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Supply chain is the linkage of series of organizations with facilities, functions, and logistic activities that are involved in producing and also delivering a product or service. In the past, when firms manufactured in-house, they sourced locally and sold directly to customer. During that period, supply chain risk was less diffused and easier to manage. In recent years global supply chain was hit by increasing globalization, because all organizations had to face vulnerable by different types of risk in their inbound and outbound supply chain network. The various supply chain (SC) vulnerabilities are reputation, unreliability, overstocking, price increases, corruption, natural disasters and financial failure. The implications of supply chain possessing vulnerability costlier and lead to significant customer delivery delays, etc. Though, different types of supply chain vulnerability management methodologies have been proposed for managing supply risk. To the above concern, reinforce outbound supply chain risk management by proposing an integrated methodology to classify, manage and assess outbound supply risks were made. The contributions of the work owing to namely (1) outbound supply risk factors are identified through both supply chain risk literature review and industrial interview; (2) Hierarchical risk factor classification structure is created; (3) reduction of outbound supplier risk by using six sigma methodologies was validated. This project is an attempt to quantify the outbound supplier risk with a suitable case study.
Karthick. M, Manikandan .V. 2014. "FMEA based Quantification analysis of Outbound Supplier Risk and its Resilience". Global Journal of Research in Engineering, Global Journal of Research in Engineering - G: Industrial Engineering GJRE-G Volume 14 (GJRE Volume 14 Issue G1).
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
v1.2
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Total Score: 102
Country: India
Subject: Global Journal of Research in Engineering
Authors: Karthick. M, Manikandan .V (PhD/Dr. count: 0)
View Count (all-time): 377
Total Views (Real + Logic): 1864
Total Downloads (simulated): 134
Publish Date: 2014 01, Wed
Monthly Totals (Real + Logic):
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