Applying Artificial Intelligence in Retrieving Design Solution

Design is a very important step in the product life cycle, because it is generally the key for the success or the failure of the product. The field of design theories and methodologies is fill with theories and methods that have been taught and developed throughout the years. Most of them relay on subdividing the design process into phases, where the transition between each two phases relay on using some design tools. One of the main challenges of nowadays is to find a way for the integration of artificial intelligence (AI) in the design process. This integration could be very benefic, due to the fact that AI can learn quickly the relationship between input and output of any phenomena, and it can also give us a prediction of the behavior, if the inputs parameters vary. In our previous work we shaded the light, on how we can improve the transition between design phase by storing and retrieving design solutions using morphological analysis and design tools like DFX. In this work, we present a deferent methodology to perform this transition which relay on using an artificial intelligence tool called Artificial Neural Networks (ANN) instead of morphological analysis to retrieve the right design solution. To illustrate this method, we will take the same example from our previous work and will show how we can use ANN to learn and predict the right design solution.