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To achieve changing customer demands, organizations are striving hard to embrace cutting-edge technologies facilitating a high level of customization. Industry 4.0 (I4.0) implementation aids in handling big data that could help generate customized products. Lean six sigma (LSS) depends on data analysis to execute complex problems. Hence, the present study aims to empirically examine the key operational characteristics of LSS and I4.0 integration such as principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 technologies and performance measures.

To stay competitive in the market and quickly respond to market demands, industries need to go ahead with digital transformation. I4.0 enables building intelligent factories by creating smart manufacturing systems comprising machines, operators and information and communication technologies through the complete value chain. This study utilizes an online survey on Operational Excellence professionals (Lean/Six Sigma), Managers/Consultants, Managing Directors/Executive Directors, Specialists/Analysts/Engineers, CEO/COO/CIO, SVP/VP/AVP, Industry 4.0 professionals and others working in the field of I4.0 and LSS. In total, 83 respondents participated in the study.

Based on the responses received, reliability, exploratory factor analysis and non-response bias analysis were carried out to understand the biasness of the responses. Further, the top five operational characteristics were reported for LSS and I4.0 integration.

One of the limitations of the study is the sample size. Since I4.0 is a new concept and its integration with LSS is not yet explored; it was difficult to achieve a large sample size.

Organizations can utilize the study findings to realize the top principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 tools and performance measures with respect to LSS and I4.0 integration. Moreover, these operational characteristics will help to assess the organization's readiness before and after the implementation of this integration.

The authors' original contribution is the empirical investigation of operational characteristics responsible for I4.0 and LSS integration.

The integration of Lean Six Sigma (LSS) and Industry 4.0 (I4.0) is in the nascent stage and promises to achieve new optimums in operational excellence. This study aims to empirically examine the enablers, barriers, benefits and application of I4.0 technologies in LSS and I4.0 integration.

A pilot survey was chosen as an appropriate methodology, as LSS and I4.0 integration is still budding. The survey targeted senior quality management professionals, quality managers, team leaders, LSS Black Belts and operations managers to collect the relevant research data. The questionnaire was sent to 200 respondents and received 53 valid responses.

This study reveals that “top management support” is an essential enabler for LSS and I4.0 integration. The most significant barrier was “poor understanding of data analysis” and “lack of top management support”. The findings further illustrated that LSS and I4.0 integration resulted in greater efficiency, lower operational costs, improved productivity, improved customer satisfaction and improved quality. Regarding I4.0 technology integration at different phases of LSS, the authors noticed that big data analytics and artificial intelligence (AI) are the most prominent technologies used in all phases of LSS implementation.

One of the limitations of this study is the sample size. LSS and I4.0 are emerging concepts; hence, obtaining a larger sample size is difficult. In addition, the study used non-parametric tests to analyse the data. Therefore, future studies should be conducted with large sample sizes across different continents and countries to understand differences in the key findings.

The outcomes of this study can be useful for organisational managers to understand the enablers and barriers before integrating LSS and I4.0 for adoption in their organisations. Secondly, it helps to convince top management and human resource personnel by providing a list of benefits of LSS and I4.0 integration. Finally, it can help decision-makers understand which I4.0 technologies can be used in different stages of LSS methodology.

LSS and I4.0 integration was studied at a conceptual level. This is the first empirical study targeted toward understanding the LSS and I4.0 integration. In addition, this study investigates the application of widely used I4.0 technologies in different phases of LSS.

Lean Six Sigma (LSS) implementation follows a structured approach called define-measure-analyze-improve-control (DMAIC). Earlier research about its application in emergency healthcare services shows that it requires organizational transformation, which many healthcare setups find difficult. The Kotter change management model facilitates organizational transformation but has not been attempted in LSS settings till now. This study aims to integrate the LSS framework with the Kotter change management model to come up with an integrated framework that will facilitate LSS deployment in emergency health services.

Two-stage Delphi method was conducted by using a literature review. First, the success factors and barriers of LSS are investigated, especially from an emergency healthcare point of view. The features and benefits of Kotter's change management models are then reviewed. Subsequently, they are integrated to form a framework specific to LSS deployment in an emergency healthcare set-up. The elements of this framework are analyzed using expert opinion ratings. A new framework for LSS deployment in emergency healthcare has been developed, which can prevent failures due to challenges faced by organizations in overcoming resistance to changes.

The eight steps of the Kotter model such as establishing a sense of urgency, forming a powerful guiding coalition, creating a vision, communicating the vision, empowering others to act on the vision, planning for and creating short-term wins, consolidating improvements and producing still more change, institutionalizing new approaches are derived from the eight common errors that managers make while implementing change in the institution. The study integrated LSS principles and Kotter’s change management model to apply in emergency care units in order to reduce waste and raise the level of service quality provided by healthcare companies.

The present study could contribute knowledge to the literature by providing a framework to integrate lean management and Kotter's change management model for the emergency care unit of the healthcare organization. This framework guides decision-makers and organizations as proper strategies are required for applying lean management practices in any system.

The proposed framework is unique and no other study has prescribed any integrated framework for LSS implementation in emergency healthcare that overcomes resistance to change.

There is increasing interest in the connection between Industry 4.0 (I4.0) and operational excellence approaches; however, studies on the integration between Six Sigma (SS) and I4.0 have been absent from the literature. Integration with I4.0 technologies can maximize the positive effects of SS. The purpose of this study is to understand what types of relationships exist between SS and I4.0 and with I4.0's technologies, as well as the benefits derived from this integration and future directions for this field of study.

A Systematic Literature Review (SLR) was carried out to analyze studies about connections between I4.0 technologies and SS. SLR analyzed 59 articles from 2013 to 2021 extracted from the Web of Science and Scopus databases, including documents from journals and conferences.

The SLR identified relationships between SS and several I4.0 technologies, the most cited and with the greatest possibilities of relationships being Big Data/Big Data Analytics (BDA) and Internet of Things (IoT). Three main types of relationships were identified: (1) support of I4.0 technologies to SS; (2) assistance from the SS to the introduction of I4.0 technologies, and, to a lesser extent; (3) incompatibilities between SS and I4.0 technologies. The benefits are mainly related to availability of large data sets and real-time information, enabling better decision-making in less time.

In addition, the study can help managers to understand the integration relationships, which may encourage companies to adopt SS/Lean Six Sigma (LSS) in conjunction with I4.0 technologies. The results also drew attention to the incompatibilities between SS and I4.0 to anticipate potential barriers to implementation.

The study focuses on three previously unexplored subjects: the connection between SS and I4.0, the existing relationships with different technologies and the benefits resulting from the relationships. In addition, the study compiled and structured different types of relationships for SS and I4.0 and I4.0's technologies, identifying patterns and presenting evidence on how these relationships occur. Finally, exposes current trends and possible research directions.

This article aims to optimise energy use and consumption by integrating Lean Six Sigma methodology with the ISO 50001 energy management system standard in an Irish dairy plant operation.

This work utilised Lean Six Sigma methodology to identify methods to measure and optimise energy consumption. The authors use a single descriptive case study in an Irish dairy as the methodology to explain how DMAIC was applied to reduce energy consumption.

The replacement of heavy oil with liquid natural gas in combination with the new design of steam boilers led to a CO₂ footprint reduction of almost 50%.

A further longitudinal study would be useful to measure and monitor the energy management system progress and carry out more case studies on LSS integration with energy management systems across the dairy industry.

The novelty of this study is the application of LSS in the dairy sector as an enabler of a greater energy-efficient facility, as well as the testing of the DMAIC approach to meet a key objective for ISO 50001 accreditation.

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.

The purpose of the present work is identification and prioritization of barriers to Lean Six Sigma (LSS) implementation in Indian manufacturing industries in the context of Industry 4.0 (I4.0) to surmount the impediments in the path of successful implementation.

In total, 27 barriers identified through critical review of literature and expert's opinion are evaluated with Cronbach's alpha values including item-total correlations or corrected item-total correlations (CITC) using statistical tool. Finally, 20 barriers were analyzed and ranked employing Fuzzy Analytical Hierarchy Process (FAHP).

The study depicts that “Lack of leadership, advisory and monitoring,” “Lack of clarity about economic benefits” and “Lack of integration of LSS with smart tools/I4.0” are potential barriers to drive the path for proper implementation of LSS in Industry 4.0 with due consideration of its technologies in Indian manufacturing industries.

The study provides better knowledge platform for academicians and researchers about hidden aspects of LSS implementation barriers in view of advanced manufacturing technologies. This research will help the practitioners to design their business plans in implementing new quality improvement tools to get advantage in current competitive environment.

The barriers are selected based on literature and opinion from industry and academic experts. Five major criteria are decided after incorporating inputs. The ranking of the barriers is attained by well standard mathematical technique. This will enable the practitioners to design strategies to eliminate the hindrances in order to shape the right path for effective implementation of LSS approach in view of advanced manufacturing technologies.

To redesign the spare parts (MRO) inventory management at Company XYZ's warehouse, considering the conditions after the COVID-19 pandemic.

To address this research project, the authors integrated three methodologies: action research, Lean Six Sigma (DMAIC) and Cross Industry Standard Process for Data Mining. These methodologies integrated the Lean Six Sigma (LSS) 4.0 framework applied in this project.

The spare parts inventory value was reduced by 15%, and inventory turnover increased by 120% without negatively impacting the internal service level.

Practitioners leading or participating in continuous improvement projects (CIPs) should consider data quality (data available and data trustworthiness), problem-solving approach and target area involvement to achieve CIP goals. Otherwise, the LSS 4.0 could fail or extend its duration by several weeks or months.

This project shows the importance of controlling a target area before deciding to conduct a LSS 4.0 project. To address this problem, the LSS 4.0 team implemented 5S during the measure phase of the DMAIC. Also, this project offers significant practitioner and theoretical contributions to the body of knowledge about LSS 4.0.

The purpose of this paper is to contribute to the limited body of empirical knowledge on the impact of Lean Six Sigma (LSS) program implementations on organizational performance in financial services by investigating how antecedents of Lean Six Sigma program success (motivations, selected LSS methods and challenges) affect organizational performance enhancement via LSS program performance.

A sample of 198 LSS professionals from 7 countries are surveyed. Structural equation modeling (SEM) is performed to test the questioned relations.

This study’s findings comprise: (1) LSS program performance partially mediates the relationship between motivations for LSS implementation and organizational performance, (2) selected LSS method applications has a fully (mediated) indirect impact on organizational performance, (3) LSS implementation challenges also have an indirect (mediated) impact on organizational performance and (4) LSS program performance has a positive impact on organizational performance.

The findings of this research predominantly provide nuances and details about LSS implementation antecedents and effects, useful for managers in advising their business leaders about the prerequisites and potential operational and financial benefits of LSS implementation. Furthermore, the paper provides evidence and details about the relationship between important antecedents for LSS implementation identified in existing literature and their impact on organizational performance in services. Thereby, this research is the first in providing empirical, cross-sectional, evidence for the antecedents and effects of LSS program implementations in financial services.

This paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.

This study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.

The results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.

It is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.

The practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.

This study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.