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The purpose of this paper is to review Lean Six Sigma (LSS) literature and report different definitions, demographics, methodologies and industries.

This paper highlights various definitions by different researchers and practitioners. A total of 235 research papers has been reviewed for the LSS theme, research methodology adopted, type of industry, author profile, country of research and year of publication.

From the review, four significant LSS classifications were identified that deal with the spread of LSS in different industries followed by observation for classification.

LSS is a strategy for success, but it did not examine its presence in various Industries. From this paper, readers can understand the quantum of its spread before implementing LSS. For academicians, it will be a comprehensive list of papers for research.

This paper reviews 235 research papers for their year, author profile, research methodology and type of industry. Various characteristics of LSS definitions and their theme are also reviewed.

Defective parts in manufacturing is a serious issue faced by every manufacturer. Even after proper care in design, material selection and manufacturing of product, there exists a defective part. The purpose of this paper is to explore the quality of the manufacturing, and find the use of effective quality tools to reduce the part defect rate in an electrical parts manufacturing unit, thereby, reducing the replaced cost of defective parts.

With the help of quality initiatives, like total quality management (TQM) and Lean Six Sigma (LSS), the firms can produce quality product in each stage of production. The paper focuses on the primary data collected from the XYZ electric manufacturer.

The main finding of this case analysis is that by the effective use of quality tools, the defective part return rate can be reduced, because of which the firm can observe reduction in replaced cost of almost INR24 lakh. In addition, 10A switch part contributes more in replacement cost. Further, it adds to the 35 percent of the overall part rejection.

The study is more focused on particular type of switch product and can extend to other types of products. In addition, the analysis reveals the results of only 88 percent of the defective products.

The study provides results of the improved quality by effective use of quality tools and discusses the different types of defects in the electrical parts manufacturing. Introducing TQM and LSS to manufacturing can reduce the customer return rate to 1,300 parts per million (PPM) and even to 1,000 PPM in future.

The paper discusses the quality issues in the electrical manufacturer. Moreover, the case analysis briefs effective ways to improve the product quality and reduce the rejection rate.

Many organizations have reported significant benefits after the implementation of Lean Six Sigma (LSS). Embracing LSS requires asking some important questions: How Lean Six Sigma Readiness (LESIRE) can be measured? How can an organization identify the barriers for LESIRE? Answers to these questions are critical to both academicians and practitioners. The paper aims to discuss this issue.

This study illustrates the development process of a Lean Six Sigma Readiness (LESIRE) evaluation model to assess an organization’s readiness for LSS deployment using the fuzzy approach. The model was developed from 4 enablers, 16 criteria and 46 attributes of LSS, identified through a literature review.

To demonstrate the efficiency of the model, this study testing the LESIRE evaluation model in three Indian SMEs. Using experts’ ratings and weight, the researchers calculated the Fuzzy Lean Six Sigma index (FLSS) which indicates the LESIRE level of an organization and the Fuzzy Performance Importance Index (FPII) that helps to identify the barriers for LESIRE.

The main limitations of this study are that it did not consider the failure factors of LSS for model development and the LESIRE was only tested in manufacturing industries. Thus, future researchers could focus on developing a model with failure factors. The results obtained from the SMEs show that LESIRE is capable of assessing LESIRE in an industrial scenario and helps practitioners to measure LESIRE for the future decision making process.

The LESIRE model is easy to understand and use without much computation complexity. This simplicity makes the LESIRE evaluation model unique from other LSS models. Further, LESIRE was tested in three different SMEs, and it aided them to identify and improve their weak areas, thereby readying them for LSS deployment.

The main contribution of this study it proposes a LESIRE model that evaluates the organization for FLSS and FPII for LESIRE, which is essential for the organization embarking on an LSS journey. Further, it improves the readiness of the organization that is already practicing LSS.

Many projects focus on the reliable operation of the activities in the project. Any failure in the process activities leads to major problems resulting in waste, defects, equipment damage, which has a direct impact on the consumers. In addition, Lean Six Sigma (LSS) is not new to this issue. LSS projects have faced an interruption in the process flow and unforeseen defects. Therefore, the purpose of this paper is to identify the vital failure factors of LSS projects.

Through extant literature review, the researchers found 44 critical failure factors (CFFs) of LSS. Using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) SIMOS approach, the decision makers’ (DMs) rating and weight for each factor were collected. Moreover, the study was conducted in both the manufacturing and service industries to identify the impact of CFFs in LSS projects.

CFFs and their evaluation have received little attention in the literature. Most of the previous studies deal only with the identification of the success factors in general. Therefore, the study identified 44 CFFs and ranked them through DMs. In addition, the TOPSIS SIMOS approach ranked the vital failure factors enabling the management to avert the LSS project from failures.

The study focused on project failures due to CFFs of LSS. Nevertheless, it did not consider other failure factors of project and knowledge management. Further, the sample used to test the approach was considerably small. Therefore, the study can be repeated with significant samples and the vital failure factors compared.

In real-life application, all the parameters in the LSS project need to be understood in a better manner. In such a condition, the practitioner needs to know that the project never fails due to the CFFs and TOPSIS SIMOS approach can prevent the LSS project failures.

The study applied TOPSIS SIMOS approach to rank the CFFs in an LSS project, which is first of its kind and aids the practitioners to make the right decisions in the business environment.

The purpose of this paper is to review the existing literature on the critical success factors (CSFs) of various continuous improvement (CI) like total quality management (TQM), Lean, Six Sigma and Lean Six Sigma (LSS), and perform a content analysis (CA) leading to an agenda for future research.

CA is based on literature review of 41 papers published in peer-reviewed scholarly journals. A four-stage methodology is used by the authors, with Stage 1 featuring relevant material collection; Stage 2 presenting a descriptive analysis; Stage 3 outlining the category selection; and Stage 4 featuring the material evaluation using clustering and Pareto analysis.

The CA revealed various research implications and directions for the future. The number of studies in the literature regarding CSF assessment is found to be far from substantial while compared to CI implementation. Assessment methodologies developed have been ranging from qualitative to quantitative models. Key gaps were identified and directions for CSF assessment are proposed which requires further validation.

Only articles that appeared in peer-reviewed journals were analyzed; conference papers, reports, manuals and white papers from practice were excluded. Another limitation of the paper would be the scope of CA limited to four CI constructs – TQM, Lean, Six Sigma and LSS. Research implications indicate that the future studies in this domain would be intensive toward analyzing the vital CSFs for enterprise organizational excellence and not merely process excellence.

This review study can serve as a resource for both researchers and practitioners to understand the importance of CSFs and positioning CSFs for the successful implementation of CI programs.

The CA on the existing literature on CSFs for CI presents a unique, systematic effort to identify an agenda for future research. This study is the apparently the first of its kind on CSF assessment.

Nowadays, firms are keen on improving the quality culture in the organizations. The proven success of Lean and Six Sigma has given rise to the synergetic Lean Six Sigma (LSS) approach that has been catching fire in the past one decade. However, there exists a gap between the understanding and implementation of LSS in the organizations, especially in the emerging economies. Taking this as a valuable opportunity, the purpose of this paper is to present a development of LSS training module.

This study starts with a literature review of LSS to reinforce the understanding of the research subject in scope of manufacturing sector. Then, an online questionnaire was designed and used to collect responses from 181 companies located in the Indian sub-continent. Subsequently, the results obtained from the survey were analyzed using COARSE approach.

This study reveals two key findings and associated contributions. First, it was found that the overall awareness of LSS within the responded manufacturing firms is about 70.4 percent. Second, there is no single standard training module that exists in any of the sampled firms to cater to their quality programs. Hence, in order to improve the LSS awareness which could subsequently help managers as a resource for creating an efficient workplace, this paper presents a structured LSS training framework.

Although this paper presents the importance of LSS and associated awareness level among the responded firms, more empirical evidence is required to generalize the model findings. Second, this study is scoped to firms that work out of the Indian sub-continent, and this provides a future opportunity to expand the scope of this research toward a global study for a comparison between emerging and developed economies. Third, this study is limited to manufacturing firms and hence paves an opportunity to research on a similar theme in services context as well.

Before embarking on an LSS journey, an organization can use the LSS training module proposed in this study to assess the employee awareness on LSS. Furthermore, organizations that already have a mature LSS practice can incorporate the LSS training module for periodic evaluation of the employees for effective change management.

The training module presented in this paper is the original contribution by the authors. This is no association to any single identifiable organization or associated funding. The direct practical implication of its application in real time is the value that managers could derive from the proposed LSS training framework.

As COVID-19 outbreak has created a global crisis, treating patients with minimum resources and traditional methods has become a hectic task. In this technological era, the rapid growth of coronavirus has affected the countries in lightspeed manner. Therefore, the present study proposes a model to analyse the resource allocation for the COVID-19 pandemic from a pluralistic perspective.

The present study has combined data analytics with the K-mean clustering and probability queueing theory (PQT) and analysed the evolution of COVID-19 all over the world from the data obtained from public repositories. By using K-mean clustering, partitioning of patients’ records along with their status of hospitalization can be mapped and clustered. After K-mean analysis, cluster functions are trained and modelled along with eigen vectors and eigen functions.

After successful iterative training, the model is programmed using R functions and given as input to Bayesian filter for predictive model analysis. Through the proposed model, disposal rate; PPE (personal protective equipment) utilization and recycle rate for different countries were calculated.

Using probabilistic queueing theory and clustering, the study was able to predict the resource allocation for patients. Also, the study has tried to model the failure quotient ratio upon unsuccessful delivery rate in crisis condition.

The study has gathered epidemiological and clinical data from various government websites and research laboratories. Using these data, the study has identified the COVID-19 impact in various countries. Further, effective decision-making for resource allocation in pluralistic setting has being evaluated for the practitioner's reference.

Further, the proposed model is a two-stage approach for vulnerability mapping in a pandemic situation in a healthcare setting for resource allocation and utilization.

The purpose of this paper is to improve the operational excellence of public sector services such as construction, telecommunication and health care. To achieve this endeavor, the study explores the structural attributes and obstacles in the public services and develops a Green Lean Six Sigma (GLSS) model for the public sector.

The study involved two stages: first, structured literature reviews; second, a focus group study involving Black Belts and supply chain practitioners. Using the results from the literature reviews and focus group study, the researchers have developed a Green Lean Six Sigma (GLSS) model for the public sectors.

Black belts and supply chain practitioners have identified the success in deploying Lean Six Sigma with green supply chain management. This leads to eradicating the obstacles faced by the public sector, leading to process improvement.

This study proposed an approach for developing a GLSS model for the public services, which can be applicable for other public service organizations.

The current paper presents a predictive model for process improvement in the public sector by integrating green supply chain management with Lean Six Sigma.

A huge number of events can affect the operations of a long and complicated supply chain. This paper deals with the development of a supply chain risk mitigation index (SCRMI) based on a risk mitigation maturity framework. A comprehensive list of supply chain risks has been ascertained and segregated into risks faced at various supply chain echelons through a detailed literature review.

This paper is based on an extensive literature review and questionnaire to identify risks. order of magnitude analytic hierarchy process (OM-AHP) was used as the methodology to assess the prioritization of supply chain risks under two clusters, viz., Probability and severity leading to risk were tested in a distillery.

SCRMI was determined and used to categorize their maturity level in facing supply chain risks. Thus, organization can focus on improvements for their specific needs.

The model was tested in the distillery industry. It should be tested in other contexts with other methods to provide generalizability.

This research provides direction to managers for choosing risk mitigation strategies based on the global supply chain environment. SCRMI can be a performance metric for the supply chain managers.

The manufacturer's readiness to take action in the face of disruptions in the supply chain is a critical challenge in today's complex business environment and SCRMI framework is instrumental in such business environment.

The purpose of this paper is to identify major healthcare service quality (HSQ) dimensions, their most preferred service levels, and their effect on HSQ perceptions of patients using a Taguchi experiment.

This study adopted a sequential incidence technique to identify factors relevant in HSQ and examined the relative importance of different factor levels in the service journey using Taguchi experiment.

For HSQ, the optimum factor levels are online appointment booking facility with provision to review and modify appointments; a separate reception for booked patients; provision to meet the doctor of choice; prior detailing of procedures; doctor on call facility to the room of stay; electronic sharing of discharge summary, an online payment facility. Consultation phase followed by the stay and then procedures have maximum effect on S/N and mean responses of patients. The appointment stage has a maximum effect on standard deviations.

Theoretically, this study attempted to address the dearth of research on service settings using robust methodologies like Taguchi experiment, which is popular in the manufacturing sector. The study implies the need for patient-centric initiatives for better HSQ through periodic experiments that inform about the changing priorities of patients.

The trade-off between standardization and customization create challenges in healthcare. Practically, a classification of processes based on standardization vs customization potential is useful to revamp processes for HSQ.

This study applied the Taguchi approach to get insights in re-designing a patient-centric healthcare servicescapes.