Search results

The present environmental concern has enforced manufacturing firms to re-evaluate their business practices to reduce the adverse impact on the environment with optimum production. Therefore, the present study aims to deal with the implementation of the environmental lean six sigma (ELSS) framework in an Indian medical equipment manufacturing industry to obtain operational and environmental sustainability.

The proposed ELSS framework is based on the DMAIC (Define–Measure–Analyze–Improve–Control) methodology, sustainability and lean tools. The efficacy of the developed framework is tested through a case study in an Indian medical equipment manufacturing unit.

In the case company, four major issues were reported, i.e. improper material handling, non-productive movement of men and material, poor indoor air quality and rework. The ELSS project facilitates the case organization to enhance their capacity utilization from 59.25% to 74.3%, defects per million opportunities reduce from 309,523 to 48,951.44 and indoor air quality levels decrease from 156.87 to 86.85 µgm3.

The efficacy of the developed ELSS framework is evaluated through a case study conducted only in one Indian manufacturing environment.

The present study facilitates industrial managers and practitioners to achieve sustainability and process excellence through ELSS implementation. Organizations that intend to simultaneously improve operational and environmental performance can benefit from this paper as it can be used as a guide to conduct similar projects with both operational and environmental benefits.

This paper presents a successful implementation of the ELSS framework in the healthcare industry to achieve operational and environmental sustainability.

The purpose of this study is to present the systematic literature review (SLR) on Lean Six Sigma (LSS) by exploring the state of the art on growth of literature on LSS within the manufacturing sector, critical factors to implement LSS, the role of LSS in the manufacturing sector from an implementation and sustainability viewpoint and Industry 4.0 viewpoints while highlighting the research gaps.

An SLR of 2,876 published articles extracted from Scopus, WoS, Emerald Insight, IEEE Xplore, Taylor & Francis, Springer and Inderscience databases was carried out following the protocol of systematic review. In total, 154 articles published in different journals over the past 10 years were selected for quantitative and qualitative analysis which revealed a number of research gaps.

The findings of the SLR revealed the growth of literature on LSS within the manufacturing sector. The review also highlighted the most cited critical success factors, critical failure factors, performance indicators and associated tools and techniques applied during LSS implementation. The review also focused on studies related to LSS and sustainability viewpoint and LSS and Industry 4.0 viewpoints.

The findings of this SLR can help senior managers, practitioners and researchers to understand the current developments and future requirements to adopt LSS in manufacturing sectors from sustainability and Industry 4.0 viewpoints.

Academic publications in the context of the role of LSS in various research streams are sparse, and to the best of the authors’ knowledge, this paper is one of the first SLRs which explore current developments and future requirements to implement LSS from sustainability and Industry 4.0 perspective.

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.

Despite differing strategies towards environmental sustainability in developed and developing nations, the manufacturing sector in these regional domains faces substantial environmental issues. The purpose of this study is to examine the green-lean-six sigma (GLSS) enablers and outcomes for enhancing environmental sustainability of manufacturing firms in both, a developed and developing country context by using an environment-centric natural resource-based view (NRBV).

First, a framework of GLSS enablers and outcomes aligned with the NRBV strategic capabilities is proposed through a systematic literature review. Second, this framework is used to empirically investigate the GLSS enablers and outcomes of manufacturing firms through in-depth interviews with lean six sigma and environmental consultants from New Zealand (NZ) and Pakistan (PK) (developed and developing nations).

Analysis from both regional domains highlights the use of GLSS enablers and outcomes under different NRBV capabilities of pollution prevention, product stewardship and sustainable development. A comparison reveals that NZ firms practice GLSS to comply with environmental regulatory requirements, avoid penalties and maintain their clean-green image. Conversely, Pakistani firms execute GLSS to reduce energy use, satisfy international customers and create a green image.

This paper provides new insights on GLSS for environmental sustainability which can assist industrial experts and academia for future strategies and research.

This is one of the early comparative studies that has used the NRBV to investigate GLSS enablers and outcomes in manufacturing firms for enhancing environmental performance comparing developed and developing nations

In light of the recent changes in the internal audit (IA) landscape, the role of auditors has undergone a significant transformation. This paper aims to investigate the effects of applying Lean Six Sigma (LSS) techniques on the effectiveness and efficiency of IA.

The study used a quantitative approach, surveying Iranian internal auditors with a sample size of 384 participants. Data analysis involved confirmatory factor analysis and structural equation modeling.

The analyses demonstrate a significant association between LSS application and IA effectiveness and efficiency. In addition, an exploratory analysis indicates that the application of LSS techniques by less experienced internal auditors had a reverse effect on IA function quality as a component of IA competency. However, IA motivation factors, including education and position, did not mediate the impact of LSS on IA effectiveness and efficiency.

This study was conducted with Iranian internal auditors, which may limit the generalizability of the findings to other countries. However, the primary academic implication of this research lies in its novel perspective on emphasizing the concept of continuous improvement in IA through the use of LSS techniques. By focusing on the need for internal auditors to add value to the business in new ways, this research contributes to the literature on IA quality.

This study has significant implications for the effective management of IA departments. By promoting the application of LSS techniques in IA, lean auditing is enhanced, and IA can create value by improving the quality of its functions. Moreover, IA regulators can benefit from this study as it emphasizes providing guidance and training on LSS techniques to enhance IA skills.

This research is pioneering in applying LSS methodology to enhance the effectiveness and efficiency of internal auditing. It also considers the integration of lean thinking into current audit practices, making it unique and valuable in internal auditing research.

India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological advancements lead to enhancements in products and processes. These forced Indian organizations to adopt innovative business strategies in the past 30 years. Meanwhile, the Lean Six Sigma methodology has significantly grown with vast applicability during the past 30 years. Thus, the purpose of this study is to develop the learning on Lean Six Sigma methodology in the Indian context through investigation of literature.

A three-stage systematic literature review approach was adopted to investigate the literature during the present study. In total, 187 articles published in 62 journals/conference proceedings from 2005 to 2022 (18 years) were shortlisted. The first part of the article summarizes the significant milestones towards the quality journey in the Indian context, along with the evolution of the Lean Six Sigma methodology. The second part examines the shortlisted papers on Lean Six Sigma frameworks, their applicability in industrial sectors, performance metrics, outcomes realized, publication trends, authorship patterns and leading researchers from the Indian perspective.

Lean Six Sigma has emerged as a highly acclaimed and structured business improvement strategy worldwide. The Indian economy has seen remarkable growth in the past decade and is one of the fastest-growing economies in the 21st century. Lean Six Sigma implementation in India has significantly increased from 2014 onward. The study revealed that researchers have proposed several different frameworks for Lean Six Sigma implementation, the majority of which are conceptual. Furthermore, the balanced applicability of Lean Six Sigma in manufacturing and service sectors was observed with the highest implementation in the health-care sector. Additionally, the widely adopted tools, techniques along with performance metrics exploring case studies were reported along with a summary of eminent and leading researchers in the Indian context.

This study is confined to reviewed papers as per the research criteria with a significant focus on the Indian context and might have missed some papers due to the adopted papers selection strategy.

The present study is one of the initial attempts to investigate the literature published on Lean Six Sigma in the Indian context, including perspective on the Indian quality movement. Therefore, the present study will provide an understanding of Lean Six Sigma methodology in the Indian context to graduating students in engineering and management and entry-level executives. The analysis and findings on Lean Six Sigma frameworks, research approach, publications details, etc., will be helpful to potential research scholars and academia. Additionally, analysis of case studies on Lean Six Sigma implementation by Indian industries will assist the managers and professionals in decision making.

This research investigates the impact of Industry 4.0 technologies (I4.0) on the resilience of manufacturing firms against the COVID-19 pandemic. The study explores the mediating effects linked to the firm’s supply chain resilience and absorptive capacity in this relationship.

The empirical analysis involves 304 manufacturing firms and uses Partial Least Squares Structural Equation Modeling (PLS-SEM). A two-step hierarchical component model has been employed, considering the statistical analysis validation (reliability and validity) of the LOC and HOC models. The choice of the manufacturing industry is justified due to its degree of automation in emerging economies, such as Mexico, and its significant impact on job creation and the national gross domestic product.

The results confirm the positive impact of I4.0 technologies on companies’ resilience to COVID-19. They also support the indirect effects of the firm’s supply chain resilience and absorptive capacity. Absorptive capacity was found to have a higher significant indirect effect than supply chain resilience. Consequently, the study accentuates the significance of leveraging external knowledge and highlights the role of acquisition, assimilation, transformation, and exploitation capabilities in enhancing absorptive capacity.

The implications of this research extend to both manufacturing companies and public administrations, suggesting the need for I4.0 technologies implementation and supportive policies aimed at fostering absorptive capacity.

This research contributes to the literature by filling gaps in empirical studies in the context of developing economies. It provides valuable insights into the effects of I4.0 on absorptive capacity, supply chain resilience, and COVID-19 resilience, particularly in non-essential supply chains. It enriches the understanding of how I4.0 impacts the absorptive capacity and resilience of the supply chain during the COVID-19 crisis.

Sustainability has become a priority for companies due to pressure from multiple stakeholders. In an overly competitive market, shareholders push for economic results, allowing lean manufacturing to establish itself as dominant paradigm in manufacturing. However, concerns grow regarding how lean implementation can allow companies to achieve sustainable development goals, or, if the resources required for a successful lean implementation can result in a detriment of environmental and social performance. This paper intends to help close the knowledge gap regarding the effects of lean manufacturing on sustainable performance from a triple bottom line perspective, and how operational, environmental and social outcomes interact between themselves.

Two models for the interaction between lean and sustainability were proposed. The first is called the “sand-cone” model, which poses that performance improvements derived from lean are cumulative on each one of the sustainability dimensions. The second is called the “trade-offs” approach. In this case, the resources required to improve one dimension of sustainability clash with those required by the others. Data were gathered from a sample of 133 Colombian metalworking companies and processed using structural equations models.

The results support the cumulative “sand-cone”, which follows a sequence of operational-environmental-social improvement in the presence of lean. For the “trade-offs” model, partial evidence suggests that they can occur in detriment of social performance.

The “sand-cone” and “trade-offs” are empirically tested for the first time in the context of sustainability, providing further knowledge into its interaction with lean manufacturing. The models’ results contribute to practitioners by providing a tested path for companies to improve their performance in a cumulative sequence that will provide better long-term results.

This article aims to focus on implementing Lean Six Sigma (LSS) in steel manufacturing to enhance productivity and quality in the galvanizing process line. In recent trends, manufacturing organizations have expressed strong interest in the LSS since they attempt to enhance its overall operations without imposing significant financial burdens.

This article used lean tools and Six Sigma's DMAIC (Define, Measure, Analyze, Improve and Control) with Yin's case study approach. This study tried to implement the LSS for the steel galvanizing process in order to reduce the number of defects using various LSS tools, including 5S, Value stream map (VSM), Pareto chart, cause and effect diagram, Design of experiments (DoE).

Results revealed a significant reduction in nonvalue-added time in the process, which led to improved productivity and Process cycle efficiency (PCE) attributed to applying lean-Kaizen techniques. By deploying the LSS, the overall PCE improved from 22% to 62%, and lead time was reduced from 1,347 min to 501 min. DoE results showed that the optimum process parameter levels decreased defects per unit steel sheet.

This research demonstrated how successful LSS implementation eliminates waste, improves process performance and accomplishes operational distinction in steel manufacturing.

Since low-cost/high-effect improvement initiatives have not been adequately presented, further research studies on adopting LSS in manufacturing sectors are needed. The cost-effective method of process improvement can be considered as an innovation.

Industry 4.0 technologies have the potential to improve the quality management performance of industrial companies. The paper analyses the influence of Industry 4.0 technologies on quality management aspects, but also the barriers that slow down the deployment of each Industry 4.0 technology and limit each impact.

The impact of Industry 4.0 technologies on quality management aspects (QMAs) is a heterogeneous and multidimensional phenomenon dependent on the current context, a holistic multiple case study has been applied. Twenty-six case studies were carried out on eight Industry 4.0 technologies, with a minimum of two cases per technology. These cases were selected from the 168 projects presented in the four editions of the BIND 4.0 program, winner of the 14th edition of the European Enterprise Promotion Awards. The cases were selected based on a preliminary survey of 124 project managers. Subsequently, individual case and cross-case analyses for each technology were carried out. Finally, these results were confirmed by interviews with a minimum of two customers per Industry 4.0.

Results show that the adoption of Industry 4.0 technologies positively affects QMAs. Specifically, the influences received by “process control” and “customer satisfaction” from all the Industry 4.0 technologies studied are medium to high. In addition, barriers from the “economic and legal” and “workers” categories exert greater influence than the barriers pertaining to “organization”, “lack of training and information” and “technology”.

The main limitation is the generalizability of the findings of qualitative studies (ergo the case study). In this sense, statistical generalizability, characteristic of a random sample, is not intended in this paper. Therefore, the use of multiple case studies has been chosen to reinforce analytical generalizations with corroborated evidence (literal replication).

Managers interested in adopting Industry 4.0 technologies Ts should plan the implementation process to minimize the impact of these barriers and optimize the results for each stakeholder. In this sense, the barriers that concern the workers should be managed. It is the responsibility of managers to inform and explain how data will be handled, and how privacy concerns will be addressed.

It is essential to explain and convince workers about the need for a renewal of tasks. New types of jobs (i.e. the use of robots) will involve training for workers to enable their integration alongside the new technologies.

This paper addresses two under-researched areas that are essential when defining strategies in the industrial business context. Firstly, the paper analyses the influence of each I40 T on each QMA. Secondly, it analyses the barriers to adopt that slow down the rollout of each I40 T and limits each impact.