Task Definition for Design Automation

Abstract

Design automation has been the focus of research for more than five decades. It supports design processes in several aspects by automating design tasks based on computational methods and tools to save time, generate alternative design solutions, explore solution spaces, and reuse engineering knowledge. Yet, the current industrial practice does not reflect the opportunities provided by state-of-the-art design automation methods. The factors contributing to this gap are: first, a lack of knowledge of design automation opportunities and insufficient support for the integration of design automation in design practice including the supporting methods and technological environments. Second, metrics and methods for comprehensive estimation of the impact of design automation implementation on design practice do not exist making it difficult to quantify the value of design automation and justify efforts for implementation. Finally, design automation applications are often perceived as black-box systems since knowledge is hard-coded in design automation applications. This also increases efforts for knowledge formalization. In response to these issues, this thesis proposes a methodology for design automation task definition that features collaborative workshops to account for the different viewpoints of designers. It builds upon a design automation task categorization that is characterized by the knowledge levels required for design automation task definition and consists of four different methods that build on each other. The first method focuses on the identification of design automation use cases. It features detailed analysis of design processes and reuse of design automation task templates to support both the identification of possible use cases and the integration of the corresponding software applications into design practice. The second method introduces a top-down derivation of metrics based on potential failure modes in design. The third method enables estimation of the impact and value of design automation implementation based on design automation task templates enabling reuse and associating metrics to design processes. Finally, design automation task formalization by designers is enabled using graphical modeling. The method supports reuse and modularization of knowledge based on the design automation task categorization. To enable reasoning in the context of the methodology, a meta-model that clarifies the vocabulary is established based on standardized languages. The proposed methodology is evaluated based on three industrial use cases that highlight the necessity to involve multiple designers for design automation task definition to account for different viewpoints for needs identification. Further, the results show the potential for design automation application in the early stages of design as well as the applicability of the proposed approach for design automation task formalization by designers. Thus, the work presented in this thesis contributes by ii introducing and evaluating a novel methodology for design automation task definition that brings the opportunities of state-of-the-art design automation methods into line with designers’ needs. It extends the state-of-the-art with respect to new methods supporting design automation task definition and also consolidates research in design automation. Thereby, the methodology enables alignment of research on design automation and increases awareness of design automation opportunities in industry among the different stages of the design process.