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Bolognini, Francesca; Shea, Kristina; Seshia, Ashwin

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From modelling to manufacturing, computers have increasingly become partners in the design process, helping automate many phases once carried out by hand. In the creative phase, computational synthesis methods aim at facilitating designers’ tasks through the automated generation of optimally directed design alternatives. Nevertheless, applications of these techniques are mainly academic and industrial design practice is still far from applying them routinely. This is due to the complex nature of many design tasks and to the difficulty of developing synthesis methods that can be easily adapted to multiple case studies and external automated simulation. This work stems from the analysis of implementation issues and obstacles to their widespread use found in previous research on synthesis methods. The research investigates possible improvements to these methods through the application of a novel technique to complex design tasks. The ability of this technique to scale-up without sacrificing accuracy is demonstrated. The successful results confirm the possibility to use synthesis methods in complex design tasks and spread their commercial and industrial application.

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