An application of Hebbian learning in the design process decision-making

The design of a product involves a process in which several different aspects are combined in order to obtain a final, suitable and optimum product. Designers must interact with different stakeholder groups, make decisions and complete the design process. In order to achieve this, different evaluation techniques are used. Depending on the chosen technique and on the field and environment in which each member of the design team was trained, each one of the members will consider one or several aspects of the design project but from a point of view or perspective in line with his/her particular professional background. As a result, all decisions which will affect the design process of the product are focused on these aspects and individual viewpoints. In this paper, an evaluation technique is proposed which allows one to take suitable decisions, taking into account all the factors and perspectives which affect the design process in the best way, searching for a balance among them in relation to the aims and interests of a specific design project. The development of this evaluation technique was inspired by the way in which neurons interact with one another in the brain and it has been based on the Hebbian learning rule for neural networks. Lastly, a real application of the proposed technique is presented to demonstrate its applicability in evaluating industrial designs.