A comprehensive and integrated stochastic-fuzzy method for sustainability assessment in the Malaysian food manufacturing industry

Abstract

Manufacturing activities carry significant burdens for all three dimensions of sustainability, i.e., environment, economy and society. However, most of the available sustainability assessment methods for manufacturing are based on environmental concerns only. Moreover, it is hard to find a sustainability assessment method that considers both stochastic and fuzzy uncertainties concurrently and a comprehensive set of weighted and applicable indicators. Thus, the main purpose of this paper was to develop and test an integrated sustainability assessment method that included both stochastic and fuzzy uncertainties. Both quantitative and qualitative, and weighted sustainability indicators for the Malaysian food manufacturing industry needed to be considered, with reliable assessment results. In order to achieve the objective, the Monte Carlo simulation and fuzzy logic approaches were employed. An overall unit-less sustainability index was calculated to evaluate the current sustainability level. This method was demonstrated using a real-world case study of a Malaysian food manufacturing company. The results highlighted and traced the company-wide major low and high performing areas for all three dimensions of sustainability. The results unveiled that the case company could improve its sustainability performance more effectively by decreasing the amount of air emissions, polluted wastewater, etc., and improving the working conditions. This would enable the practitioners and decision-makers to allocate resources accordingly and more efficiently. Finally, the developed method was validated and the implications and conclusions of the research were presented.