Product service system configuration based on support vector machine considering customer perception

Nowadays, more and more manufacturers bundle products and services together as product service systems (PSSs) to create more values for customers and gain competitive advantages for themselves. To achieve desired benefits and customer satisfaction, PSSs are usually configured by selecting product components and service modules from a predefined component and service library according to some constraints and customer needs. In this paper, an approach for PSS configuration is proposed in which customer needs are firstly divided as functional needs and perception needs which are generally expressed by customers through their own words. And then, the representative descriptions of perception needs are extracted by factor analysis. Based on it, a multiclass support vector machine model is built for configurating a specific PSS that meets customer needs. Finally, weighbridge is used as an example to validate the proposed approach and the results show that it is effective.