Decision support system for rapid prototyping process selection through integration of fuzzy synthetic evaluation and an expert system

A new method is proposed for selecting the most appropriate rapid prototyping process according to user's specific requirements by using the expert system and fuzzy synthetic evaluation. The selection process is divided into two stages. First, it is necessary to generate feasible alternatives, which are executed under the expert system environment. Second, given those feasible alternatives, the fuzzy synthetic evaluation approach is employed to produce a ranking order of the alternatives and to finalize the most suitable rapid prototyping system. One distinctive characteristic of this method is that quantitative as well as qualitative measures are employed, providing more accurate results. The decision system developed based on the proposed method is composed of four modules: a database to store the specifications of various rapid prototyping processes; a knowledge-based expert system for determining the feasible alternatives; a fuzzy synthetic evaluation model to select the most suitable rapid prototyping process; and a user interface and an expert interface to interact with the system. The fuzzy synthetic evaluation approach used in the system is illustrated in detail by a numerical example. Furthermore, a Java-enabled solution, together with web techniques, is employed for developing such a networked decision support system. Finally, two examples of rapid prototyping process selection are designed to demonstrate the application of the system. The system has been implemented and can run at a rapid prototyping and manufacturing networked service platform that the authors have developed.