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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 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 purpose of this paper is to explore the voice of the customer, key performance indicators, critical to quality characteristics, critical success factors, and commonly used tools and techniques for deploying the Lean Six Sigma (LSS) strategy in Indian private hospitals, with special attention to the medical records.

The study utilizes the action research methodology to obtain a greater understanding of the use of LSS in the Indian healthcare sector. Multiple case studies were designed and successfully deployed to understand and ascertain challenges in LSS implementation. Five case studies were carried out in the Medical Records Departments (MRD) of four private hospitals in India.

Patients perceive that waiting in queue harms their health, which can be rectified by addressing the cycle time of the system. The research also found that effective leadership, availability of data, involvement of cross-functional team and effective communication are critical to the success of LSS projects. In addition, control charts, cause and effect diagram, 5S, gemba, two-sample t-test, standardization, waste analysis and value stream mapping are some of the common tools used to improve healthcare systems.

The research was restricted to studying the impact of LSS on the workflow and resource consumption of the MRD in Indian allopathic hospitals only. The validity of the results can be improved by including more hospitals and more case studies from the healthcare sector in different countries.

The findings will enable researchers, academicians and practitioners to incorporate the results of the study in LSS implementation within the healthcare system to increase the likelihood of successful deployment. This will provide greater stimulus across other departments in the hospital sector for wider and broader application of LSS for creating and sustaining process improvements.

The purpose of this article is to demonstrate the application of the tools and techniques of Quality by Design (QbD) approach in an Indian pharmaceutical drug product manufacturing company and to understand the challenges, managerial implications and lessons learned while implementing this initiative.

This work adopts the Action Research methodology for impurity reduction in a drug product manufacturing company in India by using the tools and techniques of QbD approach. Various QbD tools like Design of experiments, process capability evaluation and control charts were effectively utilized for the study.

As a part of QbD implementation in the organization, a specific drug product was identified and the impurity level in the product was studied. Significant variables impacting the impurity were identified and the optimum levels for the significant variables were identified through design of experiments. The solutions were implemented and the impurity levels were reduced significantly.

Even though the article is based on a single case study related to tools and techniques of QbD in a single organization in India, the identified problem is a generic product quality related issue for any pharmaceutical drug product manufacturing company. Hence the findings of this research are applicable to pharmaceutical drug manufacturing industry in general.

This article illustrates the systematic usage of various tools and techniques of QbD methodology in a pharmaceutical drug product manufacturing company. The usage of Design of Experiments for process optimization and application of other tools and techniques are ready references for the practitioners and novice users in the field.

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 purpose of this paper is to compare various methods of estimation of P(X<Y) based on Type-II censored data, where X and Y represent a quality characteristic of interest for two groups.

This paper assumes that both X and Y are independently distributed generalized half logistic random variables. The maximum likelihood estimator and the uniformly minimum variance unbiased estimator of R are obtained based on Type-II censored data. An exact 95 percent maximum likelihood estimate-based confidence interval for R is also provided. Next, various Bayesian point and interval estimators are obtained using both the subjective and non-informative priors. A real life data set is analyzed for illustration.

The performance of various point and interval estimators is judged through a detailed simulation study. The finite sample properties of the estimators are found to be satisfactory. It is observed that the posterior mean marginally outperform other estimators with respect to the mean squared error even under the non-informative prior.

The proposed methodology can be used for comparing two groups with respect to a suitable quality characteristic of interest. It can also be applied for estimation of the stress-strength reliability, which is of particular interest to the reliability engineers.

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.

Lean Six Sigma (LSS) has been accepted globally across the service sector as a management strategy for achieving process excellence. In the past one decade, the application and success of LSS in services is remarkable across Information Technology (IT) organisations. However academic research has seldom derived implications from this practitioner’s science of improving processes. The purpose of this paper is to feature the application of LSS in the system maintenance department of a manufacturing firm.

The research reported in this paper is based on a case study carried out in system maintenance department using the Six Sigma Define-Measure-Analyse-Improve-Control (DMAIC) approach and its application in reducing complaint resolution time.

The LSS article presented here highlights a real-world case study of how LSS DMAIC methodology help reduce the complaint resolution time from 12.5 to 8.5 h (~30 per cent improvement) and the corresponding standard deviation from 28 to 17.4 days. This study also has resulted in reducing the turn-around-time of all the core processes in the organisation. The indirect financial savings estimated as a result of this overall impact was around INR2.5m.

The research was restricted to studying the impact of LSS in one organisation. The validity of the results can be improved by including more organisations and more case studies from the IT support services.

This could serve as a resource for both practitioners to derive useful implications and to academicians as it contributes to the LSS body of knowledge towards theory testing.

While Six Sigma (SS) has been deployed effectively in Indian manufacturing and service sectors as a process improvement methodology, the implementation of Design for Six Sigma (DFSS) for robust product and service development has not shown noticeable results. Therefore, this article aims to determine the critical failure factors (CFFs) of DFSS in the Indian context.

The paper presents the results of a pilot survey on the CFFs of DFSS in Indian companies. The survey participants were specialists in DFSS who have been involved in DFSS projects in their past and present companies. Moreover, the pilot study participants were DFSS Champions, Master Black Belts, Black Belts and Green Belts from the manufacturing and service sectors.

Company-wide applications of DFSS are very limited in India. Most of the DFSS project failures are reported in the Analyse phase of the project. The results indicated that all 18 CFFs used in the survey have a significant impact on project failures. Also, it was determined that all CFFs are positively correlated with each other. Further, a strong correlation was observed between the voice of the customer (VOC) and project selection and prioritisation. In addition, effective training showed a strong correlation with the right selection of tools.

The pilot survey was based on a limited sample size. Moreover, the study is confined to only the Indian context and data were collected through the authors' networks. However, respondents were proficient, certified and involved in DFSS project deployment in the manufacturing and service sectors. Therefore, the study's findings are useful and meaningful to draw robust inferences.

To the best of the authors' knowledge, this is the first empirical study conducted in the Indian context to identify the reasons for DFSS project failures. The study's findings can aid academicians and practitioners in comprehending and critically examining the CFFs of DFSS before executing a project. Moreover, the research outcome motivates policymakers to create an ecosystem to effectively adopt DFSS for start-ups and micro, small and medium enterprises (MSME) to ensure a circular economy and support the “Atmanirbhar Bharat” initiative.

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.