The evaluation and improvement of process quality by using the fuzzy sets theory and genetic algorithm approach

Abstract

The performance evaluation of business processes in uncertain environments has important consequences for investors, stakeholders and has critical importance for the improvement of business processes, which is one of the requirements of ISO 9001. In this paper, a new fuzzy model is proposed for evaluation and improvement of process quality. The fuzzy ratings of the Key Performance Indicators (KPIs) are stated as fuzzy pair-wise comparison matrices (by analogy to the AHP framework). By using the developed procedure, the fuzzy weights of KPIs are given. The KPI values are based on the assessment of decision makers. The developed solution, based on the genetic algorithm approach, is presented and tested on data from 53 Serbian manufacturing SMEs. The presented solution enables quality assessment of a purchasing process, the fuzzy ranking of KPIs, the selection of critical KPIs by using an exact approach, optimization and the provision of the basis for successful improvement of purchasing process quality.