You are currently browsing the tag archive for the ‘model-based’ tag.
After the first article discussing “The Future of PLM,” now again a post in the category of PLM and complementary practices/domains a topic that is already for a long time on the radar: Model-Based Definition, I am glad to catch up with Jennifer Herron, founder of Action Engineering, who is one of the thought leaders related to Model-Based Definition (MBD) and Model-Based Enterprise (MBE).
In 2016 I spoke with Jennifer after reading her book: “Re-Use Your CAD – The Model-Based CAD Handbook”. At that time, the discussion was initiated through two articles on Engineering.com. Action Engineering introduced OSCAR seven years later as the next step towards learning and understanding the benefits of Model-Based Definition.
Therefore, it is a perfect moment to catch up with Jennifer. Let’s start.
Model-Based Definition
Jennifer, first of all, can you bring some clarity in terminology. When I discussed the various model-based approaches, the first response I got was that model-based is all about 3D Models and that a lot of the TLA’s are just marketing terminology.
Can you clarify which parts of the model-based enterprise you focus on and with the proper TLA’s?
Model-Based means many things to many different viewpoints and systems of interest. All these perspectives lead us down many rabbit holes, and we are often left confused when first exposed to the big concepts of model-based.
At Action Engineering, we focus on Model-Based Definition (MBD), which uses and re-uses 3D data (CAD models) in design, fabrication, and inspection.
There are other model-based approaches, and the use of the word “model” is always a challenge to define within the proper context.
For MBD, a model is 3D CAD data that comes in both native and neutral formats
Another model-based approach is Model-Based Systems Engineering (MBSE). The term “model” in this context is a formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later lifecycle phases.
<Jos> I will come back on Model-Based Systems Engineering in future posts
Sometimes MBSE is about designing widgets, and often it is about representing the entire system and the business operations. For MBD, we often focus our education on the ASME Y14.47 definition that MBD is an annotated model and associated data elements that define the product without a drawing.
Model-Based Definition for Everybody?
I believe it took many years till 3D CAD design became a commodity; however, I still see the disconnected 2D drawing used to specify a product or part for manufacturing or suppliers. What are the benefits of model-based definition?
Are there companies that will not benefit from the model-based definition?
There’s no question that the manufacturing industry is addicted to their drawings. There are many reasons why, and yet mostly the problem is lack of awareness of how 3D CAD data can make design, fabrication, and inspection work easier.
For most, the person doing an inspection in the shipping and receiving department doesn’t have exposure to 3D data, and the only thing they have is a tabulated ERP database and maybe a drawing to read. If you plop down a 3D viewable that they can spin and zoom, they may not know how that relates to their job or what you want them to do differently.
Today’s approach of engineering championing MBD alone doesn’t work. To evolve information from the 2D drawing onto the 3D CAD model without engaging the stakeholders (machinists, assembly technicians, and inspectors) never yields a return on investment.
Organizations that succeed in transitioning to MBD are considering and incorporating all departments that touch the drawing today.
Incorporating all departments requires a vision from the management. Can you give some examples of companies that have transitioned to MBD, and what were the benefits they noticed?
I’ll give you an example of a small company with no First Article Inspection (FAI) regulatory requirements and a huge company with very rigorous FAI requirements.
Note: click on the images below to enjoy the details.
The small company instituted a system of CAD modeling discipline that allowed them to push 3D viewable information directly to the factory floor. The assembly technicians instantly understood engineering’s requirements faster and better.
The positive MBD messages for these use cases are 3D navigation, CAD Re-Use, and better control of their revisions on the factory floor.
The large company has added inspection requirements directly onto their engineering and created a Bill of Characteristics (BOC) for the suppliers and internal manufacturers. They are removing engineering ambiguity, resulting in direct digital information exchange between engineering, manufacturing, and quality siloes.
These practices have reduced error and reduced time to market.
The positive MBD messages for these use cases are unambiguous requirements capture by Engineering, Quality Traceability, and Model-Based PMI (Product and Manufacturing Information).
Model-Based Definition and PLM?
How do you see the relation between Model-Based Definition and PLM? Is a PLM system a complication or aid to implement a Model-Based Definition? And do you see a difference between the old and new PLM Vendors?
Model-Based Definition data is complex and rich in connected information, and we want it to be. With that amount of connected data, a data management system (beyond upload/download of documents) must keep all that data straight.
Depending on the size and function of an organization, a PLM may not be needed. However, a way to manage changes and collaboration amongst those using 3D data is necessary. Sometimes that results in a less sophisticated Product Data Management (PDM) system. Large organizations often require PLM.
There is significant resistance to doing MBD and PLM implementations simultaneously because PLM is always over budget and behind schedule. However, doing just MBD or just PLM without the other doesn’t work either. I think you should be brave and do both at once.
I think we can debate why PLM is always over budget and behind schedule. I hear the same about ERP implementations. Perhaps it has to deal with the fact that enterprise applications have to satisfy many users?
I believe that working with model versions and file versions can get mixed in larger organizations, so there is a need for PDM or PLM. Have you seen successful implementations of both interacting together?
Yes, the only successful MBD implementations are those that already have a matured PDM/PLM (scaled best to the individual business).
Model-Based Definition and Digital Transformation
In the previous question, we already touched on the challenge of old and modern PLM. How do you see the introduction of Model-Based Definition addressing the dreams of Industry 4.0, the Digital Twin and other digital concepts?
I just gave a presentation at the ASME Digital Twin Summit discussing the importance of MBD for the Digital Twin. MBD is a foundational element that allows engineering to compare their design requirements to the quality inspection results of digital twin data.
The feedback loop between Engineering and Quality is fraught with labor-intensive efforts in most businesses today.
Leveraging the combination of MBD and Digital Twin allows automation possibilities to speed up and increase the accuracy of the engineering to inspection feedback loop. That capability helps organizations realize the vision of Industry 4.0.
And then there is OSCAR.
I noticed you announced OSCAR. First, I thought OSCAR was a virtual aid for model-based definition, and I liked the launching page HERE. Can you tell us more about what makes OSCAR unique?
One thing that is hard with MBD implementation is there is so much to know. Our MBDers at Action Engineering have been involved with MBD for many years and with many companies. We are embedded in real-life transitions from using drawings to using models.
Suppose you start down the model-based path for digital manufacturing. In that case, there are significant investments in time to learn how to get to the right set of capabilities and the right implementation plan guided by a strategic focus. OSCAR reduces that ramp-up time with educational resources and provides vetted and repeatable methods for an MBD implementation.
OSCAR combines decades of Action Engineering expertise and lessons learned into a multi-media textbook of sorts. To kickstart an individual or an organization’s MBD journey, it includes asynchronous learning, downloadable resources, and CAD examples available in Creo, NX, and SOLIDWORKS formats.
CAD users can access how-to training and downloadable resources such as the latest edition of Re-Use Your CAD (RUYC). OSCAR enables process improvement champions to make their case to start the MBD journey. We add content regularly and post what’s new. Free trials are available to check out the online platform.
Learn more about what OSCAR is here:
Want to learn more?
In this post, I believe we only touched the tip of the iceberg. There is so much to learn and understand. What would you recommend to a reader of this blog who got interested?
RUYC (Re-Use Your CAD) is an excellent place to start, but if you need more audio-visual, and want to see real-life examples of MBD in action, get a Training subscription of OSCAR to get rooted in the vocabulary and benefits of MBD with a Model-Based Enterprise. Watch the videos multiple times! That’s what they are for. We love to work with European companies and would love to support you with a kickstart coaching package to get started.
What I learned
First of all, I learned that Jennifer is a very pragmatic person. Her company (Action Engineering) and her experience are a perfect pivot point for those who want to learn and understand more about Model-Based Definition. In particular, in the US, given her strong involvement in the American Society of Mechanical Engineers (ASME).
I am still curious if European or Asian counterparts exist to introduce and explain the benefits and usage of Model-Based Definition to their customers. Feel free to comment.
Next, and an important observation too, is the fact that Jennifer also describes the tension between Model-Based Definition and PLM. Current PLM systems might be too rigid to support end-to-end scenarios, taking benefit of the Model-Based definition.
I have to agree here. PLM Vendors mainly support their own MBD (model-based definition), where the ultimate purpose is to share all product-related information using various models as the main information carriers efficiently.
We have to study and solve a topic in the PLM domain, as I described in my technical highlights from the PLM Road Map & PDT Spring 2021 conference.
There is work to do!
Conclusion
Model-Based Definition is, for me, one of the must-do steps of a company to understand the model-based future. A model-based future sometimes incorporates Model-Based Systems Engineering, a real Digital Thread and one or more Digital Twins (depending on your company’s products).
It is a must-do activity because companies must transform themselves to depend on digital processes and digital continuity of data to remain competitive. Document-driven processes relying on the interpretation of a person are not sustainable.
One of my favorite conferences is the PLM Road Map & PDT conference. Probably because in the pre-COVID days, it was the best PLM conference to network with peers focusing on PLM practices, standards, and sustainability topics. Now the conference is virtual, and hopefully, after the pandemic, we will meet again in the conference space to elaborate on our experiences further.
Last year’s fall conference was special because we had three days filled with a generic PLM update and several A&D (Aerospace & Defense) working groups updates, reporting their progress and findings. Sessions related to the Multiview BOM 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.
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
After the series about “Learning from the past,” it is time to start looking toward the future. I learned from several discussions that I probably work most of the time with advanced companies. I believe this would motivate companies that lag behind even to look into the future even more.
If you look into the future for your company, you need new or better business outcomes. That should be the driver for your company. A company does not need PLM or a Digital Twin. A company might want to reduce its time to market and improve collaboration between all stakeholders. These objectives can be realized by different ways of working and an IT infrastructure to allow these processes to become digital and connected.
That is the “game”. Coming back to the future of PLM. We do not need a discussion about definitions; I leave this to the academics and vendors. We will see the same applies to the concept of a Digital Twin.
My statement: The digital twin is not new. Everybody can have their own digital twin as long as you interpret the definition differently. Does this sound like the PLM definition?
The definition
I like to follow the Gartner definition:
A digital twin is a digital representation of a real-world entity or system. The implementation of a digital twin is an encapsulated software object or model that mirrors a unique physical object, process, organization, person, or other abstraction. Data from multiple digital twins can be aggregated for a composite view across a number of real-world entities, such as a power plant or a city, and their related processes.
As you see, not a narrow definition. Now we will look at the different types of interpretations.
Single-purpose siloed Digital Twins
- Simple – data only
One of the most straightforward applications of a digital twin is, for example, my Garmin Connect environment. My device registers performance parameters (speed, cadence, power, heartbeat, location) when cycling. Then, after every trip, I can analyze my performance. I can see changes in my overall performance; compare my performance with others in my category (weight, age, sex).
Based on that, I can decide if I want to improve my performance. My personal business goal is to maintain and improve my overall performance, knowing I cannot stop aging by upgrading my body.
On November 4th, 2020, I am participating in the (almost virtual) Digital Twin conference organized by Bits&Chips in the Netherlands. In the context of human performance, I look forward to Natal van Riel’s presentation: Towards the metabolic digital twin – for sure, this direction is not simple. Natal is a full professor at the Technical University in Eindhoven, the “smart city” in the Netherlands.
- Medium – data and operating models
Many connected devices in the world use the same principle. An airplane engine, an industrial robot, a wind turbine, a medical device, and a train carriage; all track the performance based on this connection between physical and virtual, based on some sort of digital connectivity.
The business case here is also monitoring performance, predicting maintenance, and upgrading the product when needed.
This is the domain of Asset Lifecycle Management, a practice that has existed for decades. Based on financial and performance models, the optimal balance between maintaining and overhauling has to be found. Repairs are disruptive and can be extremely costly. A manufacturing site that cannot produce can cost millions per day. Connecting data between the physical and the virtual model allows us to have real-time insights and be proactive. It becomes a digital twin.
- Advanced – data and connected 3D model
The digital twin we see the most in marketing videos is a virtual twin, using a 3D representation for understanding and navigation. The 3D representation provides a Virtual Reality (VR) environment with connected data. When pointing at the virtual components, information might appear, or some animation might take place.
Building such a virtual representation is a significant effort; therefore, there needs to be a serious business case.
The simplest business case is to use the virtual twin for training purposes. A flight simulator provides a virtual environment and behavior as-if you are flying in a physical airplane – the behavior model behind the simulator should match as well as possibly the real behavior. However, as it is a model, it will never be 100 % reality and requires updates when new findings or product changes appear.
A virtual model of a platform or plant can be used for training on Standard Operating Procedures (SOPs). In the physical world, there is no place or time to conduct such training. Here the complexity might be lower. There is a 3D Model; however, serious updates can only be expected after a major maintenance or overhaul activity.
These practices are not new either and are used in places where physical training cannot be done.
More challenging is the Augmented Reality (AR) use case. Here the virtual model, most of the time, a lightweight 3D Model, connects to real-time data coming from other sources. For example, AR can be used when an engineer has to service a machine. The AR environment might project actual data from the machine, indicate service points and service procedures.
The positive side of the business case is clear for such an opportunity, ensuring service engineers always work with the right information in a real-time context. The main obstacle to implementing AR, in reality, is the access to data, the presentation of the data and keeping the data in the AR environment matching the reality.
And although there are 3D Models in use, they are, to my knowledge, always created in siloes, not yet connected to their design sources. Have a look at the Digital Twin conference from Bits&Chips, as mentioned before.
Several of the cases mentioned above will be discussed here. The conference’s target is to share real cases concluded by Q & A sessions, crucial for a virtual event.
Connected Virtual Twins along the product lifecycle
So far, we have been discussing the virtual twin concept, where we connect a product/system/person in the physical world to a virtual model. Now let us zoom in on the virtual twins relevant for the early parts of the product lifecycle, the manufacturing twin, and the development twin. This image from Siemens illustrates the concept:
On slides they imagine a complete integrated framework, which is the future vision. Let us first zoom in on the individual connected twins.
The digital production twin
This is the area of virtual manufacturing and creating a virtual model of the manufacturing plant. Virtual manufacturing planning is not a new topic. DELMIA (Dassault Systèmes) and Tecnomatix (Siemens) are already for a long time offering virtual manufacturing planning solutions.
At that time, the business case was based on the fact that the definition of a manufacturing plant and process done virtually allows you to optimize the plant before investing in physical assets.
Saving money as there is no costly prototype phase to optimize production. In a virtual world, you can perform many trade-off studies without extra costs. That was the past (and, for many companies, still the current situation).
With the need to be more flexible in manufacturing to address individual customer orders without increasing the overhead of delivering these customer-specific solutions, there is a need for a configurable plant that can produce these individual products (batch size 1).
This is where the virtual plant model comes into the picture again. Instead of having a virtual model to define the ultimate physical plant, now the virtual model remains an active model to propose and configure the production process for each of these individual products in the physical plant.
This is partly what Industry 4.0 is about. Using a model-based approach to configure the plant and its assets in a connected manner. The digital production twin drives the execution of the physical plant. The factory has to change from a static factory to a dynamic “smart” factory.
In the domain of Industry 4.0, companies are reporting progress. However, in my experience, the main challenge is still that the product source data is not yet built in a model-based, configurable manner. Therefore, requires manual rework. This is the area of Model-Based Definition, and I have been writing about this aspect several times. Latest post: Model-Based: Connecting Engineering and Manufacturing
The business case for this type of digital twin, of course, is to be able to customer-specific products with extremely competitive speed and reduced cost compared to standard. It could be your company’s survival strategy. As it is hard to predict the future, as we see from COVID-19, it is still crucial to anticipate the future instead of waiting.
The digital development twin
Before a product gets manufactured, there is a product development process. In the past, this was pure mechanical with some electronic components. Nowadays, many companies are actually manufacturing systems as the software controlling the product plays a significant role. In this context, the model-based systems engineering approach is the upcoming approach to defining and testing a system virtually before committing to the physical world.
Model-Based Systems Engineering can define a single complex product and perform all kinds of analyses on the system even before there is a physical system in place. I will explain more about model-based systems engineering in future posts. In this context, I want to stress that having a model-based system engineering environment combined with modularity (do not confuse it with model-based) is a solid foundation for dealing with unique custom products. Solutions can be configured and validated against their requirements already during the engineering phase.
The business case for the digital development twin is easy to make. Shorter time to market, improved and validated quality, and reduced engineering hours and costs compared to traditional ways of working. To achieve these results, for sure, you need to change your ways of working and the tools you are using. So it won’t be that easy!
For those interested in Industry 4.0 and the Model-Based System Engineering approach, join me at the upcoming PLM Road Map 2020 and PDT 2020 conference on 17-18-19 November. As you can see from the agenda, a lot of attention to the Digital Twin and Model-Based approaches.
Three digital half-days with hopefully a lot to learn and stay with our feet on the ground. In particular, I am looking forward to Marc Halpern’s keynote speech: Digital Thread: Be Careful What you Wish For, It Just Might Come True
Conclusion
It has been very noisy on the internet related to product features and technologies, probably due to COVID-19 and therefore disrupted interactions between all of us – vendors, implementers and companies trying to adjust their future. The Digital Twin concept is an excellent framing for a concept that everyone can relate to. Choose your business case and then look for the best matching twin.
To avoid that software geeks are getting curious about the title – in this context, ALM means Asset Lifecycle Management. In 2008 I was active for SmarTeam to promote PLM concepts relevant for Asset Lifecycle Management. The focus was on PLM being complementary to asset operation management (EAM Enterprise Asset Management and MRO – Maintenance Repair and Overhaul).
This topic has become actual for me in the past two months, having discussed and seen (PDT) the concepts of a model-based approach for assets and constructions. PLM, ALM, and BIM converge conceptually. Every year I give a one-day update from the field for students doing a master for PLM & BIM on top of their engineering/architectural background. Five years ago, there was no mentioning of BIM, now the ratio of BIM-oriented students has become significant. For me it is always great to see young students willing to learn PLM or BIM on top of their own skillset. Read more about this particular Master class in French when you click on the logo to the left.
In 2012 I started to explain PLM benefits to EPC companies (Engineering Procurement Construction), targeting a more profitable and efficient delivery of their constructions (oil platform, plant, building, infrastructure). The simplified reasoning behind using PLM was related to a more efficient and quality of multidisciplinary collaboration, reducing costly fixes during construction, and smoothening the intensive process of data handover.
More and more in the process industry, standards, like ISO 15926 (Process Industry) and ISO 19650 (BIM – mainly in the UK), became crucial. At that time, it was difficult to convince companies to focus on the horizontal-integrated process instead of dedicated, disconnected tools. Meanwhile, this has changed, thanks to the Digital Twin hype. Let’s have a look.
PLM and ALM
The initial value for using PLM concepts complementary to MRO systems came from the fact that MRO systems are mainly focusing on plant operations. You could compare these systems with ERP systems for manufacturing companies, focusing execution and continuous operation. Scheduled maintenance and inspections are also driven by the MRO system. Typical MRO systems are Maximo and SAP PM. PLM could deliver configuration management, linking the design intent to the physical implementation. Therefore provide higher data quality, visibility, and traceability of the asset history.
The SmarTeam data model for Asset Lifecycle Management
In 2010, I shared these concepts in two posts: Asset Lifecycle Management using a PLM-system and PLM for Asset Lifecycle Management and Asset Development based on lessons learned with some (nuclear) plant owner/operators. They started to discover the need for configuration management to ensure data quality for operations. In 2010-2014 the business case using PLM complementary to MRO was data quality and therefore reduced down-time when executing large maintenance programs (dependencies between the individual projects were not visible without PLM)
In MRO-systems, like in ERP-systems, the data for execution is based on information coming from various engineering sources – specifications, PFDs, P&IDs. Questions owner/operators ask themselves are:
- What are the designed operational settings?
- Are the asset parameters currently running as designed?
- What is the optimized maintenance period?
- Can we stretch maintenance intervals?
- Can we reduce inspections?
- Can we reduce downtime for maintenance and overhaul?
- What about predictive maintenance?
Most of these questions are answered by experts that use their tacit knowledge and experience to give the best so far answers. And when the answers were wrong, they were accepted as new learning points. Next time we won’t make this mistake, and the experts become even more knowledgeable.
Now, these questions could be answered if you can model your asset in a virtual environment. In the virtual world, you would use simulation models, logical models, and 3D Models to describe the asset. This is where Model-Based Systems Engineering practices are used. However, these models need to be calibrated based on reality. And that is where IoT and Asset Operation Monitoring comes in connecting physical behavior with virtual predicted behavior. You can read more about this relationship in my post: Will MBSE the new PLM instead of IoT?
PLM and BIM
In 2014 when I started to discuss PLM concepts with EPC-companies (Engineering, Procurement, and Construction), mainly in the Oil & Gas industry. Here excellent asset development tools (AVEVA, Intergraph, Bentley) are the standard, and as the purpose of an EPC company is to deliver a plant or platform. Each software tool has its purpose and there is no lifecycle strategy. The value PLM could bring was providing a program overview (complementary with Primavera), standardization, multidisciplinary coordination and visibility across projects to capture knowledge.
Most of the time, the EPC companies did not see the value of optimizing themselves as this was accepted in the process. Even while their productivity and cost due to poor quality (fixing during construction /commissioning) were absurd (10-20 % of the project budget). Cultural change – think longer instead of fix later – was hard to explain. In the end, the EPC was not responsible for operations, so why bother that much?
My blog posts: PLM for all Industries and 2014 – the year that the construction industry did not discover PLM illustrate the challenge at that time. None of the EPCs and construction companies had the, that improving collaboration based on information-continuity (not data-driven yet) could bring the significant benefits, despite their relatively low-profit margin (1- 3 % is considered excellent). Breaking the silos is too.
Two recent trends, however, changed the status quo that existed.
First of all, more and more, the owner/operator does not want to be responsible for the maintenance and operations of the asset. The typical EPC-companies now became DBO-companies (Design Build and Operate), this requires lifecycle thinking for these companies as most of the costs of an asset are during its maintenance and operation phase.
Advanced Thinking (read: (Model-Based) Systems Engineering) can help these companies to shift their focus on a more sustainable design of the asset for the future and get rewarded for that. In the old EPC-model, the target was “just” to deliver as specified.
A second significant trend is the availability of cloud infrastructure for the construction world. A cloud infrastructure does not require considerable investment for the stakeholders in a construction project. By introducing BIM in a common data environment (CDE), a comparable infrastructure to PLM is created and likely the Maintenance-and-Operatie stakeholder is eager to have the full virtual definition here for the future.
Read more about BIM and CDE for example, here: CDE – strategic BIM process tool.
Of course, technology and standards are there to collaborate. Now it is up to the stakeholders involved to develop new skills for collaboration (learn or hire) and implement them through new ways of working. A learning process can never be pushed by a big-bang, so make sure your company operates in two modes while learning.
As I mentioned the Maintenance-and-Operate stakeholders or in traditional cases, the Owner/Operators are incredibly interested in a well-defined virtual model of the asset. This allows them to analyze and simulate the implementation of fixes and enhancements for the future with an optimum result. Again we are talking about a digital twin of the asset here
Conclusion
Even though the digital twin is on the top of the Gartner Hype cycle, it has become already a vital principle to implement in particular for substantial, critical assets. As these precious assets, minor inefficiencies in data continuity can still be afforded to learn. From the moment companies have established a digital continuity between their virtual and physical assets, the concept for Digital Twin can also be profitable (and required) for other industries. In particular when these companies want to deliver their products as a service.
Note: I have been talking this year a lot about the challenges of digital transformation applied to PLM in particular. During PI PLMx London 2020 on February 3 and 4, I will lead a Think Thank session related to the challenge of connecting your PLM transformation to your executives’ vision (and budget). See you there ?
Last week I shared the first impression from my favorite conference, the PLM Roadmap / PDT conference organized by CIMdata and Eurostep. You can read some of the highlights here: The weekend after PLM Roadmap / PDT 2019 Day 1.
Click on the logo to see what was the full agenda. In this post, I will focus on some of the highlights of day 2.
Chernobyl, The megaproject with the New Arch
Christophe Portenseigne from the Bouygues Construction Group shared with us his personal story about this megaproject, called Novarka. 33 years ago, reactor #4 exploded and has been confined with an object shelter within six months in 1986. This was done with heroic speed, and it was anticipated that the shelter would only last for 20 – 30 years. You can read about this project here.
The Novarka project was about creating a shelter for Confinement of the radioactive dust and protection of the existing against external actions (wind, water, snow…) for the next 100 years!
And even necessary, the inside the arch would be a plant where people could work safely on the process of decommissioning the existing contaminated structures. You can read about the full project here at the Novarka website.
What impressed me the most the personal stories of Christophe taking us through some of the massive challenges that need to be solved with innovative thinking. High complexity, a vast number of requirements, many parties, stakeholders involved closed in June 2019. As Christophe mentioned, this was a project to be proud of as it creates a kind of optimism that no matter how big the challenges are, with human ingenuity and effort, we can solve them.
A Model Factory for the Efficient Development of High Performing Vehicles
Eric Landel, expert leader for Numerical Modeling and Simulation at Renault, gave us an interesting insight into an aspect of digitalization that has become very valuable, the connection between design and simulation to develop products, in this case, the Renault CLIO V, as much as possible in the virtual world. You need excellent simulation models to match future reality (and tests). The target of simulation was to get the highest safety test results in the Europe NCAP rating – 5 stars.
The Renault modeling factory implemented a digital loop (below) to ensure that at the end of the design/simulation, a robust design would exist. Eric mentioned that for the Clio, they did not build a prototype anymore. The first physical tests were done on cars coming from the plant. Despite the investment in simulation software, a considerable saving in crash part over cost before TGA (Tooling Go Ahead).
Combined with the savings, the process has been much faster than before. From 10 weeks for a simulation loop towards 4 weeks. The next target is to reduce this time to 1 week. A real example of digitization and a connected model-based approach.
From virtual prototype to hybrid twin
ESI – their sponsor session Evolving from Virtual Prototype Testing to Hybrid Twin: Challenges & Benefits was an excellent complementary session to the presentation from Renault
PLM, MBSE and Supply chain – challenges and opportunities
Nigel Shaw’s presentation was one of my favorite presentations, as Nigel addressed the same topics that I have been discussing in the past years. His focus was on collaboration between the OEM and supplier with the various aspects of requirements management, configuration management, simulation and the different speeds of PLM (focus on mechanical) and ALM (focus on software)
How can such activities work in a digitally-connected environment instead of a document-based approach? Nigel looked into the various aspects of existing standards in their domains and their future. There is a direction to MBE (Model-Based Everything) but still topics to consider. See below:
I agree with Nigel – the future is model-based – when will be the issue for the market leaders.
The ISO AP239 ed3 Project and the Through Life Cycle Interoperability Challenge
Yves Baudier from AFNET, a reference association in France regarding industry digitation, digital threads, and digital processes for Extended Enterprise/Supply chain. All about a digital future and Yves presentation was about the interoperability challenge, mentioning three of my favorite points to consider:
- Data becoming more and more a strategic asset – as digitalization of Industry and Services, new services enabled by data analytics
- All engineering domains (from concept design to system end of life) need to develop a data-centric approach (not only model-centric)– An opportunity for PLM to cover the full life-cycle
- Effectivity and efficiency of data interoperability through the life-cycle is now an essential industry requirement – e.g., “virtual product” and “digital twin” concepts
All the points are crucial for the domain of PLM.
In that context, Yves discussed the evolution of the ISO 10303-239 standard, also known as PLCS. The target with ISO AP239 ed3 is to become the standard for Aerospace and Defense for the full product lifecycle and through this convergence being able to push IT/PLM Vendors to comply – crucial for a digital enterprise
Time for the construction / civil industry
Christophe Castaing, director of digital engineering at Egis, shared with us their solution framework to manage large infrastructure projects by focusing on both the Asset Information (BIM-based) and the collaborative processes between the stakeholders, all based on standards. It was a broad and in-depth presentation – too much to share in a blog post. To conclude (see also Christophe’s slide below) in the construction industry more and more, there is the desire to have a digital twin of a given asset (building/construction), creating the need for standard information models.
Pierre Benning, IT director from Bouygues Public Works gave us an update on the MINnD project. MINnD standing for Modeling INteroperable INformation for sustainable INfrastructures in xD, a French research project dedicated to the deployment of BIM and digital engineering in the infrastructure sector. Where BIM has been starting from the construction industry, there is a need for a similar, digital modeling approach for civil infrastructure. In 2014 Christophe Castaing already reported the activities of the MINnD project – see The weekend after PDT 2014. Now Pierre was updating us on what are the activities for MINnD Season 2 – see below:
As you can see, again, the interest in digital twins for operations and maintenance. Perhaps here, the civil infrastructure industry will be faster than traditional industries because of its enormous value. BIM and GIS reconciliation is a precise topic as many civil infrastructures have a GIS aspect – Road/Train infrastructure for example. The third bullet is evident to me. With digitization and the integration of contractors and suppliers, BIM and PLM will be more-and-more conceptual alike. The big difference still at this moment: BIM has one standard framework where PLM-standards are still not in a consolidation stage.
Digital Transformation for PLM is not an evolution
If you have been following my blog in the past two years, you may have noticed that I am exploring ways to solve the transition from traditional, coordinated PLM processes towards future, connected PLM. In this session, I shared with the audience that digital transformation is disruptive for PLM and requires thinking in two modes.
Thinking in two modes is not what people like, however, organizations can run in two modes. Also, I shared some examples from digital transformation stories that illustrate there was no transformation, either failure or smoke, and mirrors. You can download my presentation via SlideShare here.
Fireplace discussion: Bringing all the Trends Together, What’s next
We closed the day and the conference with a fireplace chat moderated by Dr. Ken Versprille from CIMdata, where we discussed, among other things, the increasing complexity of products and products as a service. We have seen during the sessions from BAE Systems Maritime and Bouygues Construction Group that we can do complex projects, however, when there are competition and time to deliver pressure, we do not manage the project so much, we try to contain the potential risk. It was an interactive fireplace giving us enough thoughts for next year.
Conclusion
Nothing to add to Håkan Kårdén’s closing tweet – I hope to see you next year.
The usage of standards has been a recurring topic the past 10 months, probably came back to the surface at PI PLMx Chicago during the PLM Leaders panel discussion. If you want to refresh the debate, Oleg Shilovitsky posted an overview: What vendors are thinking about PLM standards – Aras, Dassault Systemes, Onshape, Oracle PLM, Propel PLM, SAP, Siemens PLM.
It is clear for vendors when they would actively support standards they reduce their competitive advantage, after all, you are opening your systems to connect to other vendor solutions, reducing the chance to sell adjacent functionality. We call it vendor lock-in. If you think this approach only counts for PLM, I would suggest you open your Apple (iPhone) and think about vendor lock-in for a moment.
Vendors will only adhere to standards when pushed by their customers, and that is why we have a wide variety of standards in the engineering domain.
Take the example of JT as a standard viewing format, heavily pushed by Siemens for the German automotive industry to be able to work downstream with CATIA and NX models. There was a JT-version (v9.5) that reached ISO 1306 alignment, but after that, Siemens changed JT (v10) again to optimize their own exchange scenarios, and the standard was lost.
And as customers did not complain (too much), the divergence continued. So it clear vendors will not maintain standards out of charity as your business does not work for charity either (or do you ?). So I do not blame them is there is no push from their customers to maintain them.
What about standards?
The discussion related to standards flared up around the IpX ConX19 conference and a debate between Oleg & Hakan Kardan (EuroSTEP) where Hakan suggested that PLCS could be a standard data model for the digital thread – you can read Oleg’s view here: Do we need a standard like PLCS to build a digital thread.
Oleg’s opening sentence made me immediately stop reading further as more and more I am tired of this type of framing if you want to do a serious discussion based on arguments. Such a statement is called framing and in particular in politics we see the bad examples of framing.
Standards are like toothbrushes, a good idea, but no one wants to use anyone else’s. The history of engineering and manufacturing software is full of stories about standards.
This opening sentence says all about the mindset related to standards – it is a one-liner – not a fact. It could have been a tweet in this society of experts.
Still later,I read the blog post and learned Oleg has no arguments to depreciate PLCS, however as he does not know the details, he will probably not use it. The main challenge of standards: you need to spend time to understand and adhere to them and agree on following them. Otherwise, you get the same diversion of JT again or similar examples.
However, I might have been wrong in my conclusion as Oleg did some thinking on a Sunday and came with an excellent post: What would happen if PLM Vendors agree about data standards. Here Oleg is making the comparison with a standard in the digital world, established by Google, Microsoft, Yahoo, and Yandex : Schema.org: Evolution of Structured Data on the Web.
There is a need for semantic mapping and understanding in the day-to-day-world, and this understanding makes you realize the same is needed for PLM. That was one of the reasons why I wrote in the past (2015) a series of posts related to the importance of a PLM data model:
All these posts were aimed to help companies and implementers to make the right choices for an item-centric PLM implementation. At that time – 2015, item-centric was the current PLM best practice. I learned from my engagements in the past 15 years, in particular when you have a flexible modeling tool like SmarTeam or nowadays Aras, making the right data model decisions are crucial for future growth.
Who needs standards?
First of all, as long as you stay in your controlled environment, you do not need standards. In particular, in the Aerospace and Automotive industry, the OEMs defined the software versions to be used, and the supply chain had to adhere to their chosen formats. Even this narrow definition was not complete enough as a 3D CAD model needed to be exported for simulation or manufacturing purposes. There was not a single vendor working on a single CAD model definition at that time. So the need for standards emerged as there was a need to exchange data.
Data exchange is the driving force behind standards.
In a second stage also neutral format data storage became an important point – how to save for 75 years an aircraft definition.
Oil & Gas / Building – Construction
These two industries both had the need for standards. The Oil & Gas industry relies on EPC (Engineering / Procurement / Construction) companies that build plants or platforms. Then the owner/operator takes over the operation and needs a hand-over of all the relevant information. However if this information would be delivered in the application-specific formats the EPC companies have used, the owner/operator would require various software environments and skills, just to have access to the data.
Therefore if the data is delivered in a standard format (ISO 15926) and the exchange follows CFIHOS (Capital Facilities Information Hand Over Specification) this exchange can be done more automated between the EPC and Owner/Operator environment, leading to lower overall cost of delivering and maintaining the information combined with a higher quality. For that reason, the Oil & Gas industry has invested already for a long time in standards as their plants/platform have a long lifecycle.
And the same is happening in the construction industry. Initially Autodesk and Bentley were fighting to become the vendor-standard and ultimately the IFC-standard has taken a lot from the Autodesk-world, but has become a neutral standard for all parties involved in a construction project to share and exchange data. In particular for the construction industry, the cloud has been an accelerator for collaboration.
So standards are needed where companies/people exchange information
For the same reason in most global companies, English became the standard language. If you needed to learn all the languages spoken in a worldwide organization, you would not have time for business. Therefore everyone making some effort to communicate in one standard language is the best way to operate.
And this is the same for a future data-driven environment – we cannot afford for every exchange to go to the native format from the receiver or source – common neutral (or winning) standards will ultimately also come up in the world of manufacturing data exchange and IoT.
Companies need to push
This is probably the blocking issue for standards. Developing standards, using standards require an effort without immediate ROI. So why not use vendor-formats/models and create custom point-to-point interface as we only need one or two interfaces? Companies delivering products with a long lifecycle know that the current data formats are not guaranteed for the future, so they push for standards (aerospace/defense/ oil & gas/construction/ infrastructure).
3D PDF Model
Other companies are looking for short term results, and standards are slowing them down. However as soon as they need to exchange data with their Eco-system (suppliers/ customers) an existing standard will make their business more scalable. The lack of standards is one of the inhibitors for Model-Based Definition or the Model-Based Enterprise – see also my post on this topic: Model-Based – Connecting Engineering and Manufacturing
When we would imagine the Digital Enterprise of the future, information will be connected through data streams and models. In a digital enterprise file conversions and proprietary formats will impede the flow of data and create non-value added work. For example if we look to current “Digital Twin” concepts, the 3D-representation of the twin is recreated again instead of a neutral 3D-model continuity. This because companies currently work in a coordinated manner. In perhaps 10 years from now we will reach maturity of a model-based enterprise, which only can exist based on standards. If the standards are based on one dominating platform or based on a merger of standards will be the question.
To discuss this question and how to bridge from the past to the future I am looking forward meeting you at the upcoming PLM Roadmap & PDT 2019 EMEA conference on 13-14 November in Paris, France. Download the program here: PLM for Professionals – Product Lifecycle Innovation
Conclusion
I believe PLM Standards will emerge when building and optimizing a digital enterprise. We need to keep on pushing and actively working for meaningful standards as they are crucial to avoid a lock-in of your data. Potentially creating dead-ends and massive inefficiencies. The future is about connected Eco-systems, and the leanest companies will survive. Standards do not need to be extraordinarily well-defined and can start from a high-level alignment as we saw from schema.org. Keep on investing and contributing to standards and related discussion to create a shared learning path.
Thanks Oleg Shilovitsky to keep the topic alive.
p.s. I had not time to read and process your PLM Data Commodizitation post
In my previous post, the PLM blame game, I briefly mentioned that there are two delivery models for PLM. One approach based on a PLM system, that contains predefined business logic and functionality, promoting to use the system as much as possible out-of-the-box (OOTB) somehow driving toward a certain rigidness or the other approach where the PLM capabilities need to be developed on top of a customizable infrastructure, providing more flexibility. I believe there has been a debate about this topic over more than 15 years without a decisive conclusion. Therefore I will take you through the pros and cons of both approaches illustrated by examples from the field.
PLM started as a toolkit
The initial cPDM/PLM systems were toolkits for several reasons. In the early days, scalable connectivity was not available or way too expensive for a standard collaboration approach. Engineering information, mostly design files, needed to be shared globally in an efficient manner, and the PLM backbone was often a centralized repository for CAD-data. Bill of Materials handling in PLM was often at a basic level, as either the ERP-system (mostly Aerospace/Defense) or home-grown developed BOM-systems(Automotive) were in place for manufacturing.
Depending on the business needs of the company, the target was too connect as much as possible engineering data sources to the PLM backbone – PLM originated from engineering and is still considered by many people as an engineering solution. For connectivity interfaces and integrations needed to be developed in a time that application integration frameworks were primitive and complicated. This made PLM implementations complex and expensive, so only the large automotive and aerospace/defense companies could afford to invest in such systems. And a lot of tuition fees spent to achieve results. Many of these environments are still operational as they became too risky to touch, as I described in my post: The PLM Migration Dilemma.
The birth of OOTB
Around the year 2000, there was the first development of OOTB PLM. There was Agile (later acquired by Oracle) focusing on the high-tech and medical industry. Instead of document management, they focused on the scenario from bringing the BOM from engineering to manufacturing based on a relatively fixed scenario – therefore fast to implement and fast to validate. The last point, in particular, is crucial in regulated medical environments.
At that time, I was working with SmarTeam on the development of templates for various industries, with a similar mindset. A predefined template would lead to faster implementations and therefore reducing the implementation costs. The challenge with SmarTeam, however, was that is was very easy to customize, based on Microsoft technology and wizards for data modeling and UI design.
This was not a benefit for OOTB-delivery as SmarTeam was implemented through Value Added Resellers, and their major revenue came from providing services to their customers. So it was easy to reprogram the concepts of the templates and use them as your unique selling points towards a customer. A similar situation is now happening with Aras – the primary implementation skills are at the implementing companies, and their revenue does not come from software (maintenance).
The result is that each implementer considers another implementer as a competitor and they are not willing to give up their IP to the software company.
SmarTeam resellers were not eager to deliver their IP back to SmarTeam to get it embedded in the product as it would reduce their unique selling points. I assume the same happens currently in the Aras channel – it might be called Open Source however probably it is only high-level infrastructure.
Around 2006 many of the main PLM-vendors had their various mid-market offerings, and I contributed at that time to the SmarTeam Engineering Express – a preconfigured solution that was rapid to implement if you wanted.
Although the SmarTeam Engineering Express was an excellent sales tool, the resellers that started to implement the software began to customize the environment as fast as possible in their own preferred manner. For two reasons: the customer most of the time had different current practices and secondly the money come from services. So why say No to a customer if you can say Yes?
OOTB and modules
Initially, for the leading PLM Vendors, their mid-market templates were not just aiming at the mid-market. All companies wanted to have a standardized PLM-system with as little as possible customizations. This meant for the PLM vendors that they had to package their functionality into modules, sometimes addressing industry-specific capabilities, sometimes areas of interfaces (CAD and ERP integrations) as a module or generic governance capabilities like portfolio management, project management, and change management.
The principles behind the modules were that they need to deliver data model capabilities combined with business logic/behavior. Otherwise, the value of the module would be not relevant. And this causes a challenge. The more business logic a module delivers, the more the company that implements the module needs to adapt to more generic practices. This requires business change management, people need to be motivated to work differently. And who is eager to make people work differently? Almost nobody, as it is an intensive coaching job that cannot be done by the vendors (they sell software), often cannot be done by the implementers (they do not have the broad set of skills needed) or by the companies (they do not have the free resources for that). Precisely the principles behind the PLM Blame Game.
OOTB modularity advantages
The first advantage of modularity in the PLM software is that you only buy the software pieces that you really need. However, most companies do not see PLM as a journey, so they agree on a budget to start, and then every module that was not identified before becomes a cost issue. Main reason because the implementation teams focus on delivering capabilities at that stage, not at providing value-based metrics.
The second potential advantage of PLM modularity is the fact that these modules supposed to be complementary to the other modules as they should have been developed in the context of each other. In reality, this is not always the case. Yes, the modules fit nicely on a single PowerPoint slide, however, when it comes to reality, there are separate systems with a minimum of integration with the core. However, the advantage is that the PLM software provider now becomes responsible for upgradability or extendibility of the provided functionality, which is a serious point to consider.
The third advantage from the OOTB modular approach is that it forces the PLM vendor to invest in your industry and future needed capabilities, for example, digital twins, AR/VR, and model-based ways of working. Some skeptic people might say PLM vendors create problems to solve that do not exist yet, optimists might say they invest in imagining the future, which can only happen by trial-and-error. In a digital enterprise, it is: think big, start small, fail fast, and scale quickly.
OOTB modularity disadvantages
Most of the OOTB modularity disadvantages will be advantages in the toolkit approach, therefore discussed in the next paragraph. One downside from the OOTB modular approach is the disconnect between the people developing the modules and the implementers in the field. Often modules are developed based on some leading customer experiences (the big ones), where the majority of usage in the field is targeting smaller companies where people have multiple roles, the typical SMB approach. SMB implementations are often not visible at the PLM Vendor R&D level as they are hidden through the Value Added Reseller network and/or usually too small to become apparent.
Toolkit advantages
The most significant advantage of a PLM toolkit approach is that the implementation can be a journey. Starting with a clear business need, for example in modern PLM, create a digital thread and then once this is achieved dive deeper in areas of the lifecycle that require improvement. And increased functionality is only linked to the number of users, not to extra costs for a new module.
However, if the development of additional functionality becomes massive, you have the risk that low license costs are nullified by development costs.
The second advantage of a PLM toolkit approach is that the implementer and users will have a better relationship in delivering capabilities and therefore, a higher chance of acceptance. The implementer builds what the customer is asking for.
However, as Henry Ford said, if I would ask my customers what they wanted, they would ask for faster horses.
Toolkit considerations
There are several points where a PLM toolkit can be an advantage but also a disadvantage, very much depending on various characteristics of your company and your implementation team. Let’s review some of them:
Innovative: a toolkit does not provide an innovative way of working immediately. The toolkit can have an infrastructure to deliver innovative capabilities, even as small demonstrations, the implementation, and methodology to implement this innovative way of working needs to come from either your company’s resources or your implementer’s skills.
Uniqueness: with a toolkit approach, you can build a unique PLM infrastructure that makes you more competitive than the other. Don’t share your IP and best practices to be more competitive. This approach can be valid if you truly have a competing plan here. Otherwise, the risk might be you are creating a legacy for your company that will slow you down later in time.
Performance: this is a crucial topic if you want to scale your solution to the enterprise level. I spent a lot of time in the past analyzing and supporting SmarTeam implementers and template developers on their journey to optimize their solutions. Choosing the right algorithms, the right data modeling choices are crucial.
Sometimes I came into a situation where the customer blamed SmarTeam because customizations were possible – you can read about this example in an old LinkedIn post: the importance of a PLM data model
Experience: When you plan to implement PLM “big” with a toolkit approach, experience becomes crucial as initial design decisions and scope are significant for future extensions and maintainability. Beautiful implementations can become a burden after five years as design decisions were not documented or analyzed. Having experience or an experienced partner/coach can help you in these situations. In general, it is sporadic for a company to have internally experienced PLM implementers as it is not their core business to implement PLM. Experienced PLM implementers vary from size and skills – make the right choice.
Conclusion
After writing this post, I still cannot write a final verdict from my side what is the best approach. Personally, I like the PLM toolkit approach as I have been working in the PLM domain for twenty years seeing and experiencing good and best practices. The OOTB-box approach represents many of these best practices and therefore are a safe path to follow. The undecisive points are who are the people involved and what is your business model. It needs to be an end-to-end coherent approach, no matter which option you choose.
Jos Voskuil's Weblog 
Jos, great thoughts about BOM management. Here are some of my thoughts. I can see how BOM management will evolve…
As a complement, even if more and more of the diversity of a product is managed at the software level…
1) A wiring diagram stores information (wires between ports of the electrical components) that does not exist in most of…
BOM has NEVER been the sole "master" of the Product. The DEFINITION FILE is ! For example the wiring of…
Interesting discussion about part numbers and where they originate. Though there seems to be consensus about the EBOM and MBOM,…