Abstract
The impact of design complexity on additive manufacturing (AM) process is a current research topic, intensified by familiar phrases such as 'complexity is for free'. The economic optimum for an AM process usually reflects a compromise between production costs and fulfilment of design for manufacturing (DfM) principles. The AM fraternity entails further investigation of the design complexity topic and its impact on production costs while targeting DfM as a holistic tool. In this paper a data-driven method was proposed which uses design complexity as a performance indicator for evaluation of specimens built using AM process. Further, this paper identifies five critical design features of an automotive air filter model to assess its optimal design complexity and manufacturability. Build time and dimensional accuracy were selected as the responses of the study. The research indicates that the proposed design complexity optimisation approach has potential to reduce build time and subsequent build cost by 10% as compared to a non-optimal model of the selected automotive case.
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