The transition to model-based systems engineering (MBSE) is essential to meet the demands of increasing system complexity, productivity, quality and shorter design cycles. Necessary perspectives, associated roles and competencies for the application of MBSE are not sufficiently defined. The paper at hand presents a role model for the practical application of MBSE based on three major steps: (1) identification, (2) categorization and (3) association of stakeholders, which implement and apply MBSE within an enterprise. The use of the role model is demonstrated and evaluated in a test case based on personas within a fictional scenario which illustrates the implementation of MBSE. The roles, which are adapted to today’s conditions, serve as a practical guide comprising all basic conditions that have to be considered when applying MBSE. Practitioners can easily tailor the illustrated results to their own use case.

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Effect chain modeling approaches are applied to model cause-effect relations and analyze affected elements and dependencies. In this paper a systematic literature research is conducted to derive main characteristics and limitations of existing approaches. Then, the Model-based Effect Chain Analysis (MECA) method is introduced. Evaluation proves applicability of the method by means of a case example. This is done in the context of a project with a German automotive company. In the project 66 workshops were conducted to model certification-compliant effect chains in accordance to the UN ECE 156.

Complexity of variances in systems leads to challenges in structuring and in making development decisions. Models can collect system information to make them available and transparent. Currently, no approach to model the variance of systems along relevant engineering artifacts exists. This research aims to develop a consistent variant modeling approach: In a literature review (1), relevant approaches in model-based variant management are identified to derive requirements for variant modelling (2). Based on the requirements, approaches are evaluated in a matrix (3). Since no approach satisfies all requirements, one approach is extended (4). For evaluation purpose (5), applicability of the approach is demonstrated and assessed by experts. The result is a modeling method for variant modeling.