Design and implementation of a fuzzy inference system for supporting customer requirements

Efficient and effective response to the requirements of customers is a major performance indicator. Failure to satisfy customer requirements implies operational weaknesses in a company. These weaknesses will damage both the rights of customers and the reputation of the company. The traditional method of handling customer requirement for a machine tool manufacturer was dominated by manual process and subjective decision. In this study, we improved the operation process of handling customer requirement. The framework of a customer requirement information system (CRIS) for machine tool manufacturers was then analyzed, integrating rule-based fuzzy inference and expert systems, and a prototype system developed. The CRIS supports both customers and service personnel in providing a systematic way of fulfilling and analyzing customer requirements. The system was installed and operated in a machine tool manufacturer and the performance was found promising.