A new product service system concept evaluation approach based on Information Axiom in a fuzzy-stochastic environment

Concept evaluation is a critical issue in product service system (PSS) development. Due to the inherent uncertainty in design and the significant difference between products and services, PSS concept evaluation is a complicated multicriteria decision-making problem involving hybrid imprecision in which fuzzy information and random factors co-occur. The traditional decision-making methods barely consider fuzziness and randomness concurrently. The results often give a false sense of reality due to neglecting hybrid uncertainties related to the evaluation data. The aim of this paper is to improve the objectivity and effectiveness of concept evaluation in the early phases of PSS concept design in a fuzzy-stochastic environment. Fuzzy random variable (FRV), which is a random variable with fuzzy values, is adopted to deal with the hybrid uncertainties. A new evaluation approach integrating Information Axiom and the theory of FRV is developed. Firstly, according to fuzziness and randomness, the evaluation criteria are classified into four categories. Secondly, Information Axiom is used to evaluate the PSS alternatives, and a new algorithm based on fuzzy random simulation methods is developed to compute the information contents for FRVs. Finally, a case study of crane machine PSS concept evaluation shows the effectiveness of the proposed approach.