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This article intends to comprehend the Lean Six Sigma (LSS) approach adopted in the aerospace industry in India for process improvement. This research has the objective of determining LSS deliverables such as Voice of Customer (VOC), Key Performance Indicators (KPIs), Critical-to-Quality (CTQ), project approach, deployment strategies and tools and techniques used to execute the project.

The study adopted an exploratory research methodology and a multiple case study analysis to draw robust inferences. The research is carried out in the Indian aerospace industry and analyses five case studies. The case studies were collated from the company via a case study protocol with pre-defined criteria. Also, a semi-structured interview is conducted with the stakeholders of each case study to determine the deployment strategies followed during the respective projects.

It is reconfirmed that LSS is crucial in the aerospace industry, particularly in engine and gear shops, to reduce rework and rejections. Also, it was found that cost and time savings are essential KPIs. Some LSS projects require multiple CTQs for process improvement in aero industries. The DMAIC approach is used for project execution, with the Design of Experiment (DOE) being an essential tool. Top management engagement, effective HRM practices, customer focus, cross-functional collaboration and clear roles are essential for successful LSS projects. Eventually, a road map was developed based on the analysis of multiple case studies.

The study is focused on the aerospace industry in India, which may limit the generalizability of the findings to other industries or regions. The small sample size and reliance on qualitative data through semi-structured interviews may introduce subjectivity. Additionally, the long-term effects of LSS implementation, particularly in the context of evolving technologies, were not fully explored.

This study provides actionable insights for aerospace companies and related organisations to enhance quality and operational performance. The developed roadmap offers a practical guide for LSS deployment, helping organisations improve efficiency and competitiveness, especially in an era of economic slowdown and high competition.

The study reveals similarities and differences in LSS deliverables in Indian aerospace industries, creating a roadmap and tool matrix for project execution and serving as a template for manufacturing industries.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Research indicates that integral control parameters (K_i) affect outputs substantially more than proportional control parameters (K_p). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

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.

This systematic literature review aims to synthesise, organise and structure the stock of knowledge relating to leadership and design for Lean Six Sigma (DFLSS) and to understand leadership’s role, traits, skills, competencies and styles within the context for DFLSS program success.

The research is based on a systematic literature review of 67 papers that were published on leadership and DFLSS, demonstrating the importance of leadership for successful DFLSS programs.

The key findings show that leadership plays a critical role in launching and sustaining a DFLSS program in organisations, while illustrating the leadership traits, skills, competencies and styles that are more conducive to a successful DFLSS program.

The study has identified several gaps in the literature from a practical approach and an empirical validation of the critical factors of leadership when applying and supporting DFLSS efforts supporting future initiatives.

Design science research (DSR) is a structured approach for solving complex ill-structured problems in organizations through the development of an artefact followed by its validation. This paper aims to evaluate existing DSR methodology and propose specific accents to promote DSR for environmental, social and governance (ESG)-oriented operational excellence (OPEX) initiatives within organizations.

This commentary paper is based on an abductive reasoning approach to evaluate and understand DSR and assess its effectiveness for developing solutions to typical ESG-oriented OPEX-based problems within organizations.

Existing literature on DSR is reviewed, after which it is evaluated on its ability to contribute to the implementation of sustainable solutions for ESG-oriented OPEX-based problems. Based on the review, specific DSR methodological accents are proposed for the development of ESG-oriented OPEX-based solutions in organizations.

This conceptual paper contributes to the conceptual understanding of the applicability, limitations and contextual preconditions for applying DSR. This paper proposes an explicit and, in some ways, alternative view on DSR research for OPEX researchers to apply and further the body of knowledge on matters of sustainability (ESG) in operations management.

Currently, there is limited understanding and application of the DSR methodology for OPEX-based problem-solving initiatives, as appears in the scant literature on DSR applied for the implementation of OPEX based initiatives for ESG purposes. This paper aims to challenge and provide accents for DSR applied to OPEX-related problems by means of a DSR framework and thereby promotes intervention-based studies among researchers.

The proposed step-by-step methodology contains novel elements and is expected to be of help for OPEX-oriented academicians and practitioners in implementing DSR methodology for practical related problems which need research interventions from academics from Higher Education Institutions.

The use of quality management (QM) to achieve the United Nations Sustainable Development Goals (UNSDGs) is a topic of growing interest in academia and industry. The IAQ (International Academy for Quality) established Quality Sustainability Award in 2020, a testament to this growing interest. This study aims to investigate how QM philosophies, methodologies and tools can be used to achieve sustainable development in organizations.

Five large manufacturing organizations – three from India and two from China – who reported their achievements about using QM in achieving Sustainable Development Goals (SDGs) were studied using multiple sources of data collection. A detailed within-case and cross-case analysis were conducted to unearth this linkage's practical and theoretical aspects.

The study finds that QM methodologies effectively met the five organizations' UNSDGs. These organizations successfully used OPEX (Operational Excellence) methodologies such as Lean, Kaizen and Six Sigma to meet UNSDGs 7, 11, 12 and 13. Moreover, UNSG 12 (Responsible Consumption and Production) is the most targeted goal across the case studies. A cross-case analysis revealed that the most frequently used quality tools were Design of Experiments (DoE), Measurement Systems Analysis (MSA), C&E analysis and Inferential statistics, among other essential tools.

The study's sample size was limited to large-scale manufacturing organizations in the two most populous countries in the world. This may limit the study's generalizability to other countries, continents, or micro-, small- and medium-sized enterprises (SMEs). Additionally, the study's conclusions would be strengthened if tested as hypotheses in a follow-up survey.

This practical paper provides case studies on how to use QM to impact SDGs. It offers both descriptive and prescriptive solutions for practitioners. The study highlights the importance of using essential QM tools in a structured and systematic manner, with effective teams, to meet the SDGs of organizations.

The study shows how QM can be used to impact UNSDGs, and this is very important because the UNSDGs are a set of global objectives that aim to address a wide range of social and environmental issues. This study could motivate organizations to achieve the UNSDGs using essential QM tools and make the world a better place for the present and future generations.

This case study is the first to investigate at a micro-level how QM can impact UNSDGs using live examples. It uses data from the IAQ to demonstrate how QM can be integrated into UNSDGs to ensure sustainable manufacturing.

Quality management (QM) plays a pivotal role in driving organisational efforts to enhance operational efficiency and customer satisfaction. This study aims to explore the most important themes in QM over the past three decades, identifying and analysing the top ten key themes that have shaped the field during this period. This study, involving leading academics and industry practitioners, lays the groundwork for a three-to-four-year exploration of the most influential QM themes worldwide.

The authors conducted a comprehensive review of QM literature over the last three decades from top specialist journals on QM. This is followed by conducting a global pilot survey with leading academics and practitioners to pinpoint the top ten dominant themes of QM for organisations to leverage in gaining and maintaining a competitive edge.

The top ten themes of QM, as identified by authors through input from academics and practitioners worldwide, offer valuable insights for companies of all sizes and sectors. These themes serve as a guide for the successful and sustainable implementation of QM practices and continuous improvement strategies.

Despite a limited sample size, the initial findings provide a glimpse into critical themes. Over the next three years, as the study progresses, we anticipate potential changes in the results. Notably, the comparison of themes between manufacturing and services as well as large and small enterprises, remains unexplored in the current investigation.

The authors of this study assert that their research will pave the way for future themes in the digitalization era. Moreover, this research stands out as one of the most exhaustive examinations from both academic and practitioner viewpoints, offering a unique perspective not commonly found in existing literature.

This study aims to fully assess the readiness for Lean Six Sigma (LSS) and Quality Performance Improvement (QPI) in an Italian Public Healthcare ecosystem.

Drawing from previously established survey development and adaptation protocols, a replication study was carried out; Lean, Six Sigma and QPI were extracted and validated through confirmatory factor analysis in an Italian Public Healthcare setting, with a sample of health professionals from the Campania region.

This study reports the adaptation of an existing scale for measuring LSS and QPI in an Italian public healthcare organisation. This analysis extracts six conceptual domains and constitutes an original adaptation of an existing scale to assess the readiness to adopt Lean, Six Sigma and Quality Performance in Italian Public Health Organizations. The constructs show strong levels of internal consistency, as demonstrated by each item factor loading and each subscale reliability.

Managers, policymakers and academics can employ the proposed tool to assess the public healthcare ecosystem’s capability to implement LSS initiatives and strategies to improve quality performance.

This is one of the first studies to assess cross-regional organisational readiness for LSS and QPI in an Italian Public Healthcare environment at this scope and level.

The present research focuses on improving the awareness related to soft total quality management (TQM) practices by looking from the viewpoint of strategic human resources (HR). In addition, it is intended to reflect on the resulting soft TQM-HR outcomes and determine the mediating effect between soft TQM-HR strategies and organizational effectiveness (OE).

An exploratory research methodology with an online survey technique was adopted for the study. Three hundred and three managerial-level personnel from nine large Indian manufacturing organizations participated in the research. A theoretical model is projected and verified using correlation and mediation analysis.

The results show that commitment, reduced turnover intentions and satisfaction levels of employees mediate the relationship between resources, development and retention strategies and OE. However, the retention strategy has the strongest association with the OE of the three strategies. Also, of the three HR outcomes, satisfaction was strongly associated with OE. The analysis proved that the proposed model is an acceptable fit.

Implementing HR-related TQM strategies will likely impact OE since it elicits positive HR outcomes such as commitment, reduced turnover intention and satisfaction. Recognizing human resources as a unique strategic asset will help HR managers devise adequate resourcing, development and retention strategies instrumental in executing TQM.

The present micro study is unique in scrutinizing the influence of soft TQM-HR practices on organizational effectiveness by analysing the mediating effects of commitment, reduced turnover intention and satisfaction in Indian large-scale manufacturing organizations. The study is unique since no literature deciphers the linkages between HR strategies and organizational effectiveness in the Indian manufacturing sector.