Popular Digital Engineering Validation Tool Now Supports Failure Analysis
Newly released Version 1.7 of our tool features failure models and effects analysis along with an expanded set of automated rules
SAIC is seeing demand for digital engineering (DE) continue to grow throughout our client spaces. Organizations are embracing DE and its benefits such as the inherent increased rigor and traceability, and more are seeking similar benefits.
Descriptive system models, typically executed in SysML — the system modeling language — as part of a model-based systems engineering (MBSE) approach, continue to be the cornerstone of efforts around DE. Organizations are using DE to bridge the gap between requirements and mission engineering and design, downstream code repositories, and traditional product life-cycle management (PLM). SAIC recently presented, in partnership with PLM software developer Aras, such linkages between an example model, CAD, and Jira. The presentation can be viewed here.
But the full realization of DE’s promise still rests upon the shoulders of the modelers creating system architectures in concert with subject matter experts. Unlike document-intensive systems engineering (DISE), MBSE enables — and requires — a much higher level of modeling consistency and completeness. Good senior-level modelers continue to be in short supply, so enterprises should not squander their talent pools on tedious tasks such as manual model reviews.
A year ago, SAIC released its first version of the free Digital Engineering Validation Tool. An outgrowth of work conducted at the University of Detroit Mercy’s SysML course, the tool contains rules that encode the best modeling practices and enforce style, consistency, and completeness to realize DE’s promise.
Since we first released the tool, it has become acknowledged as the largest publicly shared rule set, and we have continued to mature and expand it as a service to the worldwide modeling community. In November 2020, IncQuery Labs, a leading provider of server-side validation technology, ported version 1.0 of the tool into its engine. This release, part of the Open-MBEE project, further underscores the impact of SAIC’s contribution to the worldwide systems modeling and engineering community.
We have just released the version 1.7 of the SAIC Digital Engineering Validation Tool. It contains:
- 184 validation rules (for both language and style) for MagicDraw and Cameo Enterprise Architecture, including 20 new or modified rules
- 123 rules that are also available for IBM Rational Rhapsody, including 38 new or modified ones
- Customizations, including methods to connect deeply-nested ports, manage classification and data rights, and conduct failure analysis
- Model-based style guide
- Example model (based on the Ranger lunar probe)
- Explanatory videos
RELATED: Digital Engineering Validation Tool Enables Efficiency Gains
New to this release is an initial version of a profile that enables model-based failure analysis. We initially presented version 1.7 of the tool at the 2020 National Defense Industrial Association’s Virtual Systems and Mission Engineering Conference (see “Using SysML State Machines to Automatically Conduct Failure Modes and Effects Analysis”). It leverages the full behavioral and structural integration made possible by the SAIC modeling style and validation rules to maximize the rigor of and minimize the effort for failure analysis.
At the recent MBSE Lightning Round at the 2021 INCOSE International Workshop, we featured the tool in the presentation “Treadstone +1: The First Anniversary of the SAIC Digital Engineering Validation Tool." The presentation discussed the use of the profile, its growth over the past year, and its use for training modelers.
You can visit the SAIC Digital Engineering Validation Tool page to download our free tool. Also, visit our Digital Engineering microsite for more on SAIC's multifaceted DE services and solutions. We welcome any and all comments about the validation tool's rules, customizations, and methods at DigitalEngineering@saic.com.