Early and Efficient Quality Assurance of Risky Technical Parameters in a Mechatronic Design Process

Abstract

Mechatronic design processes in automation systems engineering projects require concurrent engineering of various disciplines operating within technical, commercial, and project management constraints. Unfortunately, early and efficient quality assurance of technical parameters, which affect risk-relevant constraints in the mechatronic design processes, is difficult and error-prone due to the heterogeneous local model representations of shared concepts that the domain experts use to define these constraints. In this paper, we investigate the effectiveness and efficiency of the adapted multi-model dashboard (MMD) approach and a traditional approach for monitoring technical parameters and constraints in mechatronic design processes. We evaluate these approaches in the context of a realworld use case, the welding line process for automobile parts. Major results are: the MMD process was at least as effective and efficient in eliciting relevant project constraints and model dependencies as traditional approaches in the evaluation context.