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Sustainability 2019, 11(4), 948; https://doi.org/10.3390/su11040948

A Comprehensive and Integrated Stochastic-Fuzzy Method for Sustainability Assessment in the Malaysian Food Manufacturing Industry

1
Department of Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Malaysia
2
School of Mechanical and Manufacturing Engineering, National University of Sciences and Technology, 44000 Islamabad, Pakistan
3
Department of Mathematical Sciences, Universiti Teknologi Malaysia, 81310 UTM Skudai, Malaysia
*
Author to whom correspondence should be addressed.
Received: 28 December 2018 / Revised: 28 January 2019 / Accepted: 28 January 2019 / Published: 13 February 2019
(This article belongs to the Section Sustainable Urban and Rural Development)
Full-Text   |   PDF [2571 KB, uploaded 13 February 2019]   |  

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. View Full-Text
Keywords: fuzzy logic; food industry; Monte Carlo simulation; sustainability assessment; sustainable manufacturing; Triple-bottom line fuzzy logic; food industry; Monte Carlo simulation; sustainability assessment; sustainable manufacturing; Triple-bottom line
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Ahmad, S.; Wong, K.Y.; Zaman, B. A Comprehensive and Integrated Stochastic-Fuzzy Method for Sustainability Assessment in the Malaysian Food Manufacturing Industry. Sustainability 2019, 11, 948.

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