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The integration of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) is an emerging model, and the global pressure of various stakeholders raises scepticism of any emerging model towards providing sustainability. Therefore, this research aims to identify and rank the potential significant drivers of an integrated model of I4.0 and TPM to guide manufacturing enterprises towards sustainability.

This research follows a four-phase methodology including literature review and expert opinion to select the sustainability indicators and I4.0-integrated TPM key drivers, followed by employing the analytic hierarchy process approach for weight determination of sustainability indicators. The research then deploys the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritise the I4.0-integrated TPM key drivers based on their effect on various sustainability indicators. Finally, a sensitivity analysis is conducted to check the robustness of the TOPSIS.

The findings establish the top five most influential key drivers of an I4.0-integrated TPM system, which include top management support, formal I4.0 adoption program, mid-management involvement and support, solid TPM baseline knowledge and high engagement of the production team. These top drives can lead manufacturing firms towards sustainability.

The digitalisation of shop floor practices, such as TPM, could be adapted by shop floor managers and policymakers of manufacturing companies to deliver sustainability-oriented outcomes. In addition, this research may aid decision-makers in the manufacturing sector in identifying the most important drivers of I4.0 and TPM, which will assist them in more effectively implementing an integrated system of I4.0 and TPM to practice sustainability. The scope of TPM applicability is wide, and the current research is limited to manufacturing companies. Therefore, there is a huge scope for developing and testing the integrated system of I4.0 and TPM in other industrial settings, such as the textile, food and aerospace industries.

This research makes a first-of-its-kind effort to examine how an I4.0-integrated TPM model affects manufacturing companies' sustainability and how such effects might be maximised.

Scarcity of resources, ecological imbalance, global warming, rising energy prices and the ever-changing need for variety have attracted the government and manufacturers for sustainable development of the industries. The integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS) provides a solid platform for meeting both the customers’ variety needs and business sustainability requirements. Many organizations opted for ISGLSAMS, but still due to various barriers organizations are not able to fully implement ISGLSAMS. The purpose of this paper is to identify the barriers to the ISGLSAMS, so that a more sustainable industrial manufacturing system and industrial symbiosis can be developed.

A literature review, from the Web of Science and Google Scholar database, has been carried out to identify the various barriers to the implementation of ISGLSAMS in the entire value chain. A total of 168 research papers have been reviewed for identifying the ISGLSAMS barriers.

This paper elaborates the concept of the ISGLSAMS, its attributes and various barriers and contributes to a better understanding and successful implementation of ISGLSAMS to meet business’ sustainability and market performance goals in the entire value chain. The paper also projects the future research framework and directions for the ISGLSAMS, integrated sustainable-green-lean-six sigma-agile (ISGLSA) product and ISGLSA supply and value chain.

The study contributes to a better understanding of ISGLSAMS’ barriers. The government, stakeholders and policymakers may plan the policy, road map and strategies to overcome the ISGLSAMS’ barriers. In-depth knowledge of subclauses of ISGLSAMS’ barriers will help the practitioners to overcome the ISGLSAMS’ barriers strategically. By overcoming the ISGLSAMS barriers, a more sustainable 7 Rs based market focused manufacturing system can be designed. This will also increase the opportunities to enhance the industrial ecology, industrial symbiosis and better recovery of the product, process and supply chain residual value. This will reduce the waste to the ecosystem.

This work has been carried out in search of a more sustainable manufacturing system, i.e. ISGLSAMS (which is 7 Rs based, i.e. 6 Rs of sustainability with 7th R, reconfiguration) to meet the customer variety needs along with sustainability in the ever-changing customer market. This study adds value to the practitioners to identify and prioritize the ISGLSAMS’ industry-specific barriers and design the solution for the more sustainable development of (1) industries, (2) the industrial symbiosis system and (3) the ISGLSA product, process, system and supply value chain with minimum resource consumption and environmental impact. The research also contributes to the (a) ISGLSAMS (b) ISGLSA supply chain (c) reconfigurable, sustainable and modular products and (d) redesign, recovery and refurbishing of the product to increase the product life cycle.

The study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance. Integrating lean and Industry 4.0 as the two industrial approaches is synergetic in providing operational benefits such as increasing flexibility, improving productivity, reducing cost, reducing delivery time, improving quality and value stream mapping (VSM). There is an urgent need to understand the integrated potential of OPEX strategies like lean manufacturing and also to determine the challenges for manufacturing SMEs and further suggest a strategic roadmap for the future.

The current work has used a combined approach on interpretative structural modeling (ISM) and fuzzy Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) approach to structure the multiple level analysis for the implementation challenges to integrate OPEX strategies with Industry 4.0.

The research has found that the indulgence of various implementation issues like lack of standardization, lack of vision and lack of trained support, all are the major challenges that inhibit the integration of OPEX strategies with I4.0 technologies in manufacturing.

The research has investigated the internal factors acting as a roadblock to lean and Industry 4.0 adoption. Further studies may consider external factors to lean and Industry 4.0 implementation. Also, further research may consider other operational excellence approaches and extend further to relevant sectors.

This study provides the analysis of barriers that is useful for the managers to take strategic actions for implementing OPEX strategies with I4.0 in smart manufacturing.

The research determines the adoption challenges towards the integrated framework. This is the first study to explore challenges in integrating OPEX strategies with I4.0 technologies in manufacturing SMEs.

The purposes of this paper are (1) to identify and rank the various enablers for an integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS), and (2) to study their correlations and their impact on organizational performance.

Three tiers methodology is used to analyze the enablers for the successful adoption of ISGLSAMS. First, a total of 32 ISGLSAMS enablers are identified through a comprehensive literature review. Then, data are collected with a structured questionnaire from 108 Indian manufacturing industries. Then, an analytic approach is used to analyze (1) the relevance and significance of enablers and (2) their correlations (1) with each other, and (2) with the organizational performance outcomes, to strengthen the understanding of ISGLSAMS.

The findings suggest that top management commitment, sustainable reconfigurable manufacturing system, organization resources for 6 Rs, customers' and stakeholders' involvement, corporate social responsibility (CSR), customers and stakeholders-focused strategic alliances, dynamic manufacturing strategies, use of information and communication technology, concurrent engineering, standardized tasks for continuous improvement, virtual network of supply chain partners, real-time monitoring and control, training and education, employees' involvement and empowerment enablers are the higher level enablers for the adoption of ISGLSAMS. Findings also suggest that there is a scope for research in the incorporation of lot size reduction, Keiretsu-Kraljic supply chain relationship strategy, external collaborations with the stakeholders other than supply chain members, matrix flatter organization structure, employees' career development, justified employees' wages, government support for research fund and subsidies and vendor-managed inventory practices for ISGLSAMS. Top management commitment, sustainable reconfigurable manufacturing system, organization resources for 6 Rs, corporate social responsibility (CSR), dynamic manufacturing strategies, use of information and communication technology, concurrent engineering, virtual network of supply chain partners, real-time monitoring and control, training and education, employees' involvement and empowerment have a significant effect on (1) sustainable product design, (2) sustainable production system, (3) improvement in the sale, (4) improvement in market responsiveness, (5) improvement in the competitive position and (6) improvement in the global market image.

Through this study of ISGLSAMS enablers and their interdependence, and their impact on ISGLSAMS performance outcomes government, organizations, stakeholders, policymakers and supply chain partners may plan the policy, roadmap and strategies for the successful adoption of (1) ISGLSAMS in the organizational value chain, and (2) Industrial ecology and industrial symbiosis in India. The study also contributes to the industrial managers, and value chain partners a better understanding of ISGLSAMS.

This study is the first attempt to understand (1) the ISGLSAMS enablers and their correlations, and (2) the effect of ISGLSAMS enablers on ISGLSAMS performance outcomes to get the competitive and sustainability advantage. The study contributes to the practitioners, policymakers, organizations, government, researchers and academicians a better understanding of ISGLSAMS enablers and its performance outcomes.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

Industry 4.0 has been identified as a key cornerstone to modernise economies where man and machines complement each other seamlessly to achieve synergies in decision-making and productivity for contributing to SDG 8: Decent Work and Economic Growth and SDG 9: Industry, Innovation and Infrastructure. The integration of Industry 4.0 remains a challenge for the developing world, depending on their current status in the industrial revolution journey from its predecessors 1.0, 2.0 and 3.0. This chapter reviews reported findings in literature to highlight how robotics and automated systems can pave the way to implementing and applying the principles of Industry 4.0 for developing countries like Mauritius, where data collection, processing and analysis for decision-making and prediction are key components to be integrated or designed into industrial processes centred heavily on the use of artificial intelligence (AI) and machine learning techniques. Robotics has not yet found its way into the various industrial sectors in Mauritius, although it has been an important driver for Industry 4.0 across the world. The inherent barriers and transformations needed as well as the potential application scenarios are discussed.

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

Quality 4.0 (Q4.0) leverages new emerging technologies to achieve operational excellence and enhance performance. Implementing Q4.0 in digital manufacturing can bring about reliable, flexible and decentralized manufacturing. Emerging technologies such as Non-Fungible Tokens (NFTs), Blockchain and Interplanetary File Storage (IPFS) can all be utilized to realize Q4.0 in digital manufacturing. NFTs, for instance, can provide traceability and property ownership management and protection. Blockchain provides secure and verifiable transactions in a manner that is trusted, immutable and tamper-proof. This research paper aims to explore the concept of Q4.0 within digital manufacturing systems and provide a novel solution based on Blockchain and NFTs for implementing Q4.0 in digital manufacturing.

This study reviews the relevant literature and presents a detailed system architecture, along with a sequence diagram that demonstrates the interactions between the various participants. To implement a prototype of the authors' system, the authors next develop multiple Ethereum smart contracts and test the algorithms designed. Then, the efficacy of the proposed system is validated through an evaluation of its cost-effectiveness and security parameters. Finally, this research provides other potential applications and scenarios across diverse industries.

The proposed solution's smart contracts governing the transactions among the participants were implemented successfully. Furthermore, the authors' analysis indicates that the authors' solution is cost-effective and resilient against commonly known security attacks.

This study represents a pioneering endeavor in the exploration of the potential applications of NFTs and blockchain in the attainment of a comprehensive quality framework (Q4.0) in digital manufacturing. Presently, the body of research on quality control or assurance in digital manufacturing is limited in scope, primarily focusing on the products and production processes themselves. However, this study examines the other vital elements, including management, leadership and intra- and inter-organizational relationships, which are essential for manufacturers to achieve superior performance and optimal manufacturing outcomes.

To facilitate the achievement of Q4.0 and empower manufacturers to attain outstanding quality and gain significant competitive advantages, the authors propose the integration of Blockchain and NFTs into the digital manufacturing framework, with all related processes aligned with an organization's strategic and leadership objectives.

This study represents a pioneering endeavor in the exploration of the potential applications of NFTs and blockchain in the attainment of a comprehensive quality framework (Quality 4.0) in digital manufacturing. Presently, the body of research on quality control or assurance in digital manufacturing is limited in scope, primarily focusing on the products and production processes themselves. However, this study examines the other vital elements, including management, leadership and intra- and inter-organizational relationships, which are essential for manufacturers to achieve superior performance and optimal manufacturing outcomes.