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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 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.

While every firm is striving to embrace digital transformation (DT) to form new differentiating business capabilities, there are dark sides to such initiatives, and it is essential to acknowledge, identify and address them. The purpose of this paper is to identify and emperically demonstrate the impact of such darksides of DT. While a firm's DT effort may have many dark sides, the authors identify data breaches as the most critical one and focus on proving their impact since it can inflict significant damage to the firm.

Through the lens of paradox theory, the authors argue that the DT efforts of a firm will lead to increased risk and severity of data breaches. The authors developed a one-of-a-kind longitudinal data set by combining data from multiple sources, including 3604 brands over a 10-year period, and employed a DT performance scorecard to evaluate a firm's DT effort across four key digital selling touchpoints: site, mobile, digital marketing and social media.

The findings of this study show that a firm's DT efforts pertaining to its mobile and digital marketing platforms significantly increase the likelihood and severity of a data breach event indicating that these two channels are most vulnerable and need heightened attention from firms. Furthermore, the findings suggest that the negative repercussions of some DT initiatives may be minimized as the firm becomes more innovative. The findings can help firms re-strategize their DT efforts by promoting security and also encouraging a balanced communication strategy.

This research is one of the first to identify, recognize and empirically illustrate the downsides of a DT effort that is otherwise thought to provide only benefits.

This paper aims to develop an initial understanding of the Lean Six Sigma methodology since its inception and examine the few Lean Six Sigma dimensions as a research domain through a critical review of the literature.

The paper is structured in two-part. The first part of the paper attempts to dwell on the evolution of the Lean Philosophy and Six Sigma methodology individually and the emergence of Lean Six Sigma methodology, covered under the Lean Six Sigma: a historical outline section. The second part of the study examines the dimensions associated with Lean Six Sigma such as frameworks, critical success factors, critical failure factors, type of industry, performance metric, year, publisher and journal, based on a total of 223 articles published in 72 reputed journals from the year 2000 to 2019 as a literature review.

The adoption of Lean Six Sigma, as a continuous improvement methodology, has grown enormously in the manufacturing and few service sectors such as health care and higher education during the past decade. The study revealed that researchers came out with conceptual frameworks for the implementation of Lean Six Sigma, whereas the validation through case studies seems to be lacking. The integration of Lean Six Sigma and other approaches with a focus on sustainability and the environment has emerged as a research field. A few of the most common critical success and failure factors were identified from the articles studied during the study.

This paper may not have included some of the studies due to the inaccessibility and selection criteria followed for the study.

This paper will provide an initial introduction on Lean, Six Sigma and Lean Six Sigma and research insights Lean Six Sigma to beginners such as students, researchers and entry-level professionals.

This study aims to determine the extent to which the textile industry considers ecological issues in the supplier evaluation process by examining the relationships between environmental and operational criteria.

The supplier evaluation process within the industry was examined using the Fuzzy DEMATEL-based Analytic Network Process (FDANP) hybrid method. Criterion relationships were determined using the Fuzzy DEMATEL method. Two different ANP processes (the classical DANP approach and the new DANP approach) were used to assess the criterion weights, and the analysis results were compared. The satisfaction levels of suppliers with whom businesses collaborated were also examined using IPA analysis.

The results of the hybrid approaches with different steps in the study also differ. While the classic FDANP approach prioritizes cost and quality in the green supplier evaluation process, green products and EMS come to the fore according to the new FDANP approach. In addition, while businesses are satisfied with the operational performance of suppliers, their environmental performance remains below average.

This study was conducted in a sector-specific context, limited to Denizli province and green raw material suppliers.

This study revealed important findings regarding environmental awareness in buyer-supplier relations in the textile industry and offers a practical decision-making tool for decision- makers.

The results of this study may help industrial enterprises gain an environmental perspective when planning their operations to create a more sustainable environment.

This study contributes to the literature from a holistic perspective by examining the role and importance of operational and environmental criteria in the green supplier evaluation process in the textile industry.

This paper aims to present a predictive model approach to estimate the tensile behavior of polylactic acid (PLA) under uncertainty using the fused deposition modeling (FDM) and American Society for Testing and Materials (ASTM) D638’s Types I and II test standards.

The prediction approach combines artificial neural network (ANN) and finite element analysis (FEA), Monte Carlo simulation (MCS) and experimental testing for estimating tensile behavior for FDM considering uncertainties of input parameters. FEA with variance-based sensitivity analysis is used to quantify the impacts of uncertain variables, resulting in determining the significant variables for use in the ANN model. ANN surrogates FEA models of ASTM D638’s Types I and II standards to assess their prediction capabilities using MCS. The developed model is applied for testing the tensile behavior of PLA given probabilistic variables of geometry and material properties.

The results demonstrate that Type I is more appropriate than Type II for predicting tensile behavior under uncertainty. With a training accuracy of 98% and proven presence of overfitting, the tensile behavior can be successfully modeled using predictive methods that consider the probabilistic nature of input parameters. The proposed approach is generic and can be used for other testing standards, input parameters, materials and response variables.

Using the proposed predictive approach, to the best of the authors’ knowledge, the tensile behavior of PLA is predicted for the first time considering uncertainties of input parameters. Also, incorporating global sensitivity analysis for determining the most contributing parameters influencing the tensile behavior has not yet been studied for FDM. The use of only significant variables for FEA, ANN and MCS minimizes the computational effort, allowing to simulate more runs with reduced number of variables within acceptable time.

Aluminium is the most proficiently and commonly used metal due to its desirable physical, chemical and mechanical properties. When Aluminium reinforced with hard ceramic particles, shows increased strength and good corrosion resistant and wear resistant qualities. In the present investigation, A390 + X vol. % Zro₂ (X = 5, 10 and 15) composites have been fabricated through P/M technique.

After that the microstructural properties are tested by scanning electron microscope (SEM) analysis wear test is performed using pin-on-disc machine.

The wear conditions of applied load 30N and sliding velocity 1 m/s and track distance 1000m was followed. A390 + 15% Zro₂ of surface of the composites unveiled greater hardness when compared with A390 alloy.

A390 + 15% Zro₂ exhibited superior wear resistance than that of the matrix alloy. Thus the material proves as an excellent solution for applications that requires high wear resistance.

This study aims to investigate the connection between the circular economy and sustainable operations management to identify the challenges and opportunities in platform organizations. The study looks at how the stated circular economy strategies (Reduce, Reuse, Repair, Refurbish, Repurpose and Recycle) are integrated across different industries, emphasizing how they align with the e-business model. The research evaluates their contribution to achieving Sustainable Development Goal 12, which focuses on responsible consumption and production.

A literature review has analyzed CE frameworks, business models and the role of sustainable operations management practices. This study utilized secondary data analysis of platform organizations and insights from case studies to identify patterns, strategies and outcomes. The study also involved practical examinations within organizations, specifically focusing on innovative start-ups.

The analysis uses the 6R framework (Reduce, Reuse, Repair, Refurbish, Repurpose and Recycle) to uncover valuable insights into organizational practices and highlight the role of platform organizations in promoting and achieving circular economy objectives. The research findings focus on the central importance of data regulation and governance while showcasing sustainable business practices through platform organizations.

This research is significant as it connects circular economy with platform organizations’ business models, emphasizing data regulation, resource efficiency, waste reduction and aligning business practices with Sustainable Development Goal 12.