Quantitative modelling approaches for lean manufacturing under uncertainty

[EN] Lean manufacturing (LM) applies different tools that help to eliminate waste as well as the opera-tions that do not add value to the product or processes to increase the value of each performedactivity. Here the main motivation is to study how quantitative modelling approaches can supportLM tools even under system and environment uncertainties. The main contributions of the articleare: (i) providing a systematic literature review of 99 works related to the modelling of uncertaintyin LM environments; (ii) proposing a methodology to classify the reviewed works; (iii) classifyingLM works under uncertainty; and (iv) identify quantitative models and their solution to deal withuncertainty in LM environments by identifying the main variables involved. Hence this article pro-vides a conceptual framework for future LM quantitative modelling under uncertainty as a guide foracademics, researchers and industrial practitioners. The main findings identify that LM under uncer-tainty has been empirically investigated mainly in the US, India and the UK in the automotive andaerospace manufacturing sectors using analytical and simulation models to minimise time and cost.Value stream mapping (VSM) and just in time (JIT) are the most used LM techniques to reduce wastein a context of system uncertainty.The research leading to these results received funding fromthe project 'Industrial Production and Logistics Optimizationin Industry 4.0' (i4OPT) (Ref. PROMETEO/2021/065) granted by the Valencian Regional Government; and grant PDC2022-133957-I00 funded by MCIN/AEI /10.13039/501100011033 and by European Union Next Generation EU/PRTR.Rojas, T.; Mula, J.; Sanchis, R. (2023). Quantitative modelling approaches for lean manufacturing under uncertainty. International Journal of Production Research. 1-27. https://doi.org/10.1080/00207543.2023.229313812

End-of-life vehicle (ELV) recycling management: improving performance using an ISM approach

With booming of the automobile industry, China has become the country with increasing car ownership all over the world. However, the end-of-life vehicle (ELV) recycling industry is at infancy, and there is little systematic review on ELV recycling management, as well as low adoption amongst domestic automobile industry. This study presents a literature review and an interpretive structural modeling (ISM) approach is employed to identify the drivers towards Chinese ELV recycling business from government, recycling organizations and consumer’s perspectives, so as to improve the sustainability of automobile supply chain by providing some strategic insights. The results derived from the ISM analysis manifest that regulations on auto-factory, disassembly technique, and value mining of recycling business are the essential ingredients. It is most effective and efficient to promote ELV recycling business by improving these attributes, also the driving and dependence power analysis are deemed to provide guidance on performance improvement of ELV recycling in the Chinese market

Barriers in green lean implementation: a combined systematic literature review and interpretive structural modelling approach

Green Lean has recently emerged as an alternative strategy for organizations to pursue both operational and sustainability excellence. The interest on this approach has rapidly risen in both academic and industry circles. However, despite this interest, very limited research has focused on its implementation, and no research has investigated the barriers that hinder the success of such activity. This study investigates the Green Lean implementation barriers and their contextual relationships and effects on the integration and deployment of this approach. A Systematic Literature Review (SLR), Interpretative Structural Modelling and fuzzy Matriced’ Impacts Croise’s Multiplication Appliqée a UN Classement (MICMAC) analyzes were carried out. Fifteen barriers were extracted from the SLR and then validated in consultation with industry and academic experts. The Interpretive Structural Modelling (ISM) method was used to understand the relationship between the fifteen barriers and to develop a hierarchical model of these. The different barriers were classified into ‘linkage’ and ‘dependent’ barriers by using MICMAC analysis. The results suggested that all the identified barriers play an important role, and hence can equally act as a significant hurdle to the implementation of Green Lean projects. This study can help managers and policy makers in better understanding these barriers. Thus, they can be assisted in managing and prioritizing barriers towards the successful implementation of Green Lean initiatives for better financial and environmental performance.N/

Identification of Critical Success Factors (CSF’s) to implement Green Supply Chain Management (GSCM) in an automobile industry using Analytical Hierarchy Process (AHP) technique

Due to globalization, supply chains have grown more lengthy and complex and creating an adverse effect on environment, which paved a way in emergence of Green Supply Chain, management (GSCM).Total 77 papers dealing with GSCM were reviewed to understanding researcher’s contribution in GSCM literature. Automobile industry is one of the largest polluter amongst all industries contributing 80% of total CO. In recent stretch most of automobile industries, alter their supply chain to GSCM to increase their competitive advantage. This study deals with the application of AHP method for evaluating and ranking Critical success factors for automobile company to implement GSCM. The weightages were attained based on the pair wise comparison of attributes with the help of industrial experts and academia. The results of the study revealed the most significant CSF’s for implementation of GSCM in automobile industry

Modeling and analysing the barriers to the acceptance of energy-efficient appliances using an ISM-DEMATEL approach

Electricity savings from energy-efficient appliances (EEAs) may have a significant impact on reducing global warming. There are several barriers confronted by EEAs, which have lowered their acceptance rate. The current study identifies and highlights key barriers to strengthening domestic sector adoption of EEAs in developing countries. In the current study, thirteen barriers were discovered by an indepth literature review and the judgement of experts as well. Further, integrated “Interpretive Structural Modeling” (ISM) and “Decision Making Trial and Evaluation Laboratory” (DEMATEL) approaches are utilized to evaluate barriers. The ISM technique is implemented to categorize barriers into distinct hierarchy levels, and “Cross-Impact Matrix Multiplication Applied to Classification” (MICMAC) analysis to divide barriers among four clusters “independent, linkage, dependent, and autonomous”. Moreover, the DEMATEL methodology is applied to classify the barriers among cause and effect clusters. The integrated ISM and DEMATEL approach suggests that the topmost influencing barriers to the acceptance of EEAs are the lack of Government policies and initiatives, lack of attractive loan financing, and subsidized energy prices. This study would help researchers, regulators, producers, policymakers, and consumers to comprehend the need for additional developments and understand that the adoption of EEAs is a current need. Overall, the results of this study expedite stakeholders with the key barriers that may assist to enhance the acceptance of EEAs within the domestic sector. An extensive literature survey showed a dearth of studies for the identification, modeling, and analysis of barriers collectively. Therefore, the current work utilized the ISM and DEMATEL approaches to fill the gap and to provide more comprehensive knowledge on barriers related to the acceptance of EEA

The analysis of critical success factors for successful kaizen implementation during the COVID-19 pandemic: a textile industry case study

Purpose The primary objective of this research is to determine critical success factors (CSFs) that enable textile enterprises to effectively implement Kaizen, a Japanese concept of continuous development, particularly during disruptive situations. The study aims to provide insights into how Kaizen is specifically employed within the textile sector and to offer guidance for addressing future crises. Design/methodology/approach This study employs a structured approach to determine CSFs for successful Kaizen implementation in the textile industry. The Triple Helix Actors structure, comprising business, academia and government representatives, is utilized to uncover essential insights. Additionally, the Matriced Impacts Croises-Multiplication Applique and Classement (MICMAC) analysis and interpretative structural modeling (ISM) techniques are applied to evaluate the influence of CSFs. Findings The research identifies 17 CSFs for successful Kaizen implementation in the textile industry through a comprehensive literature review and expert input. These factors are organized into a hierarchical structure with 5 distinct levels. Additionally, the application of the MICMAC analysis reveals three clusters of CSFs: linkage, dependent and independent, highlighting their interdependencies and impact. Originality/value Major contribution of this study is understanding how Kaizen can be effectively utilized in the textile industry, especially during disruptive events. The combination of the Triple Helix Actors structure, MICMAC analysis and ISM provides a unique perspective on the essential factors driving successful Kaizen implementation. The identification of CSFs and their categorization into clusters offer valuable insights for practitioners, policymakers and academia seeking to enhance the resilience and sustainability of the textile industry

Identification of Critical Factors and Their Interrelationships to Design Agile Supply Chain : Special Focus to Oil and Gas Industries

Purpose – This research attempted to identify the most critical factors and their inter-relationships to ensure designing agile supply chain, especially in oil and gas industry. This factors identification process is performed through developing a conceptual framework and the use of Interpretive Structural Modelling (ISM) tool. Design/methodology/approach – This study is conducted through an extensive literature review and questionnaires survey to identify and refine the critical factors that ensure the agile supply chain in oil and gas industry. In addition, several brainstorming sessions with the experts in the field of oil and gas industries were organized with the objective to interpret the contextual inter-relationships between the identified factors. The outcomes from the literature reviews, interview questions and experts’ opinions were used to develop a diagraph and MICMAC analysis to know the drivers of agility in supply chain. Findings –From this study, 34 enablers and 12 factors were identified, which are responsible to ensure agile supply chain in oil and gas industry. Out of these identified factors, top management commitment, strategic alignment, competency of management and integration of information and systems technology are found to be the critical drivers of supply chain agility. On the other hand, government regulations, transportation and logistics flexibility and production planning and control falls under the category of dependent factors. Originality/value – The identified factors and their interrelationships can be a valuable aid to ensure and measure the agility in supply chain, especially in oil and gas industry. These identified factors and their defined consequences will help managers and concerned authorities in oil and gas industry to take better decision to improve the agility level of their supply chain.©2020 Springer Nature. This is a post-peer-review, pre-copyedit version of an article published in Global Journal of Flexible Systems Management. The final authenticated version is available online at: http://dx.doi.org/10.1007/s40171-020-00247-5fi=vertaisarvioitu|en=peerReviewed

MODELLING FRAMEWORK FOR CRITICAL SUCCESS FACTORS OF GREEN SUPPLY CHAIN MANAGEMENT-AN INTEGRATED APPROACH OF PARETO, ISM AND SEM

The study aimed in identifying Green supply chain critical success factors, develop and validate the framework through integrated approach of ISM, MICMAC and SEM so as to promote green practices throughout the supply chain activities in Indian manufacturing sectors. Interpretive structural modelling(ISM) is applied to develop hierarchical contextual relationship among identified critical success factors via Pareto analysis. The methodology then follows classification of success factors into four clusters by Matrice d’ Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) and statistical validation of the ISM model through Structural Equation Modelling(SEM) by AMOS. In this study, 16 critical success factors of Green supply chain practices for manufacturing industries were identified, followed by development of an ISM model using 16 critical success factors, later the model was statistically verified that identified nine CSF’s responsible for generating SEM model by satisfying all the model fit indices.The linkage variables identified are Green manufacturing, Green Procurement, Green marketing and Distribution, Green purchasing, Supplier cooperation, Customer cooperation, Environmental strategies and management, Environmental Participation and Green training that are forming the driving force for practicing green supply chain. Research limitations/implications: The results of the study are restricted to manufacturing industries, which might vary when applied for other sectors. The developed model on green supply chain management practices would help policy makers, decision makers, researchers and industry professionals to anticipate potential success factors to implement green supply chain practices. Accordingly, the focus on critical success factors would be prioritized for obtaining better performance of supply chain and greening the chain

Application of additive manufacturing for mass customisation: understanding the interaction of critical barriers

Additive Manufacturing (AM) technology presents a very optimistic case for its application for mass customisation. Even though theoretically suitable, practically several critical barriers inhibit its implementation. Thus, this paper attempts to identify those barriers and also understand the dynamic interaction among them. The barriers were identified by a detailed literature review and validated by expert opinions. Interpretative Structural Modelling (ISM) was applied to determine the mutual influences among the barriers. It was also able to ascertain the level of the barriers and categorise them based on their driving power and dependence. The results are highly useful for industry practitioners to determine the interventions required to overcome the most dominant barriers

Scoping review of the readiness for sustainable implementation of lean six sigma projects in the manufacturing sector

This work presents a synthesis of current literature published from 2010 to provide an overall understanding of the sustainable implementation of Lean Six Sigma (LSS) projects in terms of project approaches rather than outcomes. A comprehensive and validated ten-step model was applied to conduct a scoping review (SR) with the following three broad phases: “review planning”, “review execution”, and “review reporting”. The analysis shows that while a few geographically and methodologically broad research studies have been conducted on LSS and green manufacturing integration, no studies have examined organisational culture or conducted readiness assessments on the sustainable implementation of LSS projects in the manufacturing sector. The present study contributes to existing knowledge by describing the current state of research on green LSS integration. The study also identifies a lack of research on the deployment of sustainable LSS projects for manufacturers. Further empirical analyses that include case studies must be conducted to assess the negative environmental impacts of LSS projects. This study serves as an initial call for practitioners and research scholars to favour the sustainable deployment of LSS projects in manufacturing alongside the use of traditional approaches with a focus on costs, quality and delivery.N/