Personalized customization in product design using customer attributes and artificial neural network

Increasingly, customers choose products in terms of the experience and enjoyment that the product can bring to them, in addition to functional performance and usability. These experiences involve a range of customer emotional feelings. Correct understanding of customer feelings and subsequently relating them to new product elements or features, are the important issues for a successful design. While this has been addressed by technologies, like kansei engineering, the difficulty remains in handling the differences of an individual kansei. This article proposes the use of artificial neural networks to solve this problem and to explore the relationship between customer attributes and product evaluation. Initial results have established the feasibility and success of this method. It will find application in product design and in particular personalized customization.