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The purpose of this study is to present the systematic literature review (SLR) on Lean Six Sigma (LSS) by exploring the state of the art on growth of literature on LSS within the manufacturing sector, critical factors to implement LSS, the role of LSS in the manufacturing sector from an implementation and sustainability viewpoint and Industry 4.0 viewpoints while highlighting the research gaps.

An SLR of 2,876 published articles extracted from Scopus, WoS, Emerald Insight, IEEE Xplore, Taylor & Francis, Springer and Inderscience databases was carried out following the protocol of systematic review. In total, 154 articles published in different journals over the past 10 years were selected for quantitative and qualitative analysis which revealed a number of research gaps.

The findings of the SLR revealed the growth of literature on LSS within the manufacturing sector. The review also highlighted the most cited critical success factors, critical failure factors, performance indicators and associated tools and techniques applied during LSS implementation. The review also focused on studies related to LSS and sustainability viewpoint and LSS and Industry 4.0 viewpoints.

The findings of this SLR can help senior managers, practitioners and researchers to understand the current developments and future requirements to adopt LSS in manufacturing sectors from sustainability and Industry 4.0 viewpoints.

Academic publications in the context of the role of LSS in various research streams are sparse, and to the best of the authors’ knowledge, this paper is one of the first SLRs which explore current developments and future requirements to implement LSS from sustainability and Industry 4.0 perspective.

This study aims to identify, analyze and rank the critical success factors (CSFs) of Lean Six Sigma (LSS) implementation in Indian manufacturing sector based micro, small and medium enterprises (MSMEs). This study provides critical insight for managers and researchers aspiring for successful implementation of LSS in Indian manufacturing MSMEs.

The CSFs were extracted from literature followed by a questionnaire-based survey from 120 industry professionals with extensive knowledge and experience about LSS working in Indian manufacturing MSMEs. Further, the CSFs were grouped based on their fundamental relevance and ranked using best worst method (BWM) approach using inputs from LSS experts.

This study provides insights on success factors that have helped Indian manufacturing MSMEs to implement LSS. The findings signify that “Strategy based CSFs” were ranked as the top most important factors, followed by two other category factors namely “Bottom-Line CSFs” and “Supplier based and other category-based CSFs”.

The proposed research is specifically relevant to the context of MSMEs in the Indian manufacturing sector. In the future, the same approach can be extended to a global context, encompassing service sector-based MSMEs in healthcare and finance.

This study provides valuable inputs for managers, decision-makers, industrial practitioners and researchers about Indian manufacturing MSMEs. The identified CSFs and their prioritization offer a roadmap for successful adoption of LSS. Managers can allocate resources, and make strategic decisions based on the prioritized CSFs. Decision-makers can align their initiatives with the identified CSFs. Industrial practitioners gain insights to enhance their LSS initiatives, and researchers can focus their efforts on areas critical to LSS implementation in Indian MSMEs. Furthermore, the structured approach employed in this study can be adopted by various MSME sectors globally, thereby broadening the comprehension of LSS implementation.

This study contributes to the existing body of knowledge by addressing the gaps in literature on CSFs related to LSS adoption within Indian manufacturing MSMEs. While LSS has been widely studied, there is limited focus on its adoption in the context of Indian MSMEs. The combination of extensive literature review, questionnaire-based survey and the application of the BWM approach for prioritizing CSFs adds originality to the research.

The purpose of this study is to examine the postprocessed wire tool surface using scanning electron microscopy and find out the streamlined conditions of input process variables using multi-objective optimization techniques to get minimum wire wear values.

A federated mode of response surface methodology (RSM) and artificial neural network (ANN) is used to optimize the process variables during the machining of a nickel-based superalloy.

The study explores that with the rise in spark-off time and spark gap voltage, the rate of wire tool consumption also escalates.

Most of the researchers used the RSM technique for the optimization of process variables. The RSM generates a second-order regression model during the modeling and optimization of a manufacturing process whose major limitation is to fit the collected data to a second-order polynomial. The leading edge of ANN on the RSM is that it has comprehensive approximation capability, i.e. it can approximate virtually all types of nonlinear functions, including quadratic functions also.

The purpose of this paper is to prioritize and establish relationships among the barriers that affect green, lean and Six Sigma (GLSS) implementation in the Indian construction sector.

A hierarchal model consisting of several levels is generated by the interpretive structural modelling (ISM) methodology. For establishing the priority weights and the ranking of the barriers, the relationships among barriers from the model in ISM are used to provide an output from the analytic network process (ANP). The 12 vital barriers that affect implementation of GLSS adoption were shortlisted from literature and then finalized in consultation with experts belonging from both industry and academia.

Based on the ISM model “Lack of awareness for green products, Lack of top management commitment and involvement as well as Lack of funds along with an improper estimation” are at the highest level. Similar results were found while ranking the barriers through ISM–ANP integration.

This study identified and prioritized the barriers that affect GLSS implementation using ISM–ANP approach, such a study has not been attempted previously for the construction sector. The ISM model and ANP ranks are based on the inputs gathered from experts and academicians so as to ensure practical validity. This approach is assists decision-makers to focus on the key barriers priority basis and enables them to implement GLSS smoothly.

Six Sigma within small and medium‐sized enterprises (SMEs) is rapidly emerging as the new wave of change in Six Sigma. The purpose of this paper is to review the implications of applying Six Sigma methodology over the SMEs, taking a specific case of a bicycle chain manufacturing unit. The study could be a paradigm initiative towards high quality products and services at low cost for every SME.

Based on the literature, this paper proposes a process flow chart to present a one‐shot picture of the Six Sigma application in a bicycle chain manufacturing unit which falls in an SME environment. The methodology adopted is DMAIC methodology of Six Sigma, which had been mostly successful so far in large‐scale industries. The methodology has been applied to reduce the bush rejection rate (bush is an important component of a cycle chain) by reducing defects inherent in the processes. The statistical techniques such as two sample t‐test and process capability analysis have been used to establish the process capability before and after the Six Sigma application.

This paper is an attempt to justify the highly useful role of quality management techniques like Six Sigma for SMEs which are normally presumed to be in the domain of large industries. In this paper, Six Sigma methodology has been applied to a small unit manufacturing bicycles chains with dwindling productivity levels. After applying Six Sigma it was found that the chain manufacturing firm can increase its profit by controlling high rejection rate of cycle chain bush. Application of Six Sigma project recommendation brought up the process sigma level to 5.46 from 1.40 by reduction in bush diameter variation in the process of bicycle chain bush manufacturing. This increase in sigma level is equivalent to monetary saving of Rs 0.288 million per annum, which is a noteworthy figure for an industry of such level. The success of this study paves the way to further extend the Six Sigma application to more such industries working in the SME environment.

This paper provides documented evidence of Six Sigma implementation in a bicycle chain manufacturing unit which has been taken as representative of a small and medium‐size industry. The study will yield a great value to academics, consultants, researchers and practitioners of Six Sigma.

The purpose of this paper is to uncover the significance of quick changeovers in die‐casting foundry environments.

The paper gives set‐up instructions and guidelines to prepare the standardized set‐up procedure without ignoring actual constraints in foundries. It uses a case study in a medium scale piston foundry to generate an integrated set‐up reduction approach, utilizing single minute exchange of die (SMED)‐based industrial engineering tools to achieve faster set‐ups. It describes the feasibility of quick changeovers in foundry small and medium enterprises based on a “SMED” approach. Finally, the paper carries out empirical analysis of the financial/non‐financial benefits incurred from set‐up reductions.

Set‐up activities are a vital part of the production lead‐time of any product and so affect overall product cost. Tools like Pareto analysis, root‐cause analysis and method study have been used to analyze the existing procedure of set‐ups. A SMED approach can help eliminate unwanted activities, externalize the internal activities, if possible and reduce them by simplification or standardization. The application of other tools such as 5S, Poke‐Yoke and specific tool‐kits are suggested to further reduce set‐up times.

The paper demonstrates the practical application of SMED showing how it can bring real breakthroughs in productivity to small and medium scale foundries.

The purpose of this paper is to investigate the applicability of lean and green practices to foundry industry in India for improving productivity and eliminating waste, incorporating the sustainability into business performance measures.

The study used survey questionnaire method to collect data against 16 lean and green practices from 71 middle- to senior-level professionals belonging to Indian foundry industry. The survey instrument of lean and green practices was developed based on a number of sources from the literature and formal discussions with academicians and foundry industry professionals. The responses were received on a five-point Likert scale ranging from least applicable to most applicable. Exploratory factor and reliability analyses are conducted to obtain and validate constructs and measure each constructs Cronbach’s α (i.e. a consistency coefficient). The lean and green practices are categorized into the four constructs, namely, workplace organization practices, management practices, inventory control practices, and industrial manufacturing and quality improvement practices. Further, descriptive statistics is employed to find out the relative significance of lean and green practices.

Factor and reliability analyses show that all four constructs are adequate and reliable to illustrate lean and green practices. Descriptive statistics indicates that lean and green practices are applicable for implementation to a certain extent in the foundry industry. Correlation analysis shows that lean practices are positively and moderately interrelated with green practices. Thus, the results present a strong evidence that lean and green practices are moderately applicable for implementation in the foundry industry.

The paper provides insights into the applicability of lean and green practices implementation in the context of a developing country and presents evidence that lean and green practices are moderately applicable in the foundry industry. In addition, this paper is one of the few efforts to promote sustainable development within the industry.

An integrated intuitionistic fuzzy (IF) modelling-based framework for examining the performance analysis of a packaging unit (PU) in three different stages has been proposed.

For the series and parallel configuration of PU, a mathematical model based on the intuitionistic fuzzy Lambda–Tau (IFLT) approach was developed in order to calculate various reliability parameters at various spreads. For determining membership and non-membership function-based reliability parameters for the top event, AND/OR gate transitions expression was employed.

For 15%–30% spread, unit’s availability for the membership function falls by 0.006442%, and it falls even more by 0.014907% with an increase in spread from 30% to 45%. In contrast, for 15%–30% spread, the availability of non-membership function-based systems reduces by 0.007491% and further diminishes. Risk analysis has presented applying an emerging approach called intuitionistic fuzzy failure mode and effect analysis (IFFMEA). For each of the stated failure causes, the output values of the intuitionistic fuzzy hybrid weighted Euclidean distance (IFHWED)-based IFFMEA have been tabulated. Failure causes like HP1, MT6, FB9, EL16, DR23, GR27, categorized under subsystems, namely hopper, motor, fluidized bed dryer, distributor, grader and bin, respectively, with corresponding IFFMEA output scores 1.0975, 1.0190, 0.8543, 1.0228, 0.9026, 1.0021, were the most critical one to contribute in the system’s failure.

The limitation of the proposed framework lies in the fact that the results obtained for both reliability and risk aspects mainly depend on the correctness of raw data provided by the experts. Also, an approximate model of PU is obtained from plant experts to carry performance analysis, and hence more attention is required in constructing the model. Under IFLT, reliability parameters of PU have been calculated at various spreads to study and analyse the failure behaviour of the unit for both membership and non-membership function in the IFS of [0.6,0.8]. For both membership- and non-membership-based results, availability of the considered system shows decreasing trend. To improve the performance of the considered system, risk assessment was carried using IFFMEA technique, ranking all the critical failure causes against IFHWED score value, on which more attention should be paid so as to avoid sudden failure of unit.

The livelihood of millions of farmers and workers depends on sugar industries. So perpetual running of these industries is very important from this viewpoint. On the basis of findings of reliability parameters, the maintenance manager could frame a correct maintenance policy for long-run availability of the sugar mills. This long-run availability will generate revenue, which, in turn, will ensure the livelihood of the farmers.

Mathematical modelling of the considered unit has been done applying basic expressions of AND/OR gate. IFTOPSIS approach has been implemented for ranking result comparison obtained under IFFMEA approach. Eventually, sensitivity analysis was also presented to demonstrate the stability of ranking of failure causes of PU.