Search results

Lean Six Sigma (LSS) is receiving a tremendous attention as a modern process of streaming to improve the organizational ability and customer satisfaction. A successful LSS implementation is influenced by various factors and the execution of all the influencing factors simultaneously is a very difficult task for any organization. From the perspective of limitation of resources, this paper aims to present a basic issue in an LSS implementation of clustering complex and impacting factors into groups to achieve them in a stepwise manner. This paper aims to present a fundamental issue of clustering the complex and impacting factors of an LSS implementation into groups to achieve them stepwise.

A total of 40 relevant influencing factors toward an LSS implementation have been identified from the extensive literature review and duly validated with experts’ opinions. Integrated fuzzy set theory and decision-making trial and evaluation laboratory (DEMATEL) approach are demonstrated to explore the causal relationships among influencing factors of the LSS implementation. An empirical case analysis of an Indian manufacturing organization is carried out to illustrate the utilization of the proposed model.

The proposed framework effectively finds out the significance of each influencing factor of an LSS implementation and clustered into cause–effect groups. As per the results of the empirical case analysis, ten critical success factors (CSFs) of the LSS implementation are evaluated for the successful LSS implementation. Top management pays more attention to achieve them and implement them in a phase-wise approach under the limitations of accessible resources.

The presented framework provides an effective, precise and systematic decision support tool for recognizing CSFs of the LSS implementation. The organization, decision-makers, industrial practitioners and academic researchers may be able to comprehend the cause–effect relationship of the influencing factors of the LSS implementation. The exploratory nature and the single case study are two major limitations of this analysis. The developed model is heavily dependent on the experts’ opinions; hence, any bias in judgment will influence the final result.

This analysis is the first of its kind of effort, according to the best of the authors’ knowledge, to classify the influencing factors of LSS implementation into the cause–effect cluster. The outcomes of this analysis make the complexity of a problem easier in handling and assisting the decision-making.

The aim of this analysis is to review the Indian manufacturing organizations practicing Lean Six Sigma (LSS) tools/techniques with an objective of monitoring the performance of an organization and to develop recommendation for strategies to benchmark organizational operational efficiency.

This study offers insights of the LSS performance measurement aspects of the Indian manufacturing organizations based on Data envelopment analysis (DEA) approach. The five inputs and two outputs are considered on the basis of literature review and discussed with the practitioners.

In this analysis, the relative efficiency score of 18 Indian manufacturing organizations has been determined in order to assist evaluation of the impact of monetary investment on the outputs. The present analysis not only investigates the optimum level of input variables but also lays down a significant observation that an organization having higher profit and inventory turnover ratio is not necessarily an efficient organization.

The results assist to determine the best practice units, potential source of inefficiency and deliver beneficial data for the consistent enhancement of the operational efficiency. The DEA results assist managers and decision makers to derive appropriate strategies to enhance their performance with reference to the efficient organization and to regard it as their role model.

This analysis renders a DEA based framework of LSS practicing Indian manufacturing organizations. The framework is unique in terms of its input-outputs variable selection and measurement procedure.

The purpose of this paper is to develop the balance score card (BSC) approach based Lean Six Sigma (LSS) performance measurement system and investigate the critical measures currently practiced by Indian manufacturing organizations.

This study offers insights of LSS performance measurement from manufacturing industry. Initially, the BSC-based framework is developed to recognize the adoption of LSS performance measures. Then, the framework is applied to nine Indian manufacturing organizations to assess the LSS performance measure practice.

The BSC-based framework of LSS performance evaluation for manufacturing industry is formulated. Then, adoption of these LSS performance measures is investigated with nine Indian manufacturing organizations. The result indicates significant variability in terms of practicing level of LSS measures. However, the majority of organizations are more sensitive to the customer perspectives.

This study reveals a background as to why the performance measurement is required for the success of LSS and for providing practical guidelines for designing performance metrics. The framework interrelates and captures various LSS perspectives and indicator measures, and furnishes a comprehensive outlook of the organization for strategic analysis. This study provides BSC-based template for performing the benchmarking study. This analysis may serve as a reference point for manufacturing organization to determine their system weaknesses, and assist them to concentrate on their most vital and suitable criteria and objectives. However, the analysis contributes to the knowledge on LSS performance measurement system and catches differences in theory and practice, paving the approach to newer research.

This study renders an industry-oriented LSS performance measurement practical approach and suggests the easily adopted vital performance measures for different manufacturing organizations.

The purpose of this paper is to examine and introduce comprehensive insights into the field of Lean Six Sigma (LSS) by reviewing the existing literature and identifying the research gap. The state of LSS research is assessed by critically examining the field, along with a number of dimensions, including time horizon, year, journal and publisher, university, country, author, geographic analysis, research design, research affairs, research methods, tools/techniques used, focus industries, major research area, benefits gained by LSS, critical success factors and barriers of LSS implementation.

This paper is based on a systematic literature review of 190 articles containing the word LSS in their title, which are published in a well-known database, such as Elsevier ScienceDirect, Taylor and Francis, Emerald Full Text, Springer Link, Wiley InterScience and Inderscience from January 2000 to September 2016.

This analysis reveals 15 significant dimensions to identify the state of LSS research. Authors find a noticeable rise in the attention of LSS research in the available literature. Major findings show that, the empirical research holds greater credibility. Statistics prove that the case study method scores the highest among all the research methods used in the discipline. The largest number of studies have investigated research issues related to implementation and process of LSS. The LSS uses a wide range of tools/techniques/methodologies: the choice of tools is situation-specific. Manufacturing and health-care sectors have been the focus of LSS research, but LSS has also been adopted by other types of industries. The organizations following LSS have improved bottom-line results, improved company profitability and growth and enhanced customer satisfaction. In general the research is more interpretive in nature; there is still a lack of standard in the LSS implementation framework.

This study is limited to reviewing those articles which contain the word LSS appeared in the title.

This study will help understand the current state of research on LSS, various trends in the field, its applicability and future prospects of investigation in the field.

The literature in the field of Lean Six Sigma (LSS) is escalating with frameworks, but, till date, no effort has been made in existing literature to critically reviewing LSS frameworks. The aim of this paper is to investigate the literature about Lean, Six Sigma and LSS frameworks and critically reviewing the existing literature over numerous parameters.

This study focuses on a literature review of Lean, Six Sigma and LSS frameworks. The time span of this analysis is 30 years. The analysis is restricted to searching online databases such as Elsevier Science direct, Taylor and Francis, Emerald, Springer link, Wiley Inter-Science and Inder-Science. A total number of 58 frameworks have been used as sample size for this study. The study focuses on reviewing these 58 frameworks based on measures such as the novelty of frameworks, source of frameworks, framework verification, approach of verification and identification of vital elements/tools/constructs of frameworks and lastly comparative analysis of all these 58 frameworks

The analysis has identified major discrepancy such as laxity of researcher toward utilizing existing frameworks, lack of participation of practitioners and consultants in the development of LSS frameworks, and the elements/constructs used in structuring the frameworks are highly incoherent. Higher proportions of frameworks are verified through various modes of verification such as survey, case study, simulation, which encourages other researchers for applicability of the frameworks. Case study is found most popular research design method for verification of frameworks. Various frameworks are highly abstract or superficial. Some of the frameworks do not show how each construct/element are related to implementation in the organization. Out of 58 frameworks, the only single framework is highly comprehensive. A coherent framework for LSS is still lacking.

This analysis is limited to peer review articles from Elsevier Science direct, Taylor and Francis, Emerald, Springer link, Wiley Inter-Science and Inder-Science databases and contains the search keywords in title only.

This study is first of its kind attempt, making an effort to the knowledge of the authors to critically review Lean, Six Sigma and LSS frameworks. This analysis will assist to recognize the LSS filed trends and framework applicability.

Selective laser melting and electron beam melting processes are well-known for the additive manufacturing of metal parts. Metal powder bed fusion (MPBF) is a common term for them. The MPBF process can empower the manufacturing of intricate shapes by reducing the use of special tools, shortening the supply chain and allowing small batches. However, the MPBF process suffers from many quality issues. In literature, several works are recorded for qualification of the MPBF part. The purpose of this study is to recollect those works done for quality control and report their helpful findings for further research and development.

A systematic literature review was conducted to highlight the major quality issues in the MPBF process and its root causes. Further, the works reported in the literature for mitigation of these issues are classified and discussed in five categories: experimental investigation, finite element method-based numerical models, physics-based analytical models, in-situ control using artificial intelligence (AI) and machine learning (ML) methods and statistical approaches. A comparison is also prepared among these strategies based on their suitability and limitations. Additionally, improvements in MPBF printers are pointed out to enhance the part quality.

Analytical models require less computational time to simulate the MPBF process and need a smaller number of experiments to confirm the results. They can be used as an efficient process parameter planning tool to print metal parts for noncritical applications. The AI-ML based quality control is also suitable for MPBF processes as it can control many processing parameters that may affect the quality of the MPBF part. Moreover, capabilities of MPBF printers like thinner layer thickness, smaller beam diameter, multiple lasers and high build temperature range can help in quality control.

This study converts the piecemeal data on MPBF part qualification methods into interesting information and presents it in tabular form under each strategy. This tabular information provides the basis for further quality improvement efforts in the MPBF process.

This study references researchers and practitioners on recent quality control efforts and their significant findings for a better quality of MPBF part.

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.

The purpose of this paper is to present an attempt to develop an instrument containing operational measures of lean combined with safety and ergonomic conditions in a workstation or production line. This operational tool aims to help researchers and practitioners to prioritize and evaluate the lean implementations, as well as the ergonomic and safety conditions, in an integrated way.

Lean manufacturing methods and principles, as well as safety and ergonomics aspects, were exhaustively researched with the ultimate goal of finding a way to improve the workplace by taking into account the efficiency and well-being of workers. The instrument was validated in an interactive process between theory and practical insights. At the end, it was tested in several workstations/production areas.

The study reveals that high scores are derived from a good interaction between lean, ergonomics and safety.

It would be important to validate it in different companies and different types of industries because each one has its own characteristics.

This tool helps practitioners (technicians and ergonomic practitioners from manufacturing companies) assess the implementation of lean principles and the safety issues in their processes. It also allows managers to evaluate their business and identify the priority areas to improve according to the previously defined company’s aims.

As Peter Drucker said: “If you can’t measure it, you can’t improve it.” For a successful implementation, managers should start the lean journey with a lean assessment and make it in a regular basis. To the authors’ knowledge, there are various lean assessment tools, but this work is innovative because it provides an assessment instrument to evaluate organizations’ workstations/production areas simultaneously in three dimensions: lean, safety and ergonomic aspects.