Solving Design Delay Factors with Model-Based Systems Engineering

Today the marketplace expects “smart” as a consumer product attribute. We expect our bathroom scales to connect to our smartphone. We expect our automobile to warn us when we are too close to the next lane.

For the engineers behind such products, “smart” becomes “complex.” The built-in electronics and the software often drive mechanical development, and the mechanical fit/form/function in turns makes demands of electronics and software. A few years ago we were talking about the rise of “mechatronics” to describe these products. Now we have “cyberphysical systems” with the added complexity of being always connected to a computing platform. Such products are not just complex systems, they are mega-complex systems of systems.

To gain new efficiencies when making such smart, connected products, manufacturers are updating traditional notions of Systems

Engineering, defined as the interdisciplinary merging of engineering and management, focusing on solving complexity. What in the past has been a document-based process is transforming into Model-Based Systems Engineering (MBSE).

A “model” in model-based systems engineering is more than a 3D CAD model of the physical attributes. There are financial models, software engineering models, simulation models, prototyping and testing models, and many other kinds of elements and systems being modeled. MBSE requires a platform approach, where all the elements can be aligned into one complete, albeit virtual, representation of the product.

A document-based approach to Systems Engineering forces separate workflows reconciled by repeated rounds of testing and refinement. Each workflow uses software tools specific to the discipline. Collaboration is limited by the separation of design elements. By contrast, Model-Based Systems Engineering allows engineering teams to work in parallel from a single platform, sharing data early when it can do the most good.

There are tangible issues behind the growth of MBSE in manufacturing. A recent survey by Gartner found that 45% of all product launches

were delayed by at least one month. In the current hyper-competitive business environment, such delays can cost revenue, profit, and market share. Management consulting firm OakStone Partners estimates a product launch delay can cost a company from 15% to 35% of Net Present Value. For electronics products, OakStone says late introduction can cost 50% of anticipated revenues.

Researchers at Georgia Tech have identified four major contributors to new product launch delays. In a separate study, researchers at the University of Bristol (UK) took a close look at an Airbus spacecraft functional avionics project and identified four recommended applications for introducing MBSE into a complex workflow. In a bit of serendipitous validation, the first three delay factors identified by the Georgia Tech team match the first three recommendations identified by the Bristol team.

Delay factors                                                               Success factors with MBSE

Poor management of development processes Organizational modeling
Frequent design changes Functional Validation
Lack of coordination among functional areas Consistency in communications
Unanticipated resource shortages Reusable MBSE templates

 

The problems inherent in complex engineering projects don’t always reveal themselves until the prototyping stage, where changes are expensive and solutions are harder to implement. In a multidisciplinary project, whether mechatronic or cyber-physical, the biggest loss factor without the use of MBSE is innovation. The “what if?” moments that bring success often occur at the intersections between disciplines. When engineers can’t easily interact and brainstorm using a common data set, opportunities for spontaneous innovation are hard to come by.

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Editor:

Learn more about a systems approach to product development

Download an eBook, Simplifying Complexity Through Model Based Systems Engineering

Listen to a seminar on Requirements in Engineering in Context of Model Based Systems Engineering

randall.newton@gmail.com'

Randall Newton

Randall S. Newton is Managing Director of Consilia Vektor, a boutique consulting firm serving the engineering software industry and related technologies. He is a Contributing Editor at Digital Engineering Magazine and AEC Magazine (UK). Mr. Newton has been in the engineering software industry since 1985 as a journalist, business analyst, publisher, programmer, and marketing consultant. His recent research explores the use of blockchain technology for industrial applications, and the rise of new design technologies for additive manufacturing.