Optimal Selection Method of Process Patents for Technology Transfer Using Fuzzy Linguistic Computing

Abstract

Under the open innovation paradigm, technology transfer of process patents is one of the most important mechanisms for manufacturing companies to implement process innovation and enhance the competitive edge. To achieve promising technology transfers, we need to evaluate the feasibility of process patents and optimally select the most appropriate patent according to the actual manufacturing situation. Hence, this paper proposes an optimal selection method of process patents using multiple criteria decision-making and 2-tuple fuzzy linguistic computing to avoid information loss during the processes of evaluation integration. An evaluation index system for technology transfer feasibility of process patents is designed initially. Then, fuzzy linguistic computing approach is applied to aggregate the evaluations of criteria weights for each criterion and corresponding subcriteria. Furthermore, performance ratings for subcriteria and fuzzy aggregated ratings of criteria are calculated. Thus, we obtain the overall technology transfer feasibility of patent alternatives. Finally, a case study of aeroengine turbine manufacturing is presented to demonstrate the applicability of the proposed method.