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In a quest to meet increasing pressure to incorporate environmental and sustainability factors due to the legislations and growing public awareness, companies are rethinking of strategizing their supply chain network to take control of the reverse flow of products as well. This growing interest has also led to tremendous growth in publications occurring in several reputed journals in the last few years. In this context, the purpose of this article is to perform a systematic literature survey of recent and state-of-the-art papers in order to draw insights and highlight the future directions.

This paper has selected and reviewed 204 papers published from the year 2002–2017. The papers were collected from the web of science and Google scholar database which have the DOI number. The selected papers were then categorized into main five core areas of RSC management namely reverse supply chain (RSC), Reverse Logistics (RL), Remanufacturing, Closed-Loop Supply Chain (CLSC) and Product Recovery Systems (PRS) and then analyzed with great detail. Finally, the research gaps that were identified from the study have been highlighted for future research opportunities.

This paper would serve as a roadmap to the managers who wish to align their forward and reverse supply chains for overall growth and development. It provides an in-depth knowledge on RSC to the researchers working in this domain. The scholars would be able to identify the areas of RSC which have been already addressed and the areas which remain unaddressed.

This paper presents a systematic literature survey of state-of-the-art papers that was published in the reputed journal in the area of RSC. Total 204 numbers of papers which were published in the reputed journals between 2002 and 2017 are reviewed, categorized and analysed to draw the opportunities and future research direction in the area of RSC.

The present paper proposes a framework for zero-defect manufacturing in Indian industries. Due to the current competitive market, there is a strong need to achieve zero defects from the customer's perspective. A survey questionnaire is analyzed based on the responses and a structured framework is drafted to implement zero defect manufacturing in the Indian industry.

To analyze zero-defect in Indian industries, a literature review and a survey questionnaire constituted a framework. This framework is independent of the type of process and product.

The findings of this study are based on a total of 925 responses received through survey questionnaires by different mediums. The framework has been tested in different manufacturing organizations to achieve zero-defect through the continuous improvement approach.

The study results aim to achieve zero-defect, help to improve customer satisfaction, reduce waste and rework in the manufacturing process. This framework is also used as a problem-solving approach to implement Six Sigma in the Indian industries.

Zero defect manufacturing is growing in India and globally. This framework helps to implement zero defect manufacturing in Indian industries. It is an essential tool to capture the voice of the customer.

Sustainable human resource management highlights the importance of the eighth sustainable development goal, “decent work and economic growth”. Thus, the purpose of this study is to align human resource practices and policies with Industry 4.0 is imperative.

The authors aimed to identify key challenges of sustainable human resource implementation in view of Industry 4.0 and to analyse these identified challenges by prioritising them for effective Industry 4.0 implementation in an emerging economy such as India. A mixed-methods approach was utilised to prioritise identified challenges. Semi-structured interviews were conducted with experts, academicians and industry mangers. Transcribed interviews were run in NVivo to emerge into broad themes/challenges, which were prioritised using fuzzy best–worst methodology.

The performance appraisal challenge holds maximum importance, followed by learning and development. This finding signifies the need for instilling job security and continuous learning opportunities for employees amidst all disruption caused by Industry 4.0.

This work enhances the link between sustainability, disruptive technologies and Industry 4.0 to transform economic outlooks, leading to improvement under economic aspects through the adoption of sustainable human resource practices into workplaces and society.

Sustainable human resource management has mostly focused on employee welfare. However, the major challenges of disruption caused by Industry 4.0 have not been addressed in the literature. The upskilling and reskilling requirements due to disruptions by Industry 4.0 range from recruitment to performance appraisal and every facet that relates to an employee's cycle in a company. Hence, there is a need to identify critical challenges for optimum adaptation to upcoming industry demands.

Urbanization and globalization in India have led to the depletion of resources and degradation of the environment to meet the demands. Because of these issues, researchers and practitioners have begun to study various strategies to reduce the level consumption of resources to utilize it for present and future needs. In pursuit of finding solutions to the problems, sustainable building construction is found as the best key to avoid depletion of resources. Sustainable material selection is found as a vital strategy in construction. The paper aims to discuss this issue.

A three-phase methodology is proposed for framing the assessment model for construction industries to select materials for construction. In the first phase, a total of 23 sub-criteria of triple bottom line (TBL) and four brick materials as alternatives were identified. The second phase finds the weights and ranks of criteria and sub-criteria using the best worst methodology (BWM) the third phase involves ranking of materials concerning sub-criteria weights determined in phase II using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).

The objective of study is fixed to identify the criteria list for the selection of material in construction industries from the literature review especially for Indian construction industries; to rank the criteria for selection of materials with the help of the BWM approach; and to prioritize the identified materials in the view of sustainability with the help of Fuzzy TOPSIS in construction industries perspective. This study analyzed and choosing right sustainable materials by the three pillars of sustainability which are the environment, economic and social, also called TBL, for Indian construction companies by framing a sustainable material assessment model.

The results of this study facilitate to frame an assessment model for evaluating and selecting sustainable building materials.

The purpose of this paper is to improve the yield of a particular model of a car windshield, as the organization faces losses due to poor performance and rejection.

The Six Sigma DMAIC (define, measure, analyze, improve and control) methodology is used to reduce variation and defects in the process. It is a methodology based on data-driven and fact-based analysis to find out the root cause of the problem with the help of statistical analysis. A worst performing model is selected as a case study through the scoping tree. The preprocess, printing, bending and layup process defects are reduced by analyzing the potential causes and hypothesis testing.

This paper describes Six Sigma methodology in a glass manufacturing industry in India for automotive applications. The overall yield of a car windshield achieved 93.57 percent against the historical yield of 88.4 percent, resulting in saving 50 lacs per annum. Due to no rework or repairing in the glass, low first-time yield causes major losses. Process improvement through focused cross-functional team reduces variation in the process. Six Sigma improves profitability and reduces defects in the automotive glass manufacturing process.

This case study is applied in automotive glass manufacturing industries. For service and healthcare industries, a similar type of study can be performed. Further research on the common type of processor industry would be valuable.

The case study can be used as a problem-solving methodology in manufacturing and service industries. The tools and techniques can be used in other manufacturing processes also. This paper is useful for industries, researchers and academics for understanding Six Sigma methodology and its practical implementation.

This case study is an attempt to solve automobile glass manufacturing problems through DMAIC approach. The paper is a real case study showing benefits of Six Sigma implementation in the manufacturing industry and saving an annual cost of 50 lacs due to rejections in the process.

This study explains the importance of performance measures and identifies the specific performance measures of sustainable lean manufacturing (SLM) for automobile industries. Awareness towards sustainability and continuous improvement approaches demand monitoring of the sustainable lean impact on organization/industry, and hence, identifying the specific performance metrics is of peak importance.

In this study, specific metrics for social, economic and environmental performance are identified from a systematic literature review of 82 significantly related journal articles. The importance of the identified metrics is assessed with the help of questionnaire responses from a group of industrial experts.

Performance indicators are statistically analyzed category wise and assessed. The key metrics are summarized based on the survey data followed by a discussion with industrial experts. From this study, performance measures have been identified and validated through hypothesis testing for Indian automobile industries. Certification of IATF16949 implementation found an important vertical for SLM implementation. In this study, SLM implementation initiatives are discussed, and reward scheme for outstanding performers are identified as important initiatives are followed by small improvement culture.

The proposed discussion of this study is useful for industrialist and researchers, as SLM performance measures are well explained for Indian automobile industries. In this study, future research direction is also explained related to other industries. These summarized performance measures will help to maintain SLM in industries.

This paper presents the original literature review based on the study of SLM, as no extensive study is available where SLM performance measure explained for automobile industries. Key initiatives and vertical of SLM are well explained for Indian automobile industries. This study proposed a complete framework for SLM implementation considering competitive manufacturing targets.

The aim of this research is to assess the key enablers of Industry 4.0 (I4.0) in the context of the Indian automobile industry. It is done to apprehend their comparative effect on executing I4.0 concepts and technology in manufacturing industries, in a developing country context. The progression to I4.0 grants the opportunity for manufacturers to harness the benefits of this industry generation.

The literature related to I4.0 has been reviewed for the identification of key enablers of I4.0. The enablers were further verified by academic professionals. Additionally, key executive insights had been revealed by using interpretive structural modelling (ISM) model for the vital enablers unique to the Indian scenario. The authors have also applied MICMAC analysis to group the enablers of I4.0.

The analysis of this study’s data from respondents using ISM provided us with seven levels of enabler framework. This study adds to the existing literature on I4.0 enablers and findings highlight the specificities of the territories in India context. The results show that top management is the major enabler to I4.0 implementation. Infact, it occupies the 7th layer of the ISM framework. Subsequently, government policies enable substantial support to develop smart factories in India.

The findings of this work provide implementers of I4.0 in the automobile industry in the form of a robust framework. This framework can be followed by the automobile sector in enhancing their competency in the competitive market and ultimately provide a positive outcome for the Indian economic development led by these businesses. Furthermore, this work will guide decision-makers in enabling strategic integration of I4.0, opening doors for the development of new business opportunities as well.

The study proposes a framework for Indian automobile industries. The automobile sector was chosen for this study as it covers a large percentage of the market share of the manufacturing industry in India. The existing literature does not address the broader picture of I4.0 and most papers do not provide validation of the data collected. This study thus addresses this research gap.

Selection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.

A group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.

A closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.

The presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.