New product acceptability evaluation and improvement model with knowledge reuse

Abstract

Evaluating and improving product acceptability is an important step to minimize the risk of a new product not being accepted. Existing approaches do not integrate any acceptability evaluation during the New Product Development process (NPD). They do not make it possible to evaluate different improvement scenarios built from experts knowledge or past projects experiences. This paper proposes a method that evaluates and improves product acceptability by allowing the project manager to find out an improvement scenario. The proposed method is based on the evaluation of the users’ concept perception. It exploits the inference properties of Bayesian networks (BN) allowing to make useful estimations of improvement scenarios. Furthermore, those scenarios are composed of actions that enable to improve different dimensions of users’ acceptability. The modeled actions are stocked in a knowledge base allowing this knowledge to be reused in other projects. The method is applied to the design case of a medical-stocking threading device in order to illustrate its interest.