A soft computing methodology to analyze sustainable risks in surgical cotton manufacturing companies

Bhalaji, R. K. A. and Bathrinath, S. and Ponnambalam, S. G. and Saravanasankar, S. (2020) A soft computing methodology to analyze sustainable risks in surgical cotton manufacturing companies. Sadhana, 45 (1). pp. 1-2. ISSN 0256-2499 (Print); 0973-7677 (Online). (Published)

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Abstract

A well-organized sustainable risk management in an organization often generates environmental and economic advantages. Addressing “sustainability and risk” simultaneously, an organization is more capable of enduring challenges that produce environmental and operational stability in management. In an industrial organization, these primary areas of concern involve social responsibility and a focus on occupants’ health and well-being; both areas address environmental and climate change, with an end result of increasing competitiveness and profitability. The key challenge lies in exploring sustainable risks associated with the industry so that they are addressed strategically. This research work is one such attempt to find sustainable risks in the manufacturing sector. This research is the outcome of a case study conducted in three leading surgical cotton manufacturing companies in the southern part of India. A hybrid multi criteria decision making based fuzzy decision making trial and evaluation laboratory and analytic network process with preference ranking organization method for enrichment evaluations (FDANP with PROMETHEE) methodologies is used to derive the results. The final outcome of this paper presents the identified critical sustainable risks from the case study, and also serves as a model for risk managers in manufacturing sectors. By identifying sustainable risks at an early stage, a company may avert the occurrence of undesirable incidents while, at the same time, may enhance their production capacity.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Sustainability; Risk factor; F-DEMATEL; ANP; PROMETHEE
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TS Manufactures
Faculty/Division: Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 03 Nov 2022 09:43
Last Modified: 03 Nov 2022 09:43
URI: http://umpir.ump.edu.my/id/eprint/28629
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