Applying MQCAC and Fuzzy TOPSIS to Improve the Unleaded Gasoline Quality

This study proposes a novel hybrid method that integrates a new multi-quality characteristic analysis chart (MQCAC) and a fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS). First, all the data of nominal-the-best, larger-the-better, and smaller-the-better quality characteristics were transferred into new evaluation data by using a change-of-variable technique. Furthermore, a new MQCAC was developed to measure whether all the quality characteristics of a product satisfy specifications. All substandard quality characteristics were regarded as alternatives when conducting fuzzy TOPSIS analysis. Subsequently, the top priority substandard quality characteristic for improvement in light of resource requirements and the performance improvement potential under a fuzzy environment was obtained using the proposed method. Finally, a real-world case study is presented to demonstrate the practicality and feasibility of the proposed method.