A. Noorul Haq

Analysis of interactions of criteria and sub-criteria for the selection of supplier in the built-in-order supply chain environment

The supplier decision-making problem is complicated by several criteria and sub-criteria. The criteria and sub-criteria used may vary across different product categories and situations. The aim of this article is to analyse the interaction of criteria and sub-criteria that are used to select the supplier for the built-in-order supply chain environment in the original equipment manufacturing company. The paper aims to demonstrate how the model can help in solving such decisions in practice. This paper uses the Interpretive Structural Modeling (ISM) methodology to understand the interactions among the criteria, which influences the supplier selection. The effectiveness of the ISM model is illustrated using a case study taken in a company in the southern part of India.

Design of an integrated supplier selection and multi-echelon distribution inventory model in a built-to-order supply chain environment

The paper deals with the development of an integrated supplier selection and multi-echelon distribution inventory model (MEDIM) for the original equipment manufacturing company in a built-to-order supply chain environment using fuzzy analytical hierarchy process (FAHP) and a genetic algorithm. The main objective is to design the integrated qualitative decision-making of the supplier selection model using FAHP with that of the quantitative mathematical model for the distribution inventory supply chain using a genetic algorithm to the built-to-order environment. The proposed model is validated by considering the case study in a tyre industry in Southern India. The software used for programming is C++ language.

ANALYSIS OF CLOSED LOOP SUPPLY CHAIN USING GENETIC ALGORITHM AND PARTICLE SWARM OPTIMISATION

There are many reasons for the growing interest in reverse logistics. The most prominent reasons are the growing concern for the environment and cost reduction. Next to environment, consumers demand for clean manufacturing and recycling. Hence, customers and retailers expect original equipment manufacturers to set up a proper reverse logistics system and expect the returned products to be processed and recovered in an environmentally responsible way and another reason is cost reduction. A well-managed reverse logistics programme can provide important cost savings in procurement, disposal, inventory carrying and transportation. In this context, looking at the entire supply chain is the best starting point for solutions. Supply chain management aims at the integration of traditional ‘forward’ supply chain processes, avoiding local optimisation by emphasising integrality. The main objective of this paper is to design an integrated forward logistics multi-echelon distribution inventory supply chain model (FLMEDIM) and closed loop multi-echelon distribution inventory supply chain model (CLMEDIM) for the built-to-order environment using genetic algorithm and particle swarm optimisation. In this paper, the proposed model is validated by considering two case studies: one for a tyre manufacturer and the other for a plastic goods manufacturer both located in the southern part of India. This paper utilises the multi-echelon distribution inventory supply chain model proposed by Haq and Kannan (2006a) for the FLMEDIM. The software used was written in the Java programming language.

Analyzing supplier development criteria for an automobile industry

Purpose – The purpose of this paper is to present an approach to identify and rank the criteria used for the supplier development using interpretative structural modeling (ISM).Design/methodology/approach – The paper develops a framework to analyze the interactions among the criteria such as competitive pressure, evaluation and certification system, incentives, supplier development programs, inter‐organizational communication, buyer‐supplier relationship, supplier commitment, supplier performance, asset specificity, joint action, trust, long‐term strategic goals, top management support, purchasing performance, and supplier strategic objective for the supplier development using ISM. The developed framework is illustrated using a case study taken in an automobile firm.Findings – The paper contributes to research in supply chain management (SCM) and particularly in supplier development. Research in the area of SCM has intensified in recent years for a number of reasons. Managers have now realized that action...

ANALYSIS AND SELECTION OF GREEN SUPPLIERS USING INTERPRETATIVE STRUCTURAL MODELLING AND ANALYTIC HIERARCHY PROCESS

Due to recent changing environmental requirements, increasing attention is given to developing Environmental Management (EM) strategies for the supply chain. A number of organisations are contemplating the integration of environmental practices into their strategic plans. The daily operations are continuously increasing and numerous initiatives have provided incentives for organisations to become more environmental friendly. Some of these regulation-driven programmes are mandatory, but increasingly, numerous voluntary environmental programmes are also introduced by organisations. This study analyses the interaction of criteria that is used to select the green suppliers who address the environmental performance using Interpretive Structural Modelling (ISM) and Analytic Hierarchy Process (AHP). The effectiveness of the ISM and AHP model is illustrated using a automobile company in the southern part of India.

Pressure analysis for green supply chain management implementation in Indian industries using analytic hierarchy process

Due to growing awareness about environment protection, firms are forced to implement environmental practices to enhance their green image. In recent times, academicians and practitioners have shown interest in green marketing and green supply chain management (GSCM). Fields of green branding and sustainability have seen special interest from different business disciplines including information management, marketing, supply chain management, etc. Due to economical and ecological impact, there is a growing concern for the environment and related critical issues. Pressure on the environment is dynamic and diverse, and demands new levels of accountability, financial commitment and supply chain capabilities. Indian manufacturing industries have started adopting green concepts in their supply chain management giving special attention to environmental issues based on pressures from different directions, e.g. customer pressure, government regulations etc. Yet, industries struggle hard to identify essential pressures for implementation of GSCM. This work focuses mainly on identifying such pressures for implementation of GSCM. Initially 65 pressures were identified through detailed literature and categorised into six groups. Then common acceptable pressures were identified through a questionnaire survey from different industrial sectors in Phase 1. Finally, essential pressures are prioritised with the help of analytic hierarchy process in Phase 2.

Simulation and parameter optimization of flux cored arc welding using artificial neural network and particle swarm optimization algorithm

Flux cored arc welding (FCAW) process is a fusion welding process in which the welding electrode is a tubular wire that is continuously fed to the weld area. It is widely used in industries and shipyards for welding heavy plates. Welding input parameters play a very significant role in determining the quality of a weld joint. This paper addresses the simulation of weld bead geometry in FCAW process using artificial neural networks (ANN) and optimization of process parameters using particle swarm optimization (PSO) algorithm. The input process variables considered here include wire feed rate (F); voltage (V); welding speed (S) and torch Angle (A) each having 5 levels. The process output characteristics are weld bead width, reinforcement and depth of penetration. As per the statistical design of experiments by Taguchi L25 orthogonal array, bead on plate weldments were made. The experimental results were fed to the ANN algorithm for establishing a relationship between the input and output parameters. The results were then embedded into the PSO algorithm which optimizes the process parameters subjected to the objectives. In this study the objectives considered are maximization of depth of penetration, minimization of bead width and minimization of reinforcement.

Integration of closed loop distribution supply chain network and 3PRLP selection for the case of battery recycling

The increased use of lead acid batteries in automotive vehicles will increase the demand for lead and to meet this increasing demand used batteries are identified as a most important source of lead through recycling. Since recycled lead is a costly commodity, the market potential for reclaiming the secondary lead from the used batteries has been growing. For this purpose, a multi-echelon, multi-product closed loop distribution supply chain (CLDSC) network is designed and integrated with the selection process of best third-party reverse logistics provider (3PRLP) to achieve cost efficiency and delivery schedules in reverse logistics. A fuzzy multi-criteria decision-making (FMCDM) model based on the VIKOR method is used for the selection of best 3PRLP. To optimise the proposed network, a mixed integer linear programming model is developed and solved using LINGO 8.0 optimisation software package for the case of battery recycling and decisions are made regarding raw material procurement from the supplier, production, distribution and amount of reclaimed/recycled material. Since the main aim of this study is to optimise the CLDSC network, the supply chain cost of the forward distribution supply chain network is found and compared with the total supply chain cost of the CLDSC network and the results show that a cost reduction can be achieved in the case of CLDSC network. Finally, model experiments for varying rate of returns are conducted to study the percentage of cost savings.

AN INTEGRATED APPROACH FOR SELECTING A VENDOR USING GREY RELATIONAL ANALYSIS

This paper develops a new model for evaluating and selecting the vendor using an integrated approach of Grey Relational Analysis (GRA) along with an Analytical Hierarchy Process (AHP) in a Forward Supply Chain Model (FSCM). The paper aims to demonstrate how the model can help in solving such decisions in practice. It also examines the structure of the decision hierarchy, whether it can represent vendor selection decisions in reality and whether it covers all key factors affecting vendor selection choices. The effectiveness of the GRA model is illustrated with an Original Equipment Manufacturing (OEM) industry in southern part of India and the results of GRA were validated using the result obtained from AHP. The proposed model helps the industry to effectively select the vendor.

An application of the Analytical Hierarchy Process and Fuzzy Analytical Hierarchy Process in the selection of collecting centre location for the reverse logistics Multicriteria Decision-Making supply chain model

This paper aims at developing an effective and efficient Multicriteria Decision-Making (MCDM) model for selecting the collecting centre location in the Reverse Logistics Supply Chain Model (RLSCM) using the Analytical Hierarchy Process (AHP) and Fuzzy Analytical Hierarchy Process (FAHP). The paper aims at demonstrating how the model can help in solving such decisions in practice. The effectiveness of the model is illustrated using a case study taken in a tyre manufacturing industry located in the southern part of India and validated the results of AHP model using the result obtained from FAHP model. The proposed model helps the industry to select the collecting centre location effectively for the RLSCM.