| Cloud manufacturing is a new manufacturing platform and service model committed togathering and sharing global manufacturing resources, and achieving the optimal allocation ofmanufacturing resources. It fully fuses the existing advanced manufacturing mode and cloudcomputing technology. It is a new intelligent and networked manufacturing mode, which isservice-oriented, high efficiency but low consumption and based on knowledge. As one of the keyways to improve the utilization ratio of cloud manufacturing resources and realize appreciation ofmanufacturing resources, manufacturing cloud service composition (MCSC) plays an importantrole in implementing and carrying out cloud manufacturing.However, in the whole life cycle of MCSC, there are many uncertainty factors that influentMCSC successfully complete the mission and requirements of users. Therefore, flexibility ofMCSC is necessary to be researched and took as one of the evaluation indexes of MCSCoptimization, so that the service quality of MCSC can be guaranteed and improved.This paper took flexibility of MCSC as the research object, and it aimed to perfectoptimization system of MCSC and realize effective and intelligent manufacturing cloud servicemanagement. Concepts of cloud manufacturing, manufacturing resources, manufacturing cloudservice and manufacturing and the process of MCSC were analyzed in basis. The concept offlexibility of MCSC was defined that the ability MCSC had to rapidly response to the unpredictabledynamic changes, dynamically adjust itself and fulfill the requirements or tasks of users, whenMCSC was affected by uncertain factors such as the external factors and the internal factors duringthe whole life cycle of MCSC. The evaluation index system of flexibility of MCSC was established,combined with the analysis and elaboration of the influencing factors of flexibility of MCSC, in thewhole life cycle of MCSC. The evaluation index system was consist of four first evaluation indexesincluding task flexibility, platform technology flexibility, collaboration flexibility and correlationflexibility, and nine second evaluation indexes including research and development flexibility,delivery flexibility, product quantity flexibility, problem identification flexibility, problem responseflexibility, project flexibility, adjustment flexibility, composable correlation flexibility and entitycorrelation flexibility. Quantitative methods for every evaluation index were presented.Combination weighting method that combined analytic hierarchy process (AHP) method andentropy weight method was used to improve the TOPSIS method. Comprehensive evaluation procedure of flexibility of MCSC was proposed. Finally, an example was used to verify thescientificity and validity of the evaluation procedure. This paper provided theoretical foundation foroptimizing MCSC. |
