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This study aims to present Lean Six Sigma (LSS) deployment and sustainment strategies for the healthcare sector from a multi-level perspective. The objective is to present LSS implementation insights to enable policymakers, practitioners and academicians to test and develop an LSS framework for healthcare sectors.

The strategies identified are the result of a multi-method research design involving literature review, action research (AR) and Delphi study. Further, the AR portion of the study involved more than 10 years of projects focused on the deployment of LSS in the healthcare sector.

The strategies include a holistic view from the multi-level perspective, considering the Top Management Level, Middle Management Level and Operational Level. The authors ascertained 27 strategies across the three levels of organizational structure for the effective deployment of LSS. Further, the authors present a customized LSS “pocket guide” from the healthcare perspective for quick reference.

The strategies delineated in this study are based on the Indian healthcare section only; thus, further research in additional geographic contexts is needed. Also, further research is necessary to provide additional empirical validation of the effects of the identified strategies on LSS program outcomes and to verify that the strategies operate at the proposed organizational levels. Future research should also focus on identifying the interrelationships between strategies within and across levels, developing a “road map” for LSS implementation in hospitals and designing the LSS curriculum for medical schools and other medical training programs.

Observations of this study can contribute to developing a holistic framework for successful LSS implementation in the healthcare sector for academicians, practitioners and policymakers. This, in turn, ensures an enhanced value proposition, improved quality of life and reduced healthcare operational costs. Thus, it ensures a win-win situation among all the stakeholders of the healthcare sector.

The strategies put forth will enable the LSS researchers, academicians and, more particularly, practitioners to delve deeper into specific enablers and safeguard the LSS deployment from backlash. The research has two significant benefits. Firstly, it enhances the understanding of LSS from the healthcare perspective. Secondly, it provides direction for future studies with specific components for hospitals’ LSS framework, which can be further tested, refined and improved.

The aim of the article is to ascertain the challenges, lessons learned and managerial implications in the deployment of Lean Six Sigma (LSS) competitiveness to micro, small and medium Enterprises (MSME) in India and to establish doctrines to strengthen the initiatives of the government.

The research adopts the Action Research methodology to develop a case study, which is carried out in the printing industry in a Tier III city using the LSS DMAIC (Define-Measure-Analyze-Improve-Control) approach. It utilizes LSS tools to deploy the strategy and to unearth the challenges and success factors in improving the printing process of a specific batch of a product.

The root cause for the critical to quality (CTQ) characteristic, turn-around-time (TAT) is determined and the solutions are deployed through the scientifically proven data-based approach. As a result of this study, the TAT reduced from an average of 1541.2–1303.36 min, which in turn, improved the sigma level from 0.55 to 2.96, a noteworthy triumph for this MSME. The company realizes an annual savings of USD 12,000 per year due to the success of this project. Top Management Leadership, Data-Based Validation, Technical Know-how and Industrial Engineering Knowledge Base are identified as critical success factors (CSFs), while profitability and on-time delivery are the key performance indicators (KPIs) for the MSME. Eventually, the lessons learned and implications indicate that LSS competitiveness can be treated as quality management standards (QMS) and quality tools and techniques (QTT) to ensure competitive advantage, sustainable green practices and growth.

Even though the findings and recommendations of this research are based on a single case study, it is worth noting that the case study is executed in a Tier III city along with novice users of LSS tools and techniques. This indicates the applicability of LSS in MSME and thus, the modality adopted can be further refined to suit the socio-cultural aspects of India.

This article illustrates the deployment of LSS from the perspective of novice users, to assist MSME and policymakers to reinforce competitiveness through LSS. Moreover, the government can initiate a scheme in line with LSS competitiveness to complement the existing schemes based on the findings of the case study.

The article intended to excavate the Lean Six Sigma (LSS) deployment challenges, Critical Success Factors (CSF), tools and techniques, and managerial implications in an Indian healthcare setting.

The article illustrates a case study established using Action Research (AR) approach. Further, the case study is based on the Define, Measure, Analyze, Improve, Control (DMAIC) phases of LSS. The performance and service quality of the Endodontics department of a dental college attached to a hospital is enhanced and sustained through the LSS strategy.

The processing time of Root Canal treatment is reduced by determining the root causes for delay and implementing sustainable solutions. The structured deployment of the LSS strategy helped the Endodontics department to reduce the processing time from an average of 116 min–84 min. Thus, the process's sigma level is enhanced from 0.06 to 4.17 and assisted in sustaining the results.

The case study's findings are based on the single AR carried out at an Endodontics department of a dental college hospital based on LSS strategies. Even though this study's results cannot be generalized, the deliverables of the case study can be used to develop the LSS roadmap for the dental colleges to enhance the service quality and safety of the patients.

The article provides step-by-step details for implementing LSS in dental college hospitals with critical analysis based on robust statistical tools and techniques. The case study provides evidence of the adoption of LSS in medical college education and provides the confidence to adopt the same through novice users. The study's findings may persuade the policymakers to add LSS in the medical education curriculum to reinforce safety and reduce errors in the healthcare system.

The primary aim of this article is to ascertain the modalities of leveraging Lean Six Sigma (LSS) for Industry 4.0 (I4.0) with special reference to the process industries. Moreover, it intends to determine the applicability of simulation-based LSS in the automation of the mineral water industry, with special emphasis on the robust design of the control system to improve productivity and performance.

This study adopts the action research methodology, which is exploratory in nature along with the DMAIC (define-measure-analyze-improve-control) approach to systematically unearth the root causes and to develop robust solutions. The MATLAB simulation software and Minitab statistical software are effectively utilized to draw the inferences.

The root causes of critical to quality characteristic (CTQ) and variation in purity level of water are addressed through the simulation-based LSS approach. All the process parameters and noise parameters of the reverse osmosis (RO) process are optimized to reduce the errors and to improve the purity of the water. The project shows substantial improvement in the sigma rating from 1.14 to 3.88 due to data-based analysis and actions in the process. Eventually, this assists the management to realize an annual saving of 20% of its production and overhead costs. This study indicates that LSS can be applicable even in the advent of I4.0 by reinforcing the existing approach and embracing data analysis through simulation.

The limitation of this research is that the inference is drawn based on a single case study confined to process industry automation. Having said that, the methodology deployed, scientific information related to optimization, and technical base established can be generalized.

This article is the first of its kind in establishing the integration of simulation, LSS, and I4.0 with special reference to automation in the process industry. It also delineates the case study in a phase-wise manner to explore the applicability and relevance of LSS with I4.0. The study is archetype in enabling LSS to a new era, and can act as a benchmark document for academicians, researchers, and practitioners for further research and development.

This paper aims to unearth the essential components of Six Sigma for successful deployment and sustainment of service quality in four different organizations in the United Arab Emirates (UAE). More specifically, the paper is intended to determine the motivation to apply Six Sigma, Voice of Customer, Key Performance Indicators (KPIs), Critical-to-Quality (CTQ), readiness factors, Critical Success Factors, sustainment measures, tools and techniques used, challenges/barriers and performance impact on the company.

An exploratory research methodology with multiple case study analyses was adopted to determine the answers to the research objectives. Four case studies from different service processes of four companies were analyzed. The case studies were collated from these companies via a case study protocol with pre-defined criteria.

The analysis shows that service operation improvement projects are primarily dependent on the voice of the internal customer, with return on investment in savings as the KPI of the process. Most organizations prefer cycle time and errors as the CTQs in the Six Sigma projects. Even novice users can effectively apply the Six Sigma methodology with external experts’ assistance, mentoring and interventions. Across the case studies, it is observed that the projects were successfully deployed due to the support of top management leadership, effective communication and cross-functional teams. Employee resistance to change is the common barrier observed during the case study analysis. Eventually, in all the four case studies, Six Sigma is executed with standard tools and techniques within the define, measure, analyze, improve, control (DMAIC) approach.

The present study’s findings cannot be generalized due to the limited number of case study analyses in different ecosystems in the UAE. The authors would like to analyse and report more case studies in service quality improvement through the Six Sigma methodology to comprehend and develop a generic roadmap for the deployment of Six Sigma in the UAE service industry.

The study’s findings provide insights into commonalities and differences between the essential factors of Six Sigma deployment and sustainability in UAE companies.

The study results might help the policymakers and key decision makers in UAE and other countries understand the effectiveness of Six Sigma in service quality improvement with its essential factors for deployment.

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 article evaluates the obstacles, lessons learned and managerial implications of deploying Lean Six Sigma (LSS) in a dental college hospital in India.

The work adopts the action research (AR) methodology to establish a case study, which is carried out using the LSS define–measure–analyze–improve–control (DAMIC) approach in a dental college. It uses LSS tools to enhance the productivity and performance of the Conservative Dentistry Department of a dental college and to unravel the obstacles and success factors in applying it to the education and healthcare sector together.

The root cause for high turn-around time (TAT) is ascertained using LSS tools and techniques. The effective deployment of the solutions to the root causes of variation assists the dental college to reduce the TAT of the Conservative Dentistry process from an average of 63.9 min–36.5 min (i.e. 42.9% improvement), and the process Standard Deviation (SD) was reduced from 2.63 to 2 min. This, in turn, raises the sigma level from 0.48 to 3.23, a noteworthy successful story for this dental college.

While the results and recommendations of this research are focused on a single case study, it is to be noted that the case study is carried out with new users of LSS tools and techniques, especially with the assistance of interns. This indicates the applicability of LSS in dental colleges; thus, the adopted modality can be further refined to fit India's education and hospital sector together.

This article explains the implementation of LSS from an aspiring user viewpoint to assist dental colleges and policymakers in improving competitiveness. In addition, the medical education sector can introduce an LSS course in the existing programme to leverage the potential of this methodology to bring synergy and collaborative research between data-based thinking and the medical field based on the findings of this study. The most important contribution of this article is the illustration of the design of experiments (DOE) in the dental college process.

The aim of this article is to demonstrate the development of environment friendly, low cost natural fibre composites by robust engineering approach. More specifically, the prime objective of the study is to optimise the composition of natural fibre reinforced polymer nanocomposites using a robust statistical approach.

In this research, the material is prepared using multi-walled carbon nanotubes (MWCNT), Cantala fibres and Epoxy Resin in accordance with the ASTM (American Society for Testing and Materials) standards. Further, the composition is prepared and optimised using the mixture-design approach for the flexural strength of the material.

The results of the study indicate that MWCNT plays a vital role in increasing the flexural strength of the composite. Moreover, it is observed that interactions between second order and third order parameters in the composition are statistically significant. This leads to proposing a special cubic model for the novel composite material with residual analysis. Moreover, the methodology assists in optimising the mixture component values to maximise the flexural strength of the novel composite material.

This article attempts to include both MWCNT and Cantala fibres to develop a novel composite material. In addition, it employs the mixture-design technique to optimise the composition and predict the model of the study in a step-by-step manner, which will act as a guideline for academicians and practitioners to optimise the material composition with specific reference to natural fibre reinforced nanocomposites.

This article aims to study the tensile properties of a functionally graded composite structure with Al–18wt%Si alloy as the matrix material and silicon carbide (SiC) particles as the reinforcing element. More specifically, the study's primary objective is to optimize the composition of the material elements using a robust statistical approach.

In this research, the composite material is fabricated using a combination of stir casting and the centrifugal casting technique. Moreover, the test specimen required to study the tensile strength are prepared according to the ASTM (American Society for Testing and Materials) standards. Eventually, optimal composition to maximize the tensile property of the material is determined using the mixture design approach.

The investigation results imply that the addition of the SiC plays a crucial role in increasing the tensile strength of the composite. The optical microstructural images of the composite show the adequate distribution of the reinforcing particles with the matrix. The proposed regression model shows better predictability of tensile strength. In addition, the methodology aids in optimizing the mixture component values to maximize the tensile strength of the produced functionally graded composite structure.

Little work has been reported so far where a hypereutectic Al–Si alloy is considered the matrix material to produce the composite structure. The article attempts to make a composite structure by using a combination of stir casting and centrifugal casting. Furthermore, it employs the mixture design to optimize the composition and predict the model of the study, which is one of a kind in the field of material science.