Barriers Prioritization of the Indian Steel Industry Supply Chain: Applying AHP and Fuzzy AHP Method

2021 ◽  
pp. 097226292110656
Author(s):  
Rupesh Kumar ◽  
Saurabh Tiwari ◽  
Surendra Kansara
Keyword(s):  
Supply Chain ◽  
Steel Industry ◽  
Fuzzy Ahp ◽  
Ahp Method ◽  
Analytical Hierarchical Process ◽  
Theoretical Examination ◽  
Multicriteria Methods

This study seeks to identify possible key barriers in the supply chain of the Indian steel industry. Each of these hindrances has a significance in serving the store network and refining the economy of India. The study is a mix of theoretical and useful structures, which would zero in on those critical barriers in the steel supply chain. It includes a theoretical examination of the barriers in the Indian steel industry and ranking of these barriers using multicriteria methods, that is, analytical hierarchical process (AHP) and fuzzy analytical hierarchical process (FAHP) approaches. The main finding is the identification of key barriers in the Indian steel industry supply chain and prioritizing them according to the severity of their impact. Eleven potential key barriers have been considered in the study for analysis. There can be more barriers in the Indian steel industry. This study exposes the application of both methods, that is, AHP and FAHP, for ranking identified barriers.

scholarly journals Interval-valued Pythagorean fuzzy AHP method-based supply chain performance evaluation by a new extension of SCOR model: SCOR 4.0

2020 ◽  
Author(s):  
Ertugrul Ayyildiz ◽  
Alev Taskin Gumus
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
Supply Chains ◽  
Operations Management ◽  
Fuzzy Ahp ◽  
Evaluation Model ◽  
Ahp Method ◽  
Scor Model ◽  
Globalizing World ◽  
Best Worst Method

Abstract Supply chain operations reference (SCOR) is a combined benchmarking, business process reengineering, and best practices, and it also references a model that is intended to be an industry standard. SCOR model is one of the best models to describe supply chain activities in operations management for research and practice alike. There are radical changes in the structure of supply chains as well as developing technology in today’s information age. The purpose of this paper is to extend the SCOR model with new metrics related to Industry 4.0 and digitalization to understand and evaluate the performance of supply chains. New metrics added to the SCOR model and a novel SCOR 4.0 model is proposed. The novel performance evaluation model is structured as a three-level hierarchical structure to evaluate the supply chain. This problem is handled as a multi-criteria decision-making problem. This study uses the hybrid Best worst method and Pythagorean fuzzy AHP method to determine the weights of metrics. SCOR model is adapted to performance evaluation of the supply chain in the globalizing world. The most important metrics on the supply chain performances are determined and classified. Level 1 metrics are evaluated by Best worst method and their inner levels are evaluated by the Pythagorean fuzzy AHP method and the importance weights of each level 2 and level 3 metrics are obtained. A real application for the oil supply chain is presented to show the applicability of the proposed model. It is aimed to show the SCOR 4.0 model can be used by both public and private sectors to improve their supply chain strategies in globalizing world.

scholarly journals Assessment of Water Quality using Fuzzy-AHP and TOPSIS

2021 ◽  
Vol 40 ◽  
pp. 02002
Author(s):  
Asmita Sonavane ◽  
Devyani Narkhede ◽  
Shruti Pawar ◽  
Tabassum Maktum
Keyword(s):  
Water Quality ◽  
Water Samples ◽  
Fuzzy Ahp ◽  
Quality Level ◽  
Relative Importance ◽  
Ahp Method ◽  
Analytical Hierarchical Process ◽  
Quality Of Water ◽  
Order Preference

The quality of water available to people has deteriorated because of the vast increase in global industries. The overall quality of water has reduced due to the high use of fertilizers in farms and chemicals in sectors such as mining and construction. The quality of water has a direct impact on the health of humans and hence it is necessary to evaluate the quality of drinking water. The quality of water is dependent on various substances like pH, ammonia, iron, arsenic etc. present in water. If these parameters are available in an appropriate amount in water then only the water is considered as of good quality. The problem of assessing water quality is usually considered as multi-criteria decision problem. In this paper an approach to evaluate quality of water using Fuzzy Analytical Hierarchical Process (Fuzzy-AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed. The parameters which are considered for evaluation include Arsenic, Ammonia , Iron , Nitrate , Dissolved Oxygen and Ph. The relative importance of these parameters is utilized while applying the Fuzzy-AHP process and weights for each parameter are computed. The various datasets containing values for considered parameters are collected and the weights are used to assign quality levels to these water samples. The paper also gives the performance analysis of the proposed method in terms of accuracy. The accuracy is measured in terms of how many water samples are assigned correct quality level and the results show that the proposed method has better accuracy as compared to traditional AHP and Fuzzy-AHP method.

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