Product configuration design based on customer requirement modelling and optimization method

Abstract

In the environment of industry 4.0, a smart production system is not a fantasy. Based on Cyber physical system (CPS) and the Internet of things (IoT), it is capable to transform its process flexibly to suit diverse customer requirements and design changes with lower cost in a short period of time, providing digital ‘configure-to-order’ (CTO) services. A product configuration system, which translates the voice of customers to technical specifications, is needed to handle variable and complex product knowledge in order acquisition and fulfilment stage. The purpose of this dissertation is to study and research a methodology to enhance the communication between customers and manufacturers. It aims to find an approach to receive the voice of customers as input to assist product conceptualization and generate a product configuration as output that maximizes the customer satisfaction. In this approach, engineering characteristics (ECs) are defined and selection pools are constructed in the first stage. Secondly, quality function deployment (QFD) is modified and integrated with the Kano’s model to qualitatively and quantitatively analyse the relationship between customer requirements (CRs) and customer satisfaction (CS). Thirdly, a mathematical programming model is applied to maximize overall customer satisfaction levels and recommend an optimal product configuration. Lastly, sensitivity analysis is conducted for customers to revise and determine the final customized product specification. A case study was conducted to demonstrate the procedure and the effectiveness of the proposed product configuration system.