Automated preliminary design using artificial neural networks

This dissertation investigates the applicability of artificial neural network systems to preliminary engineering design tasks. Synthesizing new, possibly innovative designs by exploring the development of structural topologies and determining their possible behaviors are two steps of preliminary design where this research concentrates. These two areas of preliminary structural design have proven difficult for design researchers. Using the neural network approach toward these tasks is feasible, but issues such as representing design problems in neural networks, collecting good design examples, and measuring network performance are still unresolved. This research begins by examining philosophies of design, which provides a basis for later discussions. In particular, the influence of design automation and computational models of design processes on the science of design are considered. Next, this work provides an introduction to artificial neural networks. Two classes of neural models, constraint satisfaction and supervised learning models, are examined in depth. The constraint satisfaction model is later used for development of a system for qualitative evaluation of preliminary designs. Supervised learning models provide the cornerstone for development of a model that uses induction in an attempt to learn from design examples, generalize results, and generate preliminary structural designs. A major bottleneck in developing most knowledge based systems is acquiring and representing requisite knowledge. Supervised learning models of connectionism have the potential to alleviate this obstacle. The second neural network system discussed and demonstrated is a hybrid back propagation model. This system can learn from examples of previous designs and is able to generate new designs. In addition to design issues, the discussion of connectionist models includes details of the different models, their performance, attributes, integrity, and shortcomings. The results of this research are an initial investigation into connectionism as applied to design. Both connectionism and the theory of design are relatively young in terms of formal research when compared to traditional areas of engineering and science. This work contributes to the maturing effort and identifies promising areas for further research.