Performance evaluation of manufacturing systems based on dependability management indicators—case study: chemical industry

Abstract

Dependability is a key decision factor in today’s global business environment affecting product cost and process. Dependability reflects user confidence in fitness for use by attaining satisfaction in product performance capability, delivery, service availability upon demand, and minimizing cost. The main objective of this study is to develop an integrated approach for evaluation of manufacturing systems based on dependability indicators for conducting a better dependability management system (DMS) through integration of the principal component analysis (PCA) and the data envelopment analysis (DEA). To achieve the objective of this study, an industrial sector—chemicals and chemical products in Iran—is selected as the case of this study in accordance with the International Standard for Industrial Classification of all economic activities (ISIC). Firstly, we define dependability indicators, for both inputs and outputs, based on IEC 60300. Due to the extra amount of indicators, we utilize a hierarchical structure to cluster the indicators for an easier analysis. Secondly, for reducing the number of some variables, we apply pair-wise comparison to assign weights and to unify the related sub-criteria to one main criterion. Finally, an integrated DEA–PCA approach is employed to assess the most and the least dependable units and to find critical indicators in macro and micro levels in order to make policy for implementation of DMS in manufacturing systems.