processes and silo thinking.

Educate, or our brain will block the future!

The above points need to be addressed, and here the human brain comes again into the picture.  Our unconscious, reptile brain is continuously busy to spend a least amount of energy as described in Thinking, Fast and Slow. Currently, I am reading the Idiot Brain: What Your Head Is Really Up To by Dean Burnett, another book confirming that our brain is not a logical engine making wise decisions

And then there is the Dunning-Kruger effect, explaining that the people with the lowest skills often have the most outspoken opinion and not even aware of this flaw. We see this phenomenon in particular now in social media where people push their opinion as if they are facts.

So how can we learn new model-based approaches and here I mean all the model-based aspects I have discussed recently, i.e., Model-Based Systems Engineering, Model-Based Definition/ Model-Based Enterprise and the Digital Twin? We cannot learn it from a book, as we are entering a new era.

First, you might want to understand there is a need for new ways of working related to complex products. If you have time, listen to Xin Guo Zhang’s opening keynote with the title: Co-Evolution of Complex Aeronautical Systems & Complex SE. It takes 30 minutes so force yourself to think slow and comprehend the message related to the needed paradigm shift for systems engineering towards model-based systems engineering

Also, we have to believe that model-based is the future. If not, we will find for every issue on our path a reason not to work toward the ultimate goal.

You can see this in the comments of my earlier post on LinkedIn, where Sami Grönstrand writes:

I warmly welcome the initiative to “clean up” these concepts  (It is time to clean up our model-based problem and above all, await to see live examples of transformations — even partial — coupled with reasonable business value identification. 

There are two kinds of amazing places: those you have first to see before you can believe they exist.
And then those kinds that you have to believe in first before you can see them…

And here I think we need to simplify en enhance the Model-Based myth as according to Yuval Harari in his book Sapiens, the power of the human race came from creating myths to align people to have long-term, forward-looking changes accepted by our reptile brain. We are designed to believe in myths. Therefore, the need for a Model-based myth.In my post PLM as a myth? from 2017, I discussed this topic in more detail.

Conclusion

There are so many proof points that our human brain is not as reliable as we think it is.  Knowing less about these effects makes it even harder to make progress towards a digital future. This post with all its embedded links can keep your brain active for a few hours. Try it, avoid to think fast and avoid assuming you know it all. Your thoughts?

 

Learning & Discussing more?
Still time to register for CIMdata PLM Roadmap and PDT Europe

 

 

PLM Mid-terms and the flat earth

August 12, 2018 in Blocking change, Change, Data centric, Digital Twin, Education, MBD, MBE, MBM, MDM, model-based, PLM | Tags: , , | Leave a comment

 

http://gph.is/2bSeEYU

At this moment we are in the middle of the year. Usually for me a quiet time and a good time to reflect on what has happened so far and to look forward.

Three themes triggered me to write this half-year:

  • The changing roles of (PLM) consultancy
  • The disruptive effect of digital transformation on legacy PLM
  • The Model-driven approaches

A short summary per theme here with links to the original posts for those who haven’t followed the sequence.

The changing roles of (PLM) consultancy

Triggered by Oleg Shilovitsky’s post Why traditional PLM ranking is dead. PLM ranking 2.0 a discussion started related to the changing roles of PLM choice and the roles of a consultant.  Oleg and I agreed that using the word dead in a post title is a way to catch extra attention. And as many people do not read more than the introduction, this is a way to frame ideas (not invented by us, look at your newspaper and social media posts).  Please take your time and read this post till the end.

Oleg and I concluded that the traditional PLM status reports provided by consultancy firms are no longer is relevant. They focus on the big vendors, in a status-quo and most of them are 80 % the same on their core PLM capabilities. The challenge comes in how to select a PLM approach for your company.

Here Oleg and I differ in opinion. I am more looking at PLM from a business transformation point of view, how to improve your business with new ways of working. The role of a consultant is crucial here as the consultant can help to formalize the company’s vision and areas to focus on for PLM. The value of the PLM consultant is to bring experience from other companies instead of inventing new strategies per company. And yes, a consultant should get paid for this added value.

Oleg believes more in the bottom-up approach where new technology will enable users to work differently and empower themselves to improve their business (without calling it PLM). More or less concluding there is no need for a PLM consultant as the users will decide themselves about the value of the selected technology. In the context of Oleg’s position as CEO/Co-founder of OpenBOM, it is a logical statement, fighting for the same budget.

The discussion ended during the PLMx conference in Hamburg, where Oleg and I met with an audience recorded by MarketKey. You can find the recording Panel Discussion: Digital Transformation and the Future of PLM Consulting here.
Unfortunate, like many discussions, no conclusion. My conclusion remains the same – companies need PLM coaching !

The related post to this topic are:

 

The disruptive effect of digital transformation on legacy PLM

A topic that I have discussed the past two years is that current PLM is not compatible with a modern data-driven PLM. Note: data-driven PLM is still “under-development”. Where in most companies the definition of the products is stored in documents / files, I believe that in order to manage the complexity of products, hardware and software in the future, there is a need to organize data related to models not to files. See also: From Item-centric to model-centric ?

For a company it is extremely difficult to have two approaches in parallel as the first reaction is: “let’s convert the old data to the new environment”.

This statement has been proven impossible in most of the engagements I am involved in and here I introduced the bimodal approach as a way to keep the legacy going (mode 1) and scale-up for the new environment (mode 2).

A bimodal approach is sometimes acceptable when the PLM software comes from two different vendors. Sometimes this is also called the overlay approach – the old system remains in place and a new overlay is created to connect the legacy PLM system and potentially other systems like ALM or MBSE environments. For example some of the success stories for Aras complementing Siemens PLM.

Like the bimodal approach the overlay approach creates the illusion that in the near future the old legacy PLM will disappear. I partly share that illusion when you consider the near future a period of 5 – 10+ years depending on the company’s active products. Faster is not realistic.

And related to bimodal, I now prefer to use the terminology used by McKinsey: our insights/toward an integrated technology operating model in the context of PLM.

The challenge is that PLM vendors are reluctant to support a bimodal approach for their own legacy PLM as then suddenly this vendor becomes responsible for all connectivity between mode 1 and mode 2 data – every vendors wants to sell only the latest.

I will elaborate on this topic during the PDT Europe conference in Stuttgart – Oct 25th . No posts on this topic this year (yet) as I am discussing, learning and collecting examples from the field. What kept me relative busy was the next topic:

The Model-driven approaches

Most of my blogging time I spent on explaining the meaning behind a modern model-driven approach and its three main aspects: Model-Based Systems Engineering, Model-Based Definition and Digital Twins. As some of these aspects are still in the hype phase, it was interesting to see the two different opinions are popping up. On one side people claiming the world is still flat (2D), considering model-based approaches just another hype, caused by the vendors. There is apparently no need for digital continuity. If you look into the reactions from certain people, you might come to the conclusion it is impossible to have a dialogue, throwing opinions is not a discussion..

One of the reasons might be that people reacting strongly have never experienced model-based efforts in their life and just chime in or they might have a business reason not to agree to model-based approached as it does not align with their business? It is like the people benefiting from the climate change theory – will the vote against it when facts are known ? Just my thoughts.

There is also another group, to which I am connected, that is quite active in learning and formalizing model-based approaches. This in order to move forward towards a digital enterprise where information is connected and flowing related to various models (behavior models, simulation models, software models, 3D Models, operational models, etc., etc.) . This group of people is discussing standards and how to use and enhance them. They discuss and analyze with arguments and share lessons learned. One of the best upcoming events in that context is the joined CIMdata PLM Road Map EMEA and the PDT Europe 2018 – look at the agenda following the image link and you should get involved too – if you really care.

 

And if you are looking into your agenda for a wider, less geeky type of conference, consider the PI PLMx CHICAGO 2018 conference on Nov 5 and 6. The agenda provides a wider range of sessions, however I am sure you can find the people interested in discussing model-based learnings there too, in particular in this context Stream 2: Supporting the Digital Value Chain

My related posts to model-based this year were:

Conclusion

I spent a lot of time demystifying some of PLM-related themes. The challenge remains, like in the non-PLM world, that it is hard to get educated by blog posts as you might get over-informed by (vendor-related) posts all surfing somewhere on the hype curve. Do not look at the catchy title – investigate and take time to understand HOW things will this work for you or your company. There are enough people explaining WHAT they do, but HOW it fit in a current organization needs to be solved first. Therefore the above three themes.

Model-Based: Digital Twin – the PLM side

July 25, 2018 in Asset Lifecycle Management, BIM, Change, Data centric, Digital Enterprise, Digital Twin, MBD, MBE, MBM, MBSE, MDM, model-based, Platform, PLM | Tags: , , , , , , | 1 comment

This is my concluding post related to the various aspects of the model-driven enterprise. We went through Model-Based Systems Engineering (MBSE) where the focus was on using models (functional / logical / physical / simulations) to define complex product (systems). Next we discussed Model Based Definition / Model-Based Enterprise (MBD/MBE), where the focus was on data continuity between engineering and manufacturing by using the 3D Model as a master for design, manufacturing and eventually service information.

And last time we looked at the Digital Twin from its operational side, where the Digital Twin was applied for collecting and tuning physical assets in operation, which is not a typical PLM domain to my opinion.

Now we will focus on two areas where the Digital Twin touches aspects of PLM – the most challenging one and the most over-hyped areas I believe. These two areas are:

  • The Digital Twin used to virtually define and optimize a new product/system or even a system of systems. For example, defining a new production line.
  • The Digital Twin used to be the virtual replica of an asset in operation. For example, a turbine or engine.

Digital Twin to define a new Product/System

There might be some conceptual overlap if you compare the MBSE approach and the Digital Twin concept to define a new product or system to deliver. For me the differentiation would be that MBSE is used to master and define a complex system from the R&D point of view – unknown solution concepts – use hardware or software?  Unknown constraints to be refined and optimized in an iterative manner.

In the Digital Twin concept, it is more about a defining a system that should work in the field. How to combine various systems into a working solution and each of the systems has already a pre-defined set of behavioral / operational parameters, which could be 3D related but also performance related.

You would define and analyze the new solution virtual to discover the ideal solution for performance, costs, feasibility and maintenance. Working in the context of a virtual model might take more time than traditional ways of working, however once the models are in place analyzing the solution and optimizing it takes hours instead of weeks, assuming the virtual model is based on a digital thread, not a sequential process of creating and passing documents/files. Virtual solutions allow a company to optimize the solution upfront instead of costly fixing during delivery, commissioning and maintenance.

Why aren’t we doing this already? It takes more skilled engineers instead of cheaper fixers downstream. The fact that we are used to fixing it later is also an inhibitor for change. Management needs to trust and understand the economic value instead of trying to reduce the number of engineers as they are expensive and hard to plan.

In the construction industry, companies are discovering the power of BIM (Building Information Model) , introduced to enhance the efficiency and productivity of all stakeholders involved. Massive benefits can be achieved if the construction of the building and its future behavior and maintenance can be optimized virtually compared to fixing it in an expensive way in reality when issues pop up.

The same concept applies to process plants or manufacturing plants where you could virtually run the (manufacturing) process. If the design is done with all the behavior defined (hardware-in-the-loop simulation and software-in-the-loop) a solution has been virtually tested and rapidly delivered with no late discoveries and costly fixes.

Of course it requires new ways of working. Working with digital connected models is not what engineering learn during their education time – we have just started this journey. Therefore organizations should explore on a smaller scale how to create a full Digital Twin based on connected data – this is the ultimate base for the next purpose.

Digital Twin to match a product/system in the field

When you are after the topic of a Digital Twin through the materials provided by the various software vendors, you see all kinds of previews what is possible. Augmented Reality, Virtual Reality and more. All these presentations show that clicking somewhere in a 3D Model Space relevant information pops-up. Where does this relevant information come from?

Most of the time information is re-entered in a new environment, sometimes derived from CAD but all the metadata comes from people collecting and validating data. Not the type of work we promote for a modern digital enterprise. These inefficiencies are good for learning and demos but in a final stage a company cannot afford silos where data is collected and entered again disconnected from the source.

The main problem: Legacy PLM information is stored in documents (drawings / excels) and not intended to be shared downstream with full quality.
Read also: Why PLM is the forgotten domain in digital transformation.

If a company has already implemented an end-to-end Digital Twin to deliver the solution as described in the previous section, we can understand the data has been entered somewhere during the design and delivery process and thanks to a digital continuity it is there.

How many companies have done this already? For sure not the companies that are already a long time in business as their current silos and legacy processes do not cater for digital continuity. By appointing a Chief Digital Officer, the journey might start, the biggest risk the Chief Digital Officer will be running another silo in the organization.

So where does PLM support the concept of the Digital Twin operating in the field?

For me, the IoT part of the Digital Twin is not the core of a PLM. Defining the right sensors, controls and software are the first areas where IoT is used to define the measurable/controllable behavior of a Digital Twin. This topic has been discussed in the previous section.

The second part where PLM gets involved is twofold:

  • Processing data from an individual twin
  • Processing data from a collection of similar twins

Processing data from an individual twin

Data collected from an individual twin or collection of twins can be analyzed to extract or discover failure opportunities. An R&D organization is interested in learning what is happening in the field with their products. These analyses lead to better and more competitive solutions.

Predictive maintenance is not necessarily a part of that.  When you know that certain parts will fail between 10.000 and 20.000 operating hours, you want to optimize the moment of providing service to reduce downtime of the process and you do not want to replace parts way too early.


The R&D part related to predictive maintenance could be that R&D develops sensors inside this serviceable part that signal the need for maintenance in a much smaller time from – maintenance needed within 100 hours instead of a bandwidth of 10.000 hours. Or R&D could develop new parts that need less service and guarantee a longer up-time.

For an R&D department the information from an individual Digital Twin might be only relevant if the Physical Twin is complex to repair and downtime for each individual too high. Imagine a jet engine, a turbine in a power plant or similar. Here a Digital Twin will allow service and R&D to prepare maintenance and simulate and optimize the actions for the physical world before.

The five potential platforms of a digital enterprise

The second part where R&D will be interested in, is in the behavior of similar products/systems in the field combined with their environmental conditions. In this way, R&D can discover improvement points for the whole range and give incremental innovation. The challenge for this R&D organization is to find a logical placeholder in their PLM environment to collect commonalities related to the individual modules or components. This is not an ERP or MES domain.

Concepts of a logical product structure are already known in the oil & gas, process or nuclear industry and in 2017 I wrote about PLM for Owners/Operators mentioning Bjorn Fidjeland has always been active in this domain, you can find his concepts at plmPartner here  or as an eLearning course at SharePLM.

To conclude:

  • This post is way too long (sorry)
  • PLM is not dead – it evolves into one of the crucial platforms for the future – The Product Innovation Platform
  • Current BOM-centric approach within PLM is blocking progress to a full digital thread

More to come after the holidays (a European habit) with additional topics related to the digital enterprise

 

Model-Based – The Digital Twin

July 2, 2018 in Asset Lifecycle Management, Change, Data centric, Digital Enterprise, Digital Twin, IoT, MBD, MBE, MBSE, model-based, MRO, PLM | Tags: , , , | 3 comments

This is almost my last planned post related to the concepts of model-based. After having discussed Model-Based Systems Engineering (needed to develop complex products/systems including hardware and software) and Model-Based Definition (creating an efficient connection between Engineering and Manufacturing), my last post will be related to the most over-hyped topic: The Digital Twin

There are several reasons why the Digital Twin is overhyped. One of the reasons is that the Digital Twin is not necessarily considered as a PLM-related topic. Other vendors like SAP (the network of digital twins), Oracle (Digital Twins for IoT applications)  and GE with their Predix platform also contributed to the hype related to the digital twin. The other reason is that the concept of Digital Twin is an excellent idea for marketers to shine above the clouds. Monica Schnitger’s recent comment says it all in her post 5 quick takeaways from Siemens Automation summit. Monica’s takeaway related to Digital Twin:

The whole digital twin concept is just starting to gain traction with automation users. In many cases, they don’t have a digital representation of the equipment on their lines; they may have some data from the equipment OEM or their automation contractors but it’s inconsistent and probably incomplete. The consensus seemed to be that this is a great idea but out of many attendees’ immediate reach. [But it is important to start down this path: model something critical, gather all the data you can, prove benefit then move on to a bigger project.]

Monica is aiming to the same point I have been mentioning several times. There is no digital representation and the existing data is inconsistent. Don’t wait: The importance of accurate data – act now !

What is a digital twin?

I think there are various definitions of the digital twin, and I do not want to go into a definition debate like we had before with the acronyms MBD/MBE (Model Based Definition/Enterprise – the confusion) or even the acronym PLM (classical PLM or digital PLM ?). Let’s agree on the following high-level statements:

  • A digital twin is a virtual representation of a physical product
  • The virtual part of the digital twin is defined by what you want to analyze, simulate, and predict related to the physical product
  • One physical product can have multiple digital twins, but in the ideal world, there is potentially a unique digital twin for every physical product in the world
  • When a product interacts with the environment, based on inputs and outputs, we normally call it a system. When I use Product, it will most of the time be a System, in particular in the context of a digital twin

Given the above statements, I will give some examples of digital twin concepts:

As a cyclist, I am active on platforms like Garmin and Strava, using a tracking device, heart monitor and a power meter. During every ride, my device plus the sensors measure my performance, and all the data is uploaded to the platform, providing me with a report where I drove, how fast, my heartbeat, cadence and power during the ride. On Strava, I can see the Flybys (other digital twins that crossed my path and their performances), and I can see per segment how I performed compared to others, and I can filter by age, by level, etc.)

This is the easiest part of a digital twin. Every individual can monitor and analyze their personal behavior and discover trends. Additionally, the platform owner has all the intelligence about all cyclists worldwide, how they perform and what would be the best performance per location. And based on their Premium offering (where you pay), they can advise you on how to improve. The Strava business model brings value to the individual while learning from the behavior of thousands. Note that in this scenario, there is no 3D involved.

Another known digital twin story is related to plants in operation. In the past 10 years, I have advocated for Plant Lifecycle Management (PLM for Owner/Operators), describing the value of a virtual plant model using PLM capabilities combined with Maintenance, Repair and Overhaul (MRO) to reduce downtime. In a nuclear environment, the usage of 3D verification, simulation and even control software in a virtual environment can bring great benefit due to the fact that the physical twin is not always accessible, and downtime can be up to several million per week.

The above examples provide two types of digital twins. I will discuss some characteristics in the following paragraphs.

Digital Twin – performance focus

Companies like GE and SAP focus a lot on the digital twin in relation to asset performance. Measuring the performance of assets, comparing their performance with other similar assets and based on performance characteristics the collector of the data can sell predictive maintenance analysis, performance optimization guidance and potentially other value offerings to their customers.

Small improvements in the range of a few percent can significantly impact the overall net results. The digital twin is crucial in this business model to build-up knowledge, analyze and collect it and sell the knowledge again. This type of scenario is the easiest one. You need products with sensors, you need an infrastructure to collect the data and extract and process information in a manner that it can be linked to a behavior model with parameters that influence the model.

This is the model-based part of the digital twin. For a single product, different models can be related to the parameters driving your business. E.g., performance parameters for output, parameters for optimal up-time (preventive maintenance – usage optimization) or parameters related to environmental impact, etc..) Building and selling the results of such a model is an add-on business, creating more value for your customer, combined with creating more loyalty. Using the digital twin in the context of performance focus does not require a company to change the way they are working totally.  Yes, you need new skills, data collection and analysis, and more sensor technology, but many product development activities can remain the same (for the moment).

As a conclusion for this type of digital twin, I would state that yes, there is some PLM involved, but the main focus is on business execution.

Due to the fact that I already reach more than 1000 words, I will focus in my next post on the most relevant digital twin for PLM. Here, all disciplines come together. The 3D Mechanical model, the behavior models, the embedded and control software, (manufacturing simulation and more. This is to create an almost perfect virtual copy of a real product or system in the physical world. There, we will see that this is not as easy as concepts depend on accurate data and reliable models, which is not the case currently in most companies in their engineering environment.

 

Conclusion

Digital twins are marketing hype. However, when you focus on only performance monitoring and tuning, they become a reality as they do not require a company to align digitally across the whole lifecycle. However, this is just the beginning of a real digital twin.

Where are you in your company with the digital twin journey?

A PLM Update

June 17, 2018 in Change, Digital Enterprise, Education, Innovation, MBD, MBE, model-based, Observations, Platform, PLM | Tags: , , , , | Leave a comment

I was planning to complete the model-based series with a post related to the digital twin. However, I did not find the time to structure my thoughts to write it up in a structured story. Therefore, this time some topics I am working on that I would like to share.

Executive days at CADCAM Group

Last week I supported the executive days organized by the CADCAM Group in Ljubljana and Zagreb. The CADCAM is a large PLM Solution and Services Provider (60+ employees) in the region of South-East Europe with offices in Croatia, Slovenia, Serbia and Bosnia and Herzegovina. They are operating in a challenging region, four relative young countries with historically more an inside focus than a global focus. Many of CADCAM Group customers are in the automotive supply chain and to stay significant for the future they need to understand and develop a strategy that will help them to move forward.

My presentation was related to the learning path each company has to go through to understand the power of digital combined with the observation that current and future ways of working are not compatible therefore requiring a scaled and bimodal approach (see also PDT Europe further down this post).

This presentation matched nicely with Oscar Torres’s presentation related to strategy. You need to decide on the new things you are going to do, what to keep and what to stop. Sounds easy and of course the challenge is to define the what to start, stop and keep. There you need good insights into your current and future business.

Pierre Aumont completed the inspiring session by explaining how the automotive industry is being disrupted and it is not only Tesla. So many other companies are challenging the current status quo for the big automotive OEMs. Croatia has their innovator for electrical vehicles too, i.e. Rimac. Have a look here.

The presentations were followed by a (long) panel discussion. The common theme in both discussions is that companies need to educate and organize themselves to become educated for the future. New technologies, new ways of working need time and resources which small and medium enterprises often do not have. Therefore, universities, governments and interest groups are crucial.

A real challenge for countries that do not have an industrial innovation culture (yet).

CADCAM Group as a catalyst for these countries understands this need by organizing these executive days. Now the challenge is after these inspiring days to find the people and energy to follow-up.

Note: CADCAM Group graciously covered my expenses associated with my participation in these events but did not in any way influence the content of this paragraph.

 

The MBD/MBE discussion

In my earlier post, Model-Based: Connecting Engineering and Manufacturing,  I went deeper into the MBD/MBE topic and its potential benefits, closing with the request to readers to add their experiences and/or comments to MBD/MBE. Luckily there was one comment from Paul van der Ree, who had challenging experiences with MBD in the Netherlands. Together with Paul and a MBD-advocate (to be named) I will try to have discussion analyzing pro’s and con’s from all viewpoints and hopefully come to a common conclusion.

This to avoid that proponents and opponents of MBD just repeat their viewpoints without trying to converge. Joe Brouwer is famous for his opposition to MBD. Is he right or is he wrong I cannot say as there has never been a discussion. Click on the above image to see Joe’s latest post yourself. I plan to come back with a blog post related to the pro’s and con’s

 

The Death of PLM Consultancy

Early this year Oleg Shilovitsky and I had a blog debate related to the “Death of PLM Consultancy”. The discussion started here: The Death of PLM Consultancy ? and a follow-up post was PLM Consultants are still alive and have an exit strategy. It could have been an ongoing blog discussion for month where the value would be to get response from readers from our blogs.

Therefore I was very happy that MarketKey, the organizers behind the PLMx conferences in Europe and the US, agreed on a recorded discussion session during PLMx 2018 in Hamburg.  Paul Empringham was the moderator of this discussion with approx. 10 – 12 participants in the room to join the discussion. You can view the discussion here through this link: PLMx Hamburg debate

I want to thank MarketKey for their support and look forward to participating in their upcoming PLMx European event and if you cannot wait till next year, there is the upcoming PLMx conference in North America on November 5th and 6th – click on the image on the left to see the details.

 

 

PDT Europe call for papers

As you might have noticed I am a big supporter of the joint CIMdata/PDT Europe conference. This year the conference will be in Stuttgart on October 24th (PLM Roadmap) and October 25th (PDT).

I believe that this conference has a more “geeky” audience and goes into topics of PLM that require a good base understanding of what’s happening in the field. Not a conference for a newcomer in the world of PLM, more a conference for an experienced PLM person (inside a company or from the outside) that has experience challenging topics, like changing business processes, deciding on new standards, how to move to a modern digital business platform.

It was at these events where concepts as Model-Based were discussed in-depth, the need for Master Data Management, Industry standards for data exchange and two years ago the bimodal approach, also valid for PLM.

I hope to elaborate on experiences related to this bimodal or phased approach during the conference. If you or your company wants to contribute to this conference, please let the program committee know. There is already a good set of content planned. However, one or two inspiring presentations from the field are always welcome.
Click on this link to apply for your contribution

Conclusion

There is a lot on-going related to PLM as you can see. As I mentioned in the first topic it is about education and engagement. Be engaged and I am looking forward to your response and contribution in one or more of the topics discussed.

Model-Based – Connecting Engineering and Manufacturing

June 3, 2018 in Data centric, Digital Enterprise, MBD, MBE, MBM, model-based, PLM, Standards | Tags: , , | 1 comment

Model-based continued: Model-Based Definition

After a short celebration, 10 years blogging and 200 posts, now it is time to continue my series related to the future of model-based. So far my introduction and focus on the bigger picture of the term Model-Based has led to various reactions. In particular, related to Model-Based Definition, the topic I am going to discuss in this post. Probably this is the topic where opinions vary the most as it is more close to the classical engineering and manufacturing processes.

What is Model-Based Definition?

There are various definitions of the term Model-Based Definition. Often the term Model-Based Enterprise is used in the same context. Where some people might stop thinking because the terminology is not 100 % aligned, I propose to focus on content. Let’s investigate what it is.

In the classical product lifecycle, a product is first designed for its purpose based on specifications. The product can be simple, purely mechanical or more complex, requiring mechanical design, electronic components, and software to work together. For the first case, I will focus on Model-Based definition, for the second case I recommend to start reading about Model-Based Systems Engineering approaches where the mechanical design is part of a more complex system.

Model-Based Definition for Mechanical Designs – the role of 2D

Historically designs were done on the drawing board in 2D. After the introduction of 2D CAD and later affordable 3D CAD systems at the end of the previous century, companies made a shift from designing in 2D towards 3D.  The advantages were clear. A much better understanding of products. Reading a 2D drawing requires special skills and sometimes they were not unambiguous. Therefore, 3D CAD models lead to increased efficiency and quality combined with the potential to reuse and standardize parts or sub-assemblies in a design.

These benefits were not always observed as complementary to the design (the engineering point of view), there was still the need to describe and define how a product needs to be manufactured. The manufacturing definition remained in a set of 2D drawings, and the 2D Drawings were the legal authority describing the product.

An interesting side note observation:
You will still see in industrial machinery companies, a pure EBOM does not exist, as designs were made to target the manufacturing drawings, not the 3D Model, engineering focused, intent. In this type of companies, the discussion EBOM/MBOM is challenging to explain.

Once the 3D Model becomes the authority, the split between design and manufacturing information will create extra work if you keep on creating 2D drawings for manufacturing.  It requires non-value added extra work, i.e., reinterpreting 3D data in 2D formats (extra engineering hours) and there is the risk for new errors (interpretations/versioning issues). This non-value added engineering time can add up to over 30 percent of the time spent by engineering. You can find these numbers through the links below this post. I will not be the MBD teacher in this post, I will focus on the business impact.

Model-Based Definition based on 3D

3D PDF Model

The logical step is to use the 3D Model and add manufacturing information attached to the model, through different views.  This can be Geometric Dimensioning and Tolerancing information (GF&T), Quality measurement information, Assembly instructions and more, all applied to different views of the model.

 

Of course here you become dependent on the chosen environments that support the combination of a 3D CAD model combined with annotation views that can be selected in the context of the model. There are existing standards how to annotate a model, find your most practical standard to your industry / Eco-system. Next, most CAD vendors and PLM vendors have their proprietary 3D formats and when you stay within their solution range working with a model-based definition will bring direct benefits, however …..

Model-Based Definition data standards

Every company needs to be able to combine and share information internally with other teams or with partners and suppliers, so a single vendor solution is a utopia. Even if your company has standardized themselves to one system, the next acquisition might be disturbing this dream. Anticipating for openness is crucial and when you start working according to a model-based definition, make sure that at least you have import or export capabilities from within your environment towards model-based definition standards.

The two major standards for model-based definition are 3DPDF and AP242/JT based. Don’t expect these standards to be complete. They will give you a good foundation for your model-based journey and make sure you are part of this journey. (Listen to the CIMdata webinar also listed below)

The Model-Based journey

It took almost 20 years for 3D CAD to become the mainstream for mechanical design. Engineers are now trained in 3D and think in 3D. Now it is time to start the journey to abandon 2D and connect engineering, manufacturing and service more efficient. Similar gains can be expected. Follow the links below this article, here already a quote from an old post by Isha Gupta Ray (Capgemini) related to MBD:

MBE Drivers: The need for consumption of 3D product data by non-engineering departments and the elimination of 2D drawing related rework and costs are driving companies to adopt 3D MBE methods rapidly. DoD predicts that the move away from 2D Drawings and into open and free-to-view 3D MBE documents will reduce the cost of its internal engineering activities by up to 30%, reduce the scrap and rework it currently deals with from its supply channel by nearly 20% and improves supplier response times by up to 50%.

Conclusion

Model-Based Definition is not as challenging as becoming a Model-Driven enterprise, that I described in my introduction post to this theme. It is a first step to challenge or energize your company to become a digital enterprise, as sharing between engineering and manufacturing needs to be orchestrated, even with your external parties. It is easy to do nothing and to wait till your company is pushed or pushed out, which would cause extra stress (or relieve forever).  For me Model-Based Definition is a first (baby) step towards a digital enterprise, warming-up your company to change a look at your data in a different way. Next when you combine parameters and simulation to your models, you will make the next step towards a model-driven digital enterprise.

 

Below a selection of links related to the theme of Model-Based Definition. If you feel I missed some crucial links, please provide them through the comments section of this post, and I will add them to the post if relevant.

Tech-Clarity: The How-to Guide for Adopting Model Based Definition (MBD)

Action Engineering: Articles, Blog plus training

Engineering.com: How Model-Based Definition Can Fix Your CAD Models

Lifecycle Insights: Quantifying the value of Model-Based definitions

CIMdata: Webinar on Model-Based Definition and Standards

Capgemini: Model-Based Enterprise with 3D PDF

if you want to learn more in-depth the advanced usage and potential of MBD, try to understand:

CIMdata: Minimum MDB and BOM definition with STEP AP 242

PLM Celebrations

May 20, 2018 in Education, PLM | 4 comments

200-10This post is my two-hundredth blog post, and this week it is exactly ten years ago that I started blogging related to the topic of PLM.

The world was quite different at that time. Global connectivity started to become visible, digital transformation and digital twin were not a hype at that time. I remember 2008 as the years where I was advocating for PLM practices to be adopted by Small and Medium Enterprises (the initial goal of setting up this blog) and later to explain PLM practices to people in industries that were not even thinking about these terms (Engineering, Procurement, Construction companies, the construction industry in general and Owners/Operators of process plants (Nuclear, Energy, Chemical).

dialogueThe past 5 years you will recognize a shift more to the people side of PLM (what does PLM mean / impact my daily life/my organization), what makes sense/ nonsense of the new hypes mainly about the potential and risks related to becoming a digital enterprise. I learned and discussed these themes mostly through larger enterprises, as usually, they cannot change that fast. Therefore they have to be on the lookout for threats and trends earlier.

I did not expect 10 years ago to blog for such a long time and I do not expect to keep on blogging another 10 years. However, as the future cannot be predicted, for the moment I will continue based on observations and experiences from being in the field.

Conclusion

Below you find my first blog post from ten years ago. As you might discover after reading this post, the world of PLM is not changing fast or is it ? What is your opinion ?

Next post I will continue my series related to the term model-based.

 cropped-8years2.jpg

A Virtual Dutchman’s introduction
(May 22nd 2008)

Virtual Dutchman

Why Virtual ? This is my first post, and in the future, I will update you about my experiences in the world of PLM. Those of you not familiar with PLM I suggest searching for the definition on the web, and you will find many almost similar definitions – a neutral one you can find on Wikipedia. The main goal behind PLM is that by managing all steps of the product lifecycle from concept through development until even destruction, the company will be able to optimize and integrate all steps and information. This combined with best practices on how to develop, release and benefit from customer feedback will lead to higher revenues and a more competitive position for such a company.

Most of the PLM software companies provide their solutions around a 3D CAD system, as the 3D CAD model is the understandable representation of a product. Here we see the virtual products, and with analysis and simulation software we can test these products even before they are produced. Mobile phones undergo virtual crash tests; cars crash virtually and as I learned, even diapers are tested virtually.

Some PLM companies like Dassault Systèmes and Siemens UGS go even beyond the 3D CAD and integrate the whole manufacturing process initially through software to provide a virtual production process. This allows companies to fix (virtual) errors in the production process and the prototype even before a single product is manufactured in the real world. The time and costs savings of this virtualization allow companies to respond faster and better than their competitors. This change to define a complete virtual product and production process is costly and only affordable by the big enterprise, but for sure this trend will continue.

With the introduction of PLM 2.0, Dassault Systèmes even introduced another extension to PLM, the involvement of the customer, experiencing the virtual product before it even exists. The 2.0 version is a reference to WEB 2.0 bringing WEB content to be influenced by the consumer. In the same analogy, PLM 2.0  brings the world of product design to be influenced immediately by the customer, wherein the past customers only could review and select from existing products.

Look at the See What You Mean movie.

A virtual world seems to be a future trend, with possible virtual consumers. Currently, the trend to virtualization can be compared with teenage sex; they all talk about but …….

As a Dutchman working in the real world, I am targeting to become a virtual Dutchman. This allows me to experience things I have never done and dared before. But before reaching this goal, I will entertain you with my observations around PLM and look forward to real discussions.

image.png

 

Model-Based: Systems Engineering (MBSE)

May 6, 2018 in MBD, MBE, MBSE, model-based, PLM | Tags: , , | 3 comments

This is already my fourth post related to Model-Based concepts, which started with Model-Based – An Introduction. There are at least two more posts  to come depending on your feedback. The amount of posts also illustrates that the topic is not easy to explain through blog posts with a target length of 500-1000 words.

This combined with the observation that model-based in the context of PLM is quickly associated with replacing 2D Drawings by 3D annotated CAD models, or a marketing synonym for the classical interaction between a PDM-system and a CAD-system, see Model-Based – The Confusion, there is a lot to share.  I will come back to Model-Based Definition in an upcoming post. But now Model-Based Systems Engineering.

Systems Engineering

When you need to define a complex product, that has to interact in various ways in a safe manner with the outside world, like an airplane or a car, systems engineering is the recommended approach to define the product. In 2004, when I spoke at a generic PLM conference about the possibilities to extend SmarTeam with a system engineering data model:
(a Requirements/Functional/Logical decomposition connecting to the Product- RFLP) most engineers considered this as extra work. Too complex was the feedback. A specification document was enough most of the time as the base for a product to develop. Perhaps at that time these engineers were right. At that time most of their products were purely mechanical and served a single purpose.

Now almost 15 years later products have become complex due to the combination of electronic and software. And by adding software and sensors,  the product becomes a multi-purpose product, interacting with the outside world, a system.

If you want to dive deeper into an unambiguous explanation of systems engineering, follow this link to the INCOSE website.

INCOSE (International Council On Systems Engineering) is a not-for-profit membership organization founded to develop and disseminate the interdisciplinary principles and practices that enable the realization of successful systems.

There are a few points that I want you to remember from systems engineering approach.

First of all, it is an iterative approach, where you start with a high-level concept defining which functions are needed to full-fill the high-level requirement.

Then, by choosing for certain solutions concepts, you will have trade-off  studies during this phase to select the solution concept is defined. Which functions will be supported, what are the logical components needed for the solutions and what are the lower-level requirements for these components.

Trade-off studies eliminate alternatives and create the base for the final design which will be more and more detailed and specific over time. You need a functional and logical decomposition before jumping into the design phase for mechanical electrical and software components. Therefore, jumping from requirements directly into building a solution is not real systems engineering. You use this approach only if you already know the products solutions concept and logical components. Something perhaps possible when there is no involvement of electronics and software.

 Model-Based Systems Engineering

So what’s the difference between Systems Engineering and Model-Based Systems Engineering ?

As the addition of model-based already indicates, the process of systems engineering will be driven by using domain models to exchange information between engineers instead of documents. And more recently these models are also linked to simulations to define the best trade-off and decide on lower-level requirements.

In model-based systems engineering the most efficient way of working is to use parameters for requirements, logical and physical settings.  Next decide on lower-level requirements and constraints the concept “Design of Experiments” is used, where the performance of a product is simulated by varying several design parameters. The results of a Design of Experiment assist the engineering teams to select the optimized solution, of course based on the model used.

Model-Based Systems Engineering and PLM

As I mentioned in the introduction systems engineering was often a disconnected discipline from engineering. Systems Engineering defines the boundaries for the engineering department. In a modern digital enterprise, the target is to offer data continuity where systems engineering is connected. Incremental innovation in particular thanks to software will require an environment where multidisciplinary teams can collaborate in the most efficient way together.

Slide from CIMdata: positioning of MBx approaches

The above image from CIMdata concludes my post on model-based related to systems engineering. As you can see MBSE is situated at the front-end of the product lifecycle, however we have to realize that the modern product lifecycle is no longer linear but iterative (you can read more here: From a linear world to fast and circular)

Conclusion

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

 

 

Model-Based – The Confusion

April 22, 2018 in Blocking change, Change, Data centric, Digital Enterprise, MBD, MBE, MBM, MBSE, model-based, PLM | Tags: , , , , , | 6 comments

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)

Why Model-Based? The 3D CAD Model.

April 8, 2018 in Data centric, Digital Enterprise, model-based, PLM | Tags: , | 1 comment

I wrote in my previous posts about the various aspects of a model-based enterprise. In case you missed this post you can find it here: Model-Based an introduction. In this post, I will zoom in on the aspects related to the 3D model, probably in the context of PLM, the most anticipated approach.

3D CAD vs 3D CAD Model

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.

Model-Based Definition

We talk about Model-Based Definition when the product and manufacturing information is embedded/connected to the 3D CAD model, allowing the same source of information to be used downstream for manufacturing, analysis and inspection. The embedded information normally contains geometric dimensions, annotations, surface finish and material specifications. Instead of generating easy to distribute 2D drawings, you would be using the 3D model now with its embedded information.

According to an eBook, sponsored by SolidWorks and published by Tech-Clarity: “The How-to Guide for Adopting Model-Based Definition MBD”, Tech-Clarity’s research discovered that 33 percent of design time is spent on drawing generation. Imagine you do not need this time anymore to specify manufacturing processes and operations.  Does this mean the design activities can be reduced by 30 %? Probably not, the time could be used to spend on design alternatives too, at the end contributing to better designs.

Still, this is not the reason why companies would move to MBD. Companies that have implemented MBD report fewer manufacturing mistakes/less rework (61 %) – here is where the value becomes visible. In addition, improved communication with suppliers was reported by 50 % of the companies. More clarity in the communication, however as some of the suppliers are not used to MBD either, this excuse is used not to implement MBD. Instead of creating a win-win situation, a status-quo is created.

Read the eBook to demystify Model-Based Definition and realize that although it might look like a complex change, within 8 to 9 months the company might have gone through this change, assuming you have found the proper trainers/coaches for that.

When discussing a roadmap towards a digital enterprise, this is one of the “easier” steps to take as it does not force the organization to change their primary processes. They become more efficient, lean, and integrated, delivering rapid benefits within a year.

In the same context of MBD, in my post: Digital PLM requires a Model-Based Enterprise I referred to two articles in engineering.com written by Dick Bourke with the support from Jennifer Herron.  The first article: How Model-based Definition Can Fix Your CAD Models digs into more detail and provides additional insights into benefits realizable by implementing MBD. As I am not an expert, I would recommend if you agree on the benefits and necessity for your company’s future, find the right literature. There is a lot of information related to MBD coming from vendors but also vendor-neutral sources. Technology Is not the issue. You just have to study, digest, and implement it with your suppliers.

Beyond MDB using a 3D CAD Model

Although the post gets long, it is crucial to understand that the 3D CAD model should also be built in a more sophisticated manner. Using parameters in the model instead of hard-coded values allows the model to be used and interact with other disciplines in a digital manner.

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

The 3D CAD Model and Simulation

The last (short) part related to the 3D CAD Model is about its relation to simulation. If you do no use simulation together with your 3D CAD Models, you are still designing in the past. No real advantage between 2D and 3D, just better understanding?

In engineering, we often talk about Form, Fit and Function – the three dimensions to decide on a change.  With 2D (and 3D without simulation) we manage Form and Fit disconnected from Function. Once we use 3D combined with Simulation we are able to manage these three parameters in relation.

For example, when designing a product, the first simulations can provide direct feedback on shape and dimension constraints. Where to save material costs, choose from another design solution? The ultimate approach is Generative Design where the Functional constraints and the Fit are the given constraints and the Form is optimized based on artificial intelligence rules.

In case a company has a close relation between 3D Design and Simulation, the concept of Design of Experiments (DOE) will help to find the optimal product constraints. The more integrated the 3D CAD model and the simulation are, the more efficient alternatives can be evaluated and optimized.

Conclusion

In this post we focused on model-based in relation to the 3D CAD Model. Without going to the expert level for each of the topics discussed, I hope it creates interest and enthusiasm for further investment in model-based practices.  One commonality for all model-based practices: it is about parameters. Parameters provide digital continuity where each discipline (design, simulation, manufacturing) can build upon in almost real-time without the need for people to convert or adjust information. Digital Continuity – one of the characteristics of the future digital enterprise

 

 

 

 

 

 

 

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  2. Unknown's avatar
  3. Håkan Kårdén's avatar

    Jos, all interesting and relevant. There are additional elements to be mentioned and Ontologies seem to be one of the…

  4. Lewis Kennebrew's avatar

    Jos, as usual, you've provided a buffet of "food for thought". Where do you see AI being trained by a…

  5. Håkan Kårdén's avatar