An integration model for generating and selecting product configuration plans

Abstract

In the developed market, time-to-market and market shares require companies to provide products that satisfy customer requirements in a timely manner, and the variety in product configurations has been analyzed thoroughly. Against this background, this study addresses an integration model for generating feasible configuration plans based on market transaction data and for selecting the optimal configuration plan(s) based on customer requirements. Transaction data can be used for clustering products to analyze the characteristics of segmented markets and yield the probabilities of configuration plans; along with the constraint conditions, feasible configuration plans can be generated, as well as market strategies for different segmented markets. In addition, a probabilistic classifier, the Naïve Bayes Classifier, is applied to map the customer requirements to the configuration plan with the highest probability. The classifier is suitable for handling imprecise and uncertain information, such as product requirements expressed by customers. A case study of a mouse device is illustrated, and the results indicate the integration model can achieve a good performance in terms of time advantages in project design.