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The purpose of this study is to identify, evaluate and develop a structured model to measure the interrelation between critical failure factors (CFFs) that affects the implementation of the sustainable Lean Six Sigma (SLSS) framework in a manufacturing organization. Further solution approaches have been provided that inhibit those CFFs and help in successful implementation of the framework.

To find the interrelation among the selected CFFs and develop a systematic structured model, a total interpretive structural modeling (TISM) approach has been used. A 13-level model for selected CFFs has been formed after the application of the TISM approach. Further classification of CFFs has been performed for a better understanding of their nature through MICMAC analysis.

A total of 26 SLSS CFFs have been identified through a detailed study of case organization, various literature reviews and experience of panel experts toward developing a systematic model of CFFs. The solution approach has been provided by panel experts based on their industrial experiences after observing the role of CFFs in the developed model. Based on the analysis, it was found that most dependent and dominant CFFs affect the implementation of the SLSS framework in the case organization.

This study helps SLSS practitioners, project managers, decision-makers and academicians of manufacturing industries to a better understanding of the failure factors and their interrelations while implementing the SLSS framework in manufacturing organizations. This study also guides the systematic solution approach which helps in tackling such problems that occurred in manufacturing organizations.

In this study, the TISM-based structural model of CFFs for implementing the SLSS framework in manufacturing organizations has been proposed which is a very new effort in the area of a manufacturing environment.

The purpose of this study is to determine the current status of Sustainable Lean Six Sigma (SLSS) practices execution in the industries by identifying the research gaps and also methodologies that are applied by different researchers and practitioners.

To find the current status of SLSS practices all over world, the literature review of the articles available through SCOPUS data base is given in different categories such as a country-wise and year-wise publication of the articles, journal-wise publication of articles, case study implementation focus in industry and data analysis techniques used by the researchers.

The different methodologies applied by the researchers and practitioners have been explained and the gaps for further research are identified. The extensive review of articles of last 18 years revealed that there are various opportunities such as quantitative study, framework modeling on the SLSS, and implementation of developed models in different industries, etc. which are required to be explored.

In the present study, a review of 129 articles for the time span of January 2000 to February 2018 is considered. The SCOPUS database was used for selecting the articles for review. A total of 129 articles were considered for the literature review, and the case study implementation in different industries with the focused areas such as cost reduction, defect reduction, economic, environmental and social aspects was explained.

The purpose of this study is to develop a structured hierarchical interrelationship-based model to evaluate the critical failure factors (CFFs) that affect the sustainable Lean Six Sigma (SLSS) framework implementation in a healthcare organization. Further, solution approaches have been provided that guide to eliminate them.

The CFFs has been identified through empirical study and clustered into six major categories for their better understanding. The interrelation among CFFs has been developed through total interpretive structural modeling (TISM) and classifies the nature using MICMAC technique. Further, prioritized the CFFs based on its driving and dependents power. The methodology enabled the decision-makers, practitioners to systematically analyze the CFFs and develop a structural model for implementing SLSS in the healthcare environment.

A total of 14 leading CFFs have been identified, and 7-level structured interrelationship-based model has been formed. The experts have provided the solution approach after careful analysis of the developed model. Based on the analysis, it was observed that the significant CFFs affect the deployment of the SLSS framework in healthcare organizations.

The structured model and methodological approach have been tested in a healthcare organization. In the future, the approach can be applied in the different service sectors.

The present study has been conducted in a real-time industrial problem. The practitioners, decision-makers and academicians expressed the usefulness of methodology for understanding the CFFs interrelation and their effect on SLSS implementation. This study also guides decision-makers to systematically tackle related problems.

The development of a structured CFFs based model for SLSS framework implementation using the integrated TISM-MICMAC with a detailed solution approach is a unique effort in a healthcare environment.

The Sustainable Lean Six Sigma (SLSS) adoption approach, advancements in Internet technologies and the use of Industry4.0 technologies has resulted in faster customer need fulfilment. The Industry4.0 technologies have resulted in a new paradigm where strategic and operational decisions are in favour of profitability and long-term viability. The purpose of this study is to identify Industry4.0-SLSS practices and sustainable supply chain performance metrics, as well as to develop a framework for decision-makers and managers to make supply chains more sustainable.

The 33 Industry4.0-SLSS practices and 24 performance metrics associated with the sustainable supply chain are shortlisted based on extensive literature review and expert opinion. The Pythagorean Fuzzy Analytical Hierarchy Process (PF-AHP) approach is used to evaluate the weights of Industry4.0-SLSS practices after collecting expert panel opinions. The Weighted Aggregated Sum Product Assessment (WASPAS) methodology used these weights to rank performance metrics.

According to the results of PF-AHP, “Product development competencies (PDC)” are first in the class of major criteria, followed by “Advanced technological competencies (ATC)” second, “Organisational management competencies (OMC)” third, “Personnel and sustainable competencies (PSC)” fourth and “Soft Computing competencies (SCC)” fifth. The performance metric “Frequency of NPD” was ranked first by the WASPAS method.

The proposed paradigm helps practitioners to comprehend Industry4.0 technology and SLSS practices well. The identified practices have the potential to boost the sustainability and supply chain's performance. Organizational effectiveness will benefit from practices that promote a sustainable supply chain and the use of developing technology. Managers can evaluate performance using performance metrics that have been prioritized.

The present study is one of the unique attempts to establish a framework for enhancing the performance of the sustainable supply chain. The idea of establishing Industry4.0-SLSS practices and performance measures is the authors' original contribution.

The COVID-19 pandemic era has severely hampered the economy over the globe. However, the manufacturing organizations across all the countries have struggled heavily, as they were among the least who worked on online mode. The organizations are adopting various innovative quality methodologies to improve their performance. In this regard, they are adopting the Sustainable Lean Six Sigma (SLSS) concept and Industry 4.0 technologies to develop products at a faster rate. The use of Industry 4.0 technologies may reduce material movement and supply chain disruptions with the help of smart intelligent systems. There is a strong synergy between SLSS and Industry 4.0 technologies, resulting in an integrated approach for adoption. This study aims to develop a framework that practitioners can use to adopt Industry 4.0-SLSS practices effectively.

This study portrays 31 Industry 4.0-SLSS practices and 22 performance metrics identified through a literature review to improve the manufacturing supply chain performance. To compute the weights of these practices, the Robust Best–Worst Method (RBWM) is used. The Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method is used to rank performance metrics.

According to the RBWM results, “Process Development Practices (PDP)” are first among the major criteria, followed by “Organizational Management Practices (OMP)” at second, “Technology Adoption Practices (TAP)” at third, “Strategy Management Practices (SMP)” at fourth and “Executive Management Practices (EMP)” at fifth, whereas the PF-CoCoSo method resulted in the performance metric “On time product delivery” ranking first.

The identified practices have the potential to significantly improve the performance of the manufacturing supply chain. Practices that encourage a sustainable manufacturing supply chain and the usage of emerging technology will benefit organizational effectiveness. Managers can assess performance using prioritized performance metrics.

During the COVID-19 pandemic era, this is one of the unique attempts to provide a framework to improve the manufacturing supply chain performance. This study integrates and identifies Industry 4.0-SLSS practices and performance metrics for enhancing overall performance.

This research aims to conduct a literature review of Lean Six Sigma (LSS) in the Indian context and related research publications and apply bibliometric analysis and the author's visualization to map research trends in this area.

This article conducts a bibliometric analysis of LSS-related research in the Indian context using data gathered from Scopus and Web of Science databases from 2011 to 2022. The review provides information on LSS-related research in the Indian context and evaluates performance based on primary sources, authors, keywords, countries, affiliations, and documents. The analysis employs the Biblioshiny app and Bibliometrix R-tool for data analysis and scientific mapping.

The results of the bibliometric analysis indicate that the LSS culture has widely spread in India. The International Journal of Lean Six Sigma and Production Planning and Control were found to be the most productive sources for publishing LSS-related research articles. Antony J. was identified as the most active author in this field, contributing the most over the years. Among all organizations, NITs have conducted the most comprehensive research on LSS, indicating their significant investment of resources and efforts in studying this methodology and its applications in India. Additionally, the study examined the intellectual, social, and conceptual structures to identify implicit gaps and future research opportunities.

The findings of this study can inform academicians, researchers, practitioners, and policymakers about the state-of-the-art and the specifics of the most prolific studies. This study will facilitate their exploration of emerging research areas in LSS.

To the best of the authors knowledge, this is the first bibliometric analysis of LSS in the Indian context, providing an overview of relevant publications published between 2011 and 2022. This study analyzed 194 articles on LSS in India, which can help researchers and academics identify emerging research areas, suitable collaborators, and relevant journals for future publications.

The objective of this paper is to investigate, assess and develop a hierarchical model to evaluate the interrelationship of critical success factors (CSFs) that influence the deployment of Sustainable LSS framework in hospitals. Further, developed model has been validated to investigate its applicability in hospitals towards sustainable LSS implementation.

“Interpretive Structural Modeling” (ISM) has been utilized to develop a convenient hierarchy and contextual relationship of key CSFs throughout the implementation pathway in Indian healthcare industry through systematic literature review and expert opinion, which is ensured by a taxonomy of CSFs using MICMAC (“Matrice d' Impacts Croisés-Multiplication Appliquée á un Classement”) and questionnaire-based survey to empirically validate the model through utilizing “Structural Equation Modelling” (SEM).

In this study, 17 keys CSFs to sustainable LSS implementation in healthcare industry have been investigated, and modeled. “Social and environmental responsibility,” “Financial return and project success stories,” “Top management involvement and leadership to implement Sustainable LSS,” “Availability of required resources, and their efficient utilization” are found to be the most essential CSFs for successful sustainable LSS implementation in healthcare industry. Further, classification of CSFs has been done for better interpretation of their nature using MICMAC approach. Moreover, the applicability of the proposed model has been empirically assessed utilizing SEM.

The scrutiny of data reveals that the initial inputs from experts throughout the ISM pathway could trigger biased inputs into the study and generalization of the results into others, it might be viable that this propounded model might trigger distinct outcomes for contrasting types of healthcare organizations.

This model on sustainable LSS would support the decision-makers, practitioners and researchers to predict key CSFs through deployment and support the existing academic research on sustainable LSS. Accordingly, the focus on the CSFs of the sustainable LSS can be prioritized to diminish waste, and enhance patient satisfaction and safety.

This paper is an original contribution of analysis of CSFs in Indian healthcare industry utilizing an integrated ISM-MICMAC and SEM approach.

The coronavirus (COVID-19) pandemic has led to a surge in demand for health-care facilities, medicines, vaccines and other health-care items. The purpose of this study is to investigate different facets of integrated Green Lean Six Sigma and Industry 4.0 approach in the context of COVID-19 for better healthcare management. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of health-care units and also leads to improving the quality of inpatient care with better safety, hygiene and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas and potential benefits for the adoption of an integrated GLSS-I4.0 approach within health-care facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS-I4.0 has been proposed for better COVID management.

To conduct the literature review, the authors used the preferred reporting items for systematic reviews and meta-analysis and covers relevant papers from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS-I4.0 approach and through insights of experts (academicians and health-care personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention and cure.

The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID health-care management. In this study, the proposed framework reveals that the Internet of Things, big data and artificial intelligence are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management, right from diagnosis, manufacture of items and inpatient and outpatient care of the affected person.

This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of an integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge base in medical areas and provides different novel prospects to combat other medical urgencies.

To the best of the authors’ knowledge, this study is the first of its kind to review different facets of the integrated GLSS-I4.0 approach with a view of the COVID health-care perspective and provides a conceptual framework.

This paper aims to highlight how the six sigma methods helped the medical equipment manufacturing company in finding and analysing the root causes that lead to the reduction in production rate, rejection rates, quality and other major causes that lead to the reduction in productivity of the blood bags manufacturing unit.

Given the critical nature of blood bag manufacturing Six Sigma was chosen as the primary methodology for this research since Six Sigma’s data-driven approach provides a structured framework to identify, analyse and rectify inefficiencies in the production processes. This study proposes the Six Sigma DMAIC (D-Define, M-Measure, A-Analyse, I-Improve, C-Control) encompassing rigorous problem definition, precise measurement, thorough analysis, improvement and vigilant control mechanisms for effectively attaining predetermined objectives.

The paper demonstrates how the Six Sigma principles were executed in a blood bag manufacturing unit. After a detailed and thorough data analysis, it was found that a total of 40 critical-to-quality factors under the five drivers such as Machine, Components, Inspection and Testing, People and Workspace were influential factors affecting the manufacturing of blood bags. From the study, it is identified that the drivers such as inspection and testing, components and machines contribute significantly to increasing productivity.

The paper offers valuable strategic insights into implementing Six Sigma methodologies within the specific context of a blood bag manufacturing unit. The Six Sigma tools and techniques used by the project team to solve issues within the blood bag manufacturing unit can be used for similar healthcare organizations to successfully deploy Six Sigma. The insights from this research might not be directly applicable to other manufacturing facilities or industries but can be used as a guiding reference for researchers and managers.

The current state of scholarly literature indicates a significant absence in the examination of Six Sigma methodologies designed specifically to improve production output in healthcare equipment manufacturing. This paper highlights the application of Six Sigma principles to enhance efficiency in the specific context of blood bag manufacturing.