Model-Based Systems Engineering for Digital Manufacturing: A Proof of Concept

A lack of integrated approaches to enhance product and production engineering activities can result in management overhead, the need for increased supervision, and make it difficult for engineers to trace sources of errors. Traditional solutions such as Product Lifecycle Management (PLM) software are limited in their ability to adapt quickly to change and to transfer knowledge not only between departments but also between the physical and virtual realms.

The team will develop a manufacturing/production system model to be integrated within a digital enterprise (data, models, etc.) that will provide decisionmakers with a methodology aimed at capturing manufacturing and production system considerations in a model-based environment. This will allow for the connection and integration of product design, manufacturing and production models, and data through an authoritative source of truth. At the enterprise level, this research will contribute to increasing awareness of MBSE’s value and addressing the need to develop a workforce with knowledge and skills relevant to Digital Engineering and MBSE.

MBSE tools and methodologies using Systems Modeling Language (SysML) are currently found in the aerospace and defense industries with varying levels of maturity and tool integration. SysML tools are readily available; however, the challenges and risks for MBSE development concern how to deploy these methodologies for product development and PLM integration. In the aerospace industry, many of the challenges with commercialization are compounded by the complexity of products and organizations and result in siloed digital development. By applying an integrated MBSE model to a proof-of-concept air vehicle, this project will remove barriers found in more complex systems and help form a strong foundation for future application of MBSE for analogous product solutions.

The team developed a manufacturing/production system model to be integrated within a digital enterprise (data, models, etc.) that will provide decision-makers with a methodology aimed at capturing manufacturing and production system considerations in a model-based environment. This allows for the connection and integration of product design, manufacturing and production models, and data through an authoritative source of truth (ASoT). At the enterprise level, this research contributed to increasing awareness of MBSE’s value and addressed the need to develop a workforce with knowledge and skills relevant to Digital Engineering and MBSE.