Sustainable production and waste management policies for COVID-19 medical equipment under uncertainty: A case study analysis. (July 2021)

• Record Type: Journal Article
• Authors: Ahmad, Firoz; Ahmad, Shafiq; Zaindin, Mazen
• Is Part Of: Computers & industrial engineering. Volume 157(2021)
• Publication Date: 2021-07
• Subjects: Intuitionistic fuzzy parameters -- Modified S-curve membership functions -- Interactive intuitionistic fuzzy method -- Sustainable production and waste management problem; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2021.107381
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Sustainable production and waste management of COVID-19 medical equipment under intuitionistic fuzzy parameters. Novel interactive intuitionistic fuzzy programming approach with various membership functions. Opportunity of selecting the best optimal solution based on multiple criteria. Real case study of Indian automobile company with an effective managerial implications. Abstract: Unfortunately, an abrupt corona-virus disease (COVID-19) outbreak brought a drastic change in human lives. Almost every sector of human-beings and their related activities are severely infected and affected by this COVID-19 pandemic. As days are passing, the impact of the COVID-19 epidemic is going to be more severe. The fundamental needs for personal protective equipment (PPEs) are rising drastically all over the world. In India, many non-pharmaceutical companies or organizations such as automobile companies are engaged in producing the PPEs at a very marginal rate. Thus this paper proposes a modeling and optimization framework for sustainable production and waste management (SPWM) decision-making model for COVID-19 medical equipment under uncertainty. To quantify the uncertainties among parameter values, we have taken advantage of the intuitionistic fuzzy set theory. A robust ranking function is presented to obtain a crisp version of it. Furthermore, a novel interactive intuitionistic fuzzy programming approach is developed to solve the proposed SPWM model. An ample opportunity to generate the desired solution sets are also depicted. The performance analysis based on multiple criteria such as savings from baseline, co-efficient of variations, and desirability degrees is also introduced. Practical managerial implications are also discussed based on the significant findings after applying to the real case study data-set. Finally, conclusive remarks and the future research direction are also addressed on behalf of the current contributing study.