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This research aims to enhance the operational excellence and continuous improvement of the retail supply chain in the Saudi Thobe Factory through an integrated approach of Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) with artificial intelligence (AI).

The study identified the tailoring department as the department with maximum defects by using voice of customer and critical to quality tools. An AI-integrated Six Sigma approach was applied to identify and eliminate nonproductive stages, and a new facility layout was designed to enhance productivity and customer satisfaction.

The use of the factor rating method and simulation using Arena software led to an improved sigma level from 1.597 to 2.237, representing an increment of about 40%. Additionally, the defects per million opportunities reduced from 461,538 to 230,769. The study can help production industry management to optimize facility layouts and improve overall production line efficiency.

This study addresses the lack of published research on the use of an integrated approach of Six Sigma DMAIC with AI in the retail and distribution sector of Saudi Arabia, particularly for small and medium-sized enterprises (SMEs). The study demonstrates how this approach may significantly boost SMEs’ performance and provides a basis for future research in this area.

This study provides a practical example of how an integrated approach of Six Sigma DMAIC with AI can be used in the retail and distribution sector of Saudi Arabia to enhance operational excellence and continuous improvement. The study highlights the potential benefits of this approach for SMEs in the region and provides a framework for future research.

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 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 purpose of this paper is to explore the moderating role of Lean Six Sigma (LSS) practices in explaining the relationship between quality management practices (QMPs) and quality performance.

Partial least square-based structural equation modeling (PLS-SEM) was used to empirically examine the moderating effect of LSS practices on QMPs and quality performance in Malaysian medical device manufacturing companies.

Findings revealed that both QMPs and LSS practices have a significant and positive effect on quality performance. Furthermore, LSS practices served as a substitute for moderating the positive relationship between QMPs and quality performance in such a way that the relationship becomes weaker as LSS practices increase.

LSS is acknowledged as the most well-known hybrid methodology; however, due to its relative newness, it has not been studied in great detail. Unlike previous studies, this paper argued that Lean and Six Sigma practices are distinct from its predecessor TQM practices; moreover, both Lean and Six Sigma practices do not need to substitute QM/TQM practices instead of complimenting the QMPs. In addition, this study adds to the growing body of QM literature by empirically examine the effect of LSS practices in moderating the relationship between QMPs and quality performance.

Numerous attempts at installing six sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. In this study the research has aimed to highlight that a considerable number of corporate SS initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions.

To validate the influence of critical success factors (CSFs) on SS accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. A Likert-scale questionnaire was utilized, and a simple random sampling method was employed to gather data. Out of the 2,325 potential participants approached, 573 responses were received, primarily from Germany, the United Kingdom and Sweden. The analysis focused on 260 completed questionnaires and statistical methods including structural equation modeling (SEM), exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) were utilized for data analysis.

The study acknowledged four essential components of CSFs that are imperative for sustaining the success of SS: (1) Competence of belt System employees; (2) Project management skills; (3) Organizational economic capability and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of SS’s success.

The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their SS practices.

The investigation's originality lies in its contribution to assessing CSFs in SS deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.

The purpose of this article is to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the analysis of variance (ANOVA) application after the preliminary test on the model specification.

A new approach is proposed to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the ANOVA application. First, we determine this relationship from the general perspective of Six Sigma methodology under the normality assumption. Then, the approach is extended to a balanced two-stage nested design with a random effects model in which a preliminary test is used to fix the main test statistic.

The features of mean-shifted and inflated (but centred) processes with the same specification limits from the perspective of Six Sigma are studied. The shift and inflation coefficients are derived for the two-stage balanced ANOVA model. We obtained good predictions for the process shift, given the inflation coefficient, which has been demonstrated using numerical results and applied to case studies. It is understood that the proposed method may be used as a tool to obtain an efficient variance estimator under mean shift.

In this work, as a new research approach, we studied the link between mean shift and inflation coefficients when the underlying null hypothesis is rejected in the ANOVA. Derivations for these coefficients are presented. The results when the null hypothesis is accepted are also studied. This needs the help of preliminary tests to decide on the model assumptions, and hence the researchers are expected to be familiar with the application of preliminary tests.

After studying the proposed approach with extensive numerical results, we have provided two practical examples that demonstrate the significance of the approach for real-time practitioners. The practitioners are expected to take additional care before deciding on the model assumptions by applying preliminary tests.

The proposed approach is original in the sense that there have been no similar approaches existing in the literature that combine Six Sigma and preliminary tests in ANOVA applications.

Managing project completion within the stipulated time is significant to all firms' sustainability. Especially for software start-up firms, it is of utmost importance. For any schedule variation, these firms must spend 25 to 40 percent of the development cost reworking quality defects. Significantly, the existing literature does not support defect rework opportunities under quality aspects among Indian IT start-ups. The present study aims to fill this niche by proposing a unique mathematical model of the defect rework aligned with the Six Sigma quality approach.

An optimization model was formulated, comprising the two objectives: rework “time” and rework “cost.” A case study was developed in relevance, and for the model solution, we used MATLAB and an elitist, Nondominated Sorting Genetic Algorithm (NSGA-II).

The output of the proposed approach reduced the “time” by 31 percent at a minimum “cost”. The derived “Pareto Optimal” front can be used to estimate the “cost” for a pre-determined rework “time” and vice versa, thus adding value to the existing literature.

This work has deployed a decision tree for defect prediction, but it is often criticized for overfitting. This is one of the limitations of this paper. Apart from this, comparing the predicted defect count with other prediction models hasn’t been attempted. NSGA-II has been applied to solve the optimization problem; however, the optimal results obtained have yet to be compared with other algorithms. Further study is envisaged.

The Pareto front provides an effective visual aid for managers to compare multiple strategies to decide the best possible rework “cost” and “time” for their projects. It is beneficial for cost-sensitive start-ups to estimate the rework “cost” and “time” to negotiate with their customers effectively.

This paper proposes a novel quality management framework under the Six Sigma approach, which integrates optimization of critical metrics. As part of this study, a unique mathematical model of the software defect rework process was developed (combined with the proposed framework) to obtain the optimal solution for the perennial problem of schedule slippage in the rework process of software development.

Despite the number of quality management procedures being currently applied, construction defects in the domestic sector are acknowledged to contribute to the energy performance gap of buildings. This paper investigates the limitations and challenges to the implementation of project quality plans (PQPs) and their impact on the achievement of expected thermal performance in the UK social housing projects.

A qualitative approach, guided by grounded theory, was used in this research. This methodology provided the structure for systematic data analysis iterations, enabling cross-case analysis. An analytic induction process was designed to seek the explanation of the targeted phenomenon and required data collection until no new ideas and concepts emerged from the research iterations. This study collected data from five social housing projects through interviews, site observations and project documentation.

Multiple limitations and challenges were identified in the implementation of PQP to deliver thermal efficient social housing. Generally, there is the need for more objective quality compliance procedures based on required evidence. When investigating the root of the challenges, it was concluded that the adoption of statutory approval as the main quality compliance procedure led to the dilution of the responsibility for prevention and appraisal of defects that compromised the effectiveness of PQP devised by housing associations (HA) and contractors.

This study identifies the shortcomings of PQP in addressing quality issues with potential to undermine the thermal performance of social housing projects. The findings could be used by HA, contractors and policymakers as steppingstones to improve the energy efficiency in the domestic sector.

In response to mounting global concerns about climate change and scarcity of natural resources, manufacturers have been pressured to develop strategies and enhance their sustainability performance. The integration of sustainable lean manufacturing (SLM) during value chain processes could balance environmental, social and economic concerns into their decision-making, which not only ensures responsible practices but also drives efficiency and success. This paper aims to identify, measure and prioritize metrics to develop a performance measurement system that assesses the multi-dimensional performance of SLM.

Strategic decision-making has some conflicting criteria and objectives to be considered simultaneously. The Multi-Criteria Decision Making provides a foundation for selecting, sorting and prioritizing these strategies with the determination of drivers and indicator weight.

The performance model enables the decision-makers to consistently evaluate the level of sustainability through a multidimensional framework, which could support the assessment of the existing sustainability of a manufacturing process and analyze opportunities for improvement. This study divided the performance into five drivers: Quality, Operational, Finance, Environment, Safety and People and selected 17 KPIs for assessing the multi-dimensional performance of SLM organizations. The research results revealed an organization's perspective transition from strategies focused on operational and economic performance to a more sustainable ideal with greater importance for social and environmental directions.

This framework will be facilitated by the selection of the most significant drivers and the development of strategic plans for the successful adoption of sustainable manufacturing. The practices support implementation, pursue competitive advantages and sustain manufacturing, meeting strategic requirements of suitable and lean performance. With the limited resources of the organizations, the framework proposed will guide the priorities and actions to be taken toward the SLM.

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.