Optimization of the murata vortex spinning machine parameters by the SMAA-MOORA approach

Abstract

Murata Vortex Spinner (MVS) has quickly captured the attention of staple yam producers due to its ability of spinning 100 % cotton fibers at very high speeds. Many of researchers have been studied statistical approaches to select appropriate MVS machine parameters for producing of desired yam. However, optimization of machine parameters is a multi-criteria decision making problem. In this paper we proposed a new method, SMAA-MOORA, by integrating the Stochastic Multi-Criteria Acceptability Analysis (SMAA) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) methods to determine the optimum nozzle pressure and delivery speed of MVS machine for cotton yam. Thanks to SMAA-MOORA method MOORA method is applicable with stochastic data means uncertain data. This paper shows that SMAA-MOORA gives more confident and accurate SMAA results.