Use of multi-criteria decision models for optimization of selecting the most appropriate best available techniques in cleaner production applications: A case study in a textile industry

Abstract

In the decision-making process of the best available techniques (BAT), there are important uncertainties such as the absence of versatile defined evaluation criteria and systematic decision-making models. This study aimed to contribute to the development and systematization of decision-making processes for BATs in industrial facilities. An exemplary application was carried out in an integrated home textile production facility. A comprehensive cleaner production analysis study was carried out in the facility and an initial BAT list (total of 52 BATs) was prepared. In addition, a total of 40 novel evaluation criteria was defined in seven main groups such as resource use, environmental benefits, side interactions, economic saving, and applicability. A total of 15 different multi-criteria decision-making models were investigated and among them the preference ranking organization method for enrichment evaluations (PROMETHEE), technique for order preference by similarity to ideal solution (TOPSIS), multi criteria optimization and compromise solution technique (VIKOR), additive ratio assessment (ARAS), and complex proportional assessment (COPRAS) decision-making models were selected for use in the BAT decision-making process. Employing these models, most appropriate BATs were selected for the facility. In addition, the results of the studied 5 models were technically compared. It was found that VIKOR and COPRAS models can be preferred in the process of deciding on BATs in cleaner production applications. Moreover, it was concluded that the defined evaluation criteria in this work were also sufficient for decision-making processes. It is believed that this paper will be a good technical guide and provide a significant contribution to BAT selection/decision-making processes in full-scale industrial cleaner production applications in terms of elimination of uncertainties and improvement of the overall decision-making process.