Abstract

AbstractIt has been almost 20 years since INCOSE and the OMG kicked off an effort to create a standardized model‐based systems engineering modeling language. That effort culminated in 2006 with the creation of the Systems Modeling language (SysML). Over the past several years, numerous industries have increased their adoption of SysML and MBSE as a core practice within their engineering lifecycles. However, they have not achieved many of the originally envisioned benefits. On closer inspection, many of the challenges and barriers with which MBSE practitioners are currently struggling are remarkably similar to the problems seen in large DoD software programs from the 1970s and 80s and were resolved decades ago by the software development community regarding scale and complexity. System models are becoming larger and more complex. Yet, in this expanding and maturing MBSE environment, projects continue to experience problems with model integration, repository performance and model lifecycle management. It is time to go back and take another look at how the software community attacked problems of extreme scale.The similarity between MBSE's model management pain points and those experienced years ago by the software industry is not unexpected. Adoption of MBSE requires the replacement of the largely manual, document‐based engineering processes with a complex engineering information processing system. Unlike documents, the models produced by that system are living artifacts that require management over the project lifecycle and which have all the characteristics and complexity of software.This paper presents a framework for MBSE planning and model lifecycle management based on the key practices from Systems Engineering and Software Engineering to provide an actionable set of best practices that can be applied today to address current MBSE lifecycle management issues. We have organized these best practices around three key MBSE Model Management Imperatives.

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