Assessment of Lean Supply Chain Practices in Indian Automotive Industry

2020 ◽  
pp. 097215091989023
Author(s):  
Rohit Kumar Singh ◽  
Sachin Modgil
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Performance Measures ◽  
Automotive Industry ◽  
Management Practices ◽  
Performance Practices ◽  
Future Goals ◽  
Lean Practices ◽  
Effective Performance ◽  
Lean Supply Chain

The purpose of this study is to explore the effect of lean practices on performance measures in the automotive industry and identify the lean criteria that can have significant impact on automotive supply chain. The identified lean practices can serve as a template to enhance the performance of a supply chain. The present study offers a multi-criteria decision-making approach to identify the effective performance practices in automotive lean supply chain. The decision-making trial and evaluation laboratory (DEMATEL) was applied on a matrix of observed values and the actual effect of proposed practices was observed. Further it was confirmed with the help of fuzzy- Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR; that means multicriteria optimization and compromise solution, with pronunciation). The criteria which had the most impact are proposed for achieving the future goals of leanness. It was found that among the lean criteria considered, quality management, information management and customer management practices influence the key performance measures more than others. Although DEMATEL and fuzzy-VIKOR were applied for situation leading to setting up of priorities of factors that considered affecting automotive manufacturer, the proposed methodology can be applied in diverse industrial settings. The present study may help decision-makers to device the appropriate strategy in identifying major practices that influence the lean supply chain.

Comparative analysis of ranking the lean supply chain enablers: An AHP, BWM and fuzzy SWARA based approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hemant Sharma ◽  
Nagendra Sohani ◽  
Ashish Yadav
Keyword(s):  
Supply Chain ◽  
Literature Review ◽  
Lean Manufacturing ◽  
Production Systems ◽  
Initial Step ◽  
Content Type ◽  
Lean Practices ◽  
Manufacturing Organization ◽  
Good Productivity ◽  
Lean Supply Chain

PurposeIn the recent scenario, there has been an increasing trend toward lean practices and implementation in production systems for the improvement of an organization’s performance as its basic nature is to eliminate the wastes. The increasing interest of customers in customized products and the fulfillment of customers’ demand with good productivity and efficiency within time are the challenges for the manufacturing organization; that is why adopting lean manufacturing concept is very crucial in the current scenario.Design/methodology/approachIn this paper, the authors considered three different methodologies for fulfilling the objective of our research. The analytical hierarchy process, best–worst method and fuzzy step-wise weight assessment ratio analysis are the three methods employed for weighting all the enablers and finding the priority among them and their final rankings.FindingsFurther, the best results among these methodologies could be used to analyze their interrelationships for successful lean supply chain management implementation in an organization. In this paper, 35 key enablers were identified after the rigorous analysis of literature review and the opinion of a group of experts consisting of academicians, practitioners and consultants. Thereafter, the brainstorming sessions were conducted to finalize 28 lean supply chain enablers (LSCEs).Practical implicationsFor lean manufacturing practitioners, the result of this study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process.Originality/valueThis paper is the first of the research papers that considered deep literature review of identified LSCEs as the initial step, followed by finding the best priority weightage and developing the ranking of various lean enablers of supply chain with the help of various methodologies.

Emergy Analysis and Supply Chains

2020 ◽  
pp. 72-92
Author(s):  
Lojain Alkhuzaim ◽  
Joseph Sarkis
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Performance Measures ◽  
Circular Economy ◽  
Management Practices ◽  
Emergy Analysis ◽  
Sustainable Supply Chain ◽  
Chain Management ◽  
Real Value ◽  
Stakeholder Pressures

The growth in stakeholder pressures, broader sustainable supply chain management practices, and new economic models such as circular economy, has made sustainability a priority for organizations and their supply chains. To be able to manage their activities, programs, processes, and strategies, organizations have adopted and developed performance measures. Unlike other performance measures, emergy analysis quantitatively provides a real value for the work of nature to evaluate performance beyond the traditional measures that have been traditionally presented in the supply chain literature. This chapter offers an introductory explanation of how and what emergy analysis can offer in evaluating the environmental performance of supply chains. It will also consider not only the capabilities of emergy analysis but also the limitations and much-needed research to advance both fields, EA and SSCM.

Agility and lean practices as antecedents of supply chain social sustainability

2020 ◽  
Vol 40 (10) ◽  
pp. 1589-1611 ◽  
Author(s):  
Vishnu Nath ◽  
Rajat Agrawal
Keyword(s):  
Supply Chain ◽  
Management Practices ◽  
Structural Model ◽  
Social Sustainability ◽  
Operational Performance ◽  
Validity And Reliability ◽  
Content Type ◽  
Sustainability Performance ◽  
Lean Practices ◽  
Sustainability Practices

PurposeThe present study aims to empirically investigate whether supply chain agility and lean management practices are antecedents of supply chain social sustainability.Design/methodology/approachData were collected from 311 supply chain practitioners from the Indian manufacturing sector. Confirmatory factor analysis was employed to test the validity and reliability of the measures used, and a structural model was analyzed to test the hypotheses of the current study.FindingsThe results indicate that agility and lean practices are significant antecedents of social sustainability orientation as well as social sustainability performance. The results also suggest that agility has a significant indirect effect on operational performance via social sustainability orientation, basic social sustainability practices as well as agility is indirectly affecting social sustainability performance via social sustainability orientation and basic social sustainability practices.Practical implicationsThe results of the present study have implications for managers that want to make their supply chain more socially sustainable.Originality/valueThe study is unique in the sense that it empirically links agility and lean practices with social sustainability orientation, social substantiality performance and operational performance in supply chains.

scholarly journals Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 579 ◽  
Author(s):  
Ilyas Mzougui ◽  
Silvia Carpitella ◽  
Antonella Certa ◽  
Zoubir El Felsoufi ◽  
Joaquín Izquierdo
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Systems Engineering ◽  
Automotive Industry ◽  
Economic Losses ◽  
Joint Analysis ◽  
Fuzzy Decision Making ◽  
Support Tool ◽  
Supply Chain Risks ◽  
Criticality Analysis

Supply chains are complex networks that receive assiduous attention in the literature. Like any complex network, a supply chain is subject to a wide variety of risks that can result in significant economic losses and negative impacts in terms of image and prestige for companies. In circumstances of aggressive competition among companies, effective management of supply chain risks (SCRs) is crucial, and is currently a very active field of research. Failure Mode, Effects and Criticality Analysis (FMECA) has been recently extended to SCR identification and prioritization, aiming at reducing potential losses caused by lack of risk control. This article has a twofold objective. First, SCR assessment is investigated, and a comprehensive list of specific risks related to the automotive industry is compiled to extend the set of most commonly considered risks. Second, an alternative way of calculating the Risk Priority Number (RPN) is proposed within the FMECA framework by means of an integrated Multi-Criteria Decision-Making (MCDM) approach. We give a new calculation procedure by making use of the Analytic Hierarchy Process (AHP) to derive factors weights, and then the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) to evaluate the new factor of “dependence” among the risks. The developed joint analysis constitutes a risk analysis support tool for criticality in systems engineering. The approach also deals with uncertainty and vagueness associated with input data through the use of fuzzy numbers. The results obtained from a relevant case study in the automotive industry showcase the effectiveness of this approach, which brings important value to those companies: When planning interventions of prevention/mitigation, primary importance should be given to (1) supply chain disruptions due to natural disasters; (2) manufacturing facilities, human resources, policies and breakdown processes; and (3) inefficient transport.

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