Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/42329
Title: Fuzzy Quantitative Approach to Prioritize Green Factors in Supply Chain
Authors: Parthiban, P
Amalaldhasan, S
Dhanalakshmi, R
Keywords: Eco Design;Green Supply Chain Management (GSCM);Fuzzy Quality Function Deployment (FQFD)
Issue Date: Jul-2017
Publisher: NISCAIR-CSIR, India
Abstract: Eco Design integrates environmental thinking into product design and packaging including in its production, consumption and disposal of the product life cycle in the supply chain. In today’s scenario eco design is very important for saving our environment. This papers aims to investigate the technology, organization and environment factors of the eco design that influence the adoption of Green Supply Chain Management using Fuzzy Quality Function Deployment (FQFD). Quality function deployment (QFD) is a planning and problem-solving methodology used to translate customer requirements (CRs) into technical requirements (TRs) in the Course of new product development (NPD). In the proposed model, fifteen fundamental requirements of customers are identified and eight main factors of eco design are derived to satisfy the overall requirements as detailed. The importance of the customer requirements and relationship strength were identified as linguistic data. We have collected data for the criteria from the decision makers of the automotive industry. Under different situation the values of subjective data are often inaccurate so we have applied Fuzzy Quantitative Approach to overcome this deficiency of high subjectivity and low reliability. This study shows the fuzzy logic using Quality Function Deployment for easy decision making. So this proposed method shows the final ranking of the important eco design factors that influences the adoption of Green Supply Chain Management in the automotive industry. The final result of paper gives Stakeholder Cooperation is the most important factors of eco design.
Page(s): 401-407
URI: http://nopr.niscair.res.in/handle/123456789/42329
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.76(07) [July 2017]

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