The CLM-Model-Based Connection

The answer is “yes, of course,” and I often wonder why they even ask until I probe my questioners about their understanding MBS’s. No surprise, what they perceive as MBS’s goes by dozens of names. They overlap, so peering into the enterprise’s model-based nomenclature can get murky.

My questioners are not ignorant (far from it), impatient, or penny-pinching but rather confusing and overlapping IT terminology that I often refer to as “model-based everything and anything”—or just MBx.

Many IT and related business terms are accurate but not particularly informative. “Model-based” terminologies include M-B Definition, M-B Design, M-B Engineering, M-B Systems Engineering, and the M-B Enterprise, and many others. They can be cleanly differentiated but not in this brief blog posting. They have been addressed often in articles by me and by others at CIMdata, and we will be happy to share the specifics.

The definition CIMdata and I use is:

Model-Based Structures are intelligent configurations of data (i.e., data constructs whose structures have meaning above and beyond the constituent data items) that define a product (or service or asset), which can be relied upon for decisions, fostering deeper understandings, speeding comprehension, and advancing or improving the enterprise’s product and/or service offerings.

On a broad scale, these structures’ effectiveness is greatly enhanced by Configuration Lifecycle Management (CLM), on which Configit focuses. Given its support of digital threads, digital twins, and end-to-end connectivity, Configuration Lifecycle Management is often installed in tandem with the broader capabilities of product lifecycle management (PLM), product data management (PDM), for example, especially in A&D and automotive.

Contrast this with the graphics commonly used on document-based information sources—chalkboard diagrams turned into inflexible PDFs and simplified models generated in Microsoft PowerPoint and even word-processors.

Turning now to “why,” effectively implemented MBS’s can be unmatched in dealing with common information-management problems. These include iffy toolset integration, poor capabilities for design reuse, weak management of change processes, cumbersome data configurations, and confusing tech vocabularies and terminologies.

Since 2015, the U.S. DOD has required MBS’s for all defense and weapons systems to help avoid cost overruns and project delays. The DOD aside, why should people in everyday engineering jobs (and management) care about Model-Based Systems and MBx? Why are these so important?

Simply put, by vastly improving access and comprehension. For example, as we at CIMdata see again and again, MBS’s facilitate better decision making throughout the lifecycle—especially when problems are uncovered early when fixing them is easiest, quickest, and least costly.

With an MBS, the entire design can be easily found, quickly comprehended, and reliably verified, whether the physical object in the model is a simple threaded fastener, a turbine engine, or a production line. These improvements in product quality and delivery, manufacturing productivity, and field service benefit both the top and bottom lines.

I’m also often asked if MBS’s are easily validated against the product’s or system’s fundamentals, a.k.a., the single source of truth. Yes, indeed. MBS’s are a foolproof way to ensure this vital internal consistency. CIMdata believes that managing engineering information with Model-Based Structures offers an even bigger long-term benefit.

By leveraging Configuration Lifecycle Management (CLM) within the context of end-to-end product lifecycle management, potentially huge paybacks from digital transformation gain greater support as MBS’s facilitate the removal of paper documents from the enterprise.

Peter Bilello, President & CEO of the strategic management consulting and research firm CIMdata—an internationally recognized authority on Product Lifecycle Management (PLM)—has more than 35 years of experience in the development of business-enabling information technology (IT) solutions for research, engineering, and manufacturing organizations worldwide.

He has participated in PLM analysis, selection, implementation, and training; CAD/CAM/CAE/CIM implementation and management; synchronous and lean manufacturing consulting; software engineering; and general data management strategy development and support. He has authored numerous papers and research reports on PLM and related topics, and his articles, commentaries, and perspectives have appeared in publications throughout the United States, Europe, and Asia.

Mr. Bilello has been directly involved with consultation on the selection, integration, and implementation of large-scale PLM solutions. He has spoken on a number of different PLM-related topics in Europe, North and South America, the Middle East, Africa, and Asia.

Mr. Bilello holds a Bachelor of Science degree in Computer Science with a minor in Physics from the California State University, Fullerton, and a Master of Science in Engineering degree, in Manufacturing Systems Engineering, from The University of Michigan.