COE 2018 Hot Topics: An Intro to Model Based Systems Engineering

In 2018, COE will focus on six hot topics, which have been designated as areas of interest companies are trying to capitalize on in the near future. In the next few editions of NewsNet, COE members will share an introduction to each topic. Ed Ladzinski, COE Board Member and CEO and Co-Founder of SMS_ThinkTank L.L.C., gives us a primer on Model Based Systems Engineering (MBSE).

Model Based Systems Engineering (MBSE) definition: MBSE is the 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 (INCOSE-TP-2004-004-02, Version 2.03, September 2007). The emphasis is on leveraging virtual representations of a system to support the various engineering and business activities throughout the lifecycle of a product. Domain models are the primary means of information exchange between engineers, rather than relying on document-based information exchange. Reliance is placed on the use of digital models including M-CAD, ECAD, SysML, and UML that are managed in a data rich computing environment.

It seems that MBSE is one of the most used and often abused acronyms in recent engineering discussions and publications. Is this the result of tool vendors promoting their promised solutions, trying to come across as thought leaders to the upper management clients they serve? Or, perhaps, is this a phenomenon occurring from the dissemination of key messages encouraged by various nonprofit engineering consortiums, in looking to the future of addressing the ever increasing complexity of products and processes? I would like to believe that MBSE is a discipline that most engineers, analysts, scientists and management believe is the best path to address the many additional challenges they are encountering regarding the complexity associated with increasing customer demands in products and processes.

Let’s begin with some givens. Products and processes across almost all industries are exploding with innovation – embedded systems and interactive environments accounting for an increasing share of the total product cost – while at the same time ensuring a cost-effective and reliable product is introduced to the market. For many OEMs and suppliers to remain competitive, a systems engineering culture and best practices should be adopted to address the increasing complexity in features requested and expected by customers. An additional major drive for the market is change toward an “experience-driven” economy/society where the consumer demands much more flexibility and a “one size fits all” approach is gone. 

By applying the understanding and appreciation of system modeling and simulation to the well-established systems engineering thinking, major challenges can be addressed when enabling new technologies and processes. 

To appreciate MBSE, one must first understand why different industries are so attracted to this new engineering culture. Innovation is a key differentiator. Companies define their market position by the way they capture, work with and deploy data as a major key asset, and what cultural behavior they demonstrate in their day-to-day operation. Innovation leaders realize that accurate and accessible data is the foundation for insight and inspiration. They make use of data, derive knowledge from this data in real-time (or close to it) and execute upon it. This is what we call “Innovating at the Speed of Thought.” An open and extensible systems engineering development platform with integrated modeling and simulation tools that helps manage the processes and data, provides decision-making support and allows for collaboration is needed. This platform-based approach needs to leverage a common system engineering and product data model (Model Based Systems Engineering) that encompasses well-written requirements, platform, program, project, system definition, product structure, lifecycle and configuration-management capabilities. Essentially, such an innovation platform is a key enabler to reach higher systems modeling maturity levels and, in turn, help a company reach a more competitive position within the organization’s business model. The various levels of such an approach that need to be enabled and supported by an underlying platform technology are shown in Figure 1, below. Companies need to understand at what level of innovation maturity they operate in order to stay competitive, thus sustaining their businesses for the long haul. Leaders that are operating at or are approaching the innovation maturity level of “System Innovation” are in a much better position to understand and anticipate the needs of their customers and, in turn, increase their market share. The innovation platform has to be structured in a way to support a unified data model.


1: Innovating at the Speed of Thought (Courtesy: SMS_ThinkTank™) 

The unified data model needs to support cross-discipline decomposition and aggregation, at the same time maintaining the links, relationships and rich semantics that exist between the individual artifacts that describe the system or product throughout the entire life-cycle of a product or process. (See Figure 2, below.)

This data model could be represented by a 3-D model, code, a SysML model or some other conceptual model that incorporates both behavior and data.


Figure 2:
SMS is an Iterative Process Throughout the Product Life Cycle (Courtesy: SMS_ThinkTank™) 

Yes, there are hundreds, perhaps even thousands, of these “V” models. Each company must develop their own model that reflects their optimum processes and best practices. There will be many similarities to the one pictured in Figure 2, but the important point is that blind adoption of a generic model is not the recipe for success. Implementing a successful systems engineering practice is a complex task, much more complicated than just following the predicted fields of the “V,” and must be embraced as it relates not only to the corporation’s processes and product feasibility, but to the organization and technologies as well. 

Will the perception of employing MBSE change from industry to industry? I certainly believe so. I also believe the acronym will take on a different understanding, even between departments with the same company, although the basic principles of writing good requirements and using unified data models along with other essentials will be common. Consider two groups within a company. One group is working on MBSE best practices within a PLM (Product Lifecycle Management) environment utilizing M-Cad, as opposed to another group developing the controls for a product within in ALM (Application Lifecycle Management) environment. The basic principles forming the foundations of each initiative are the same, but the implementation of each system could be very different. These subtleties can and will add to the confusion that upper management may experience in understanding the rapid pace of today’s technology and its impact on organization and process. 

The successful implementation of MBSE will include changes in organization, process and technology that must be carefully understood. The correct plans must be developed and carried out to ensure all entities agree to embrace this cultural change.

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