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This study aims to provide a systemic and integrated view of how Industry 4.0 and its enabling technologies affect companies' internal and external environments. It offers a comprehensive view of the contribution about ten years after the start of the Fourth Industrial Revolution.

The study performs a systematic literature review based on Industry 4.0 management literature. Analyzing the results of the 308 final papers in the sample made it possible to build a theoretical model to explain the contribution of Industry 4.0 to the internal and external environment of the company.

The results highlight the contribution of Industry 4.0 to the processes and environment of the company by providing a systemic and integrated view, highlighting the most applied enabling technologies and their internal, external, and combined usefulness in business processes.

Finally, the paper provides a broad view of the Industry 4.0 topic ten years after its origin through an extensive literature analysis that allows us to highlight the significant studies and the areas still under-researched by researchers and opens the debate on the Industry 5.0 scenario.

The model makes it possible to appreciate the role of Industry 4.0 and its enabling technologies in companies in a broad and systemic view and to understand, from a managerial point of view, the interactions, synergies, and possibilities within processes and the reflection on the external environment.

Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

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.

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

Additive manufacturing also known as 3D printing is an evolving advanced manufacturing technology critical for the new era of complex machinery and operating systems. Manufacturing systems are increasingly faced with risk of attacks not only by traditional malicious actors such as hackers and cyber-criminals but also by some competitors and organizations engaged in corporate espionage. This paper aims to elaborate a plausible risk practice of designing and demonstrate a case study for the compromised-based malicious for polymer 3D printing system.

This study assumes conditions when a machine was compromised and evaluates the effect of post compromised attack by studying its effects on tensile dog bone specimens as the printed object. The designed algorithm removed predetermined specific number of layers from the tensile samples. The samples were visually identical in terms of external physical dimensions even after removal of the layers. Samples were examined nondestructively for density. Additionally, destructive uniaxial tensile tests were carried out on the modified samples and compared to the unmodified sample as a control for various mechanical properties. It is worth noting that the current approach was adapted for illustrating the impact of cyber altercations on properties of additively produced parts in a quantitative manner. It concurrently pointed towards the vulnerabilities of advanced manufacturing systems and a need for designing robust mitigation/defense mechanism against the cyber altercations.

Density, Young’s modulus and maximum strength steadily decreased with an increase in the number of missing layers, whereas a no clear trend was observed in the case of % elongation. Post tensile test observations of the sample cross-sections confirmed the successful removal of the layers from the samples by the designed method. As a result, the current work presented a cyber-attack model and its quantitative implications on the mechanical properties of 3D printed objects.

To the best of the authors’ knowledge, this is the original work from the team. It is currently not under consideration for publication in any other avenue. The paper provides quantitative approach of realizing impact of cyber intrusions on deteriorated performance of additively manufactured products. It also enlists important intrusion mechanisms relevant to additive manufacturing.

This systematic literature review analyzes the academic literature to understand SC risk and resilience across different organizational sizes and industries. The academic literature has well discussed the causes of supply chain (SC) risk events, the impact of SC disruptions, and associated plans for SC resilience. However, the literature remains fragmented on the role of two fundamental elements in achieving SC resilience: the firm's size and the firm's industry as firms' contingent factors. Therefore, it is important to investigate and highlight SC resilience differences by size and industry type to establish more resilient firms.

Building upon the contingent resource-based view of the firm, the authors posit that organizational factors such as size and industry sector have important roles in developing organizational resilience capabilities. This systematic literature review and analysis is based on the structural and systematic analysis of high-ranked peer-reviewed journal papers from January 2000 to June 2021 collected through three global scientific databases (i.e. ProQuest, ScienceDirect, and Google Scholar) using relevant keywords.

This systematic literature review of 230 high-quality articles shows that SC risk events can be categorized into demand, supply, organizational, operational, environmental, and network/control risk events. This study suggests that the SC resilience plans developed by startups, small and mdium-sized enterprises (SMEs), and large organizations are not necessarily the same as those of large enterprises. While collaboration and networking and risk management are the most crucial resilience capabilities for all firms, applying lean and quality management principles and utilizing information technology are more crucial for SMEs. For large firms, knowledge management and contingency planning are more important.

This study provides a comprehensive review of the literature on SC resilience plans across different organizational sizes and industries, offering new insights into the nature and dynamics of startups', SMEs', and large enterprises' SC resilience in different industries. The study highlights the need for further investigation of SC risk and resilience for startups, SMEs, and different industries on a more detailed level using empirical data. This study’s findings have important implications for researchers and practitioners and guide the development of effective SC resilience strategies for different types of firms.

With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry has been discussed in this review. Scientists have linked the underlying structural or chemical science of textile materials and discovered several strategies for completing some of the most time-consuming tasks with ease and precision. Since the 1980s, computer algorithms and machine learning have been used to aid the majority of the textile testing process. With the rise in demand for automation, deep learning, and neural networks, these two now handle the majority of testing and quality control operations in the form of image processing.

The state-of-the-art of artificial intelligence (AI) applications in the textile sector is reviewed in this paper. Based on several research problems and AI-based methods, the current literature is evaluated. The research issues are categorized into three categories based on the operation processes of the textile industry, including yarn manufacturing, fabric manufacture and coloration.

AI-assisted automation has improved not only machine efficiency but also overall industry operations. AI's fundamental concepts have been examined for real-world challenges. Several scientists conducted the majority of the case studies, and they confirmed that image analysis, backpropagation and neural networking may be specifically used as testing techniques in textile material testing. AI can be used to automate processes in various circumstances.

This research conducts a thorough analysis of artificial neural network applications in the textile sector.

This research aims to specialise in the investigation of risk management for service-oriented manufacturing supply chains via two stages, highlighting its differences from manufacturing. The research article is commenced by executing an encyclopedic review of earlier research to ascertain the distinctive traits of service-oriented manufacturing supply chains and identify prevalent risks. Secondly, an empirical study in the construction field, amongst the industry hardest struck in the mist of the COVID-19 epidemic, is conducted to thoroughly inspect the resonant effect of these risks on service-oriented manufacturing supply chain performance.

In this study, to validate the resonant effect mechanism, a thorough assessment is undertaken by juxtaposing theoretical model to a newly constructed comparative model that encompasses the single effects of risks on supply chain performance.

63% variance of service-oriented manufacturing supply chain performance was showcased by the resonant effect model, compared with 46.3% in the comparative model. Moreover, each risk exerts a more glaringly significant impact on supply chain performance, asserting the mechanism of the resonant influence. Another noteworthy result involves the demand risk possessing a low effect on supply chain performance, thus emphasising the superiority of service-oriented manufacturing supply chains.

Future research endeavours should hinge on the optimal “resonant” model explosion, thereby foreseeing and alleviating worst-case scenarios to guarantee the robustness and resilience of supply chain networks.

Indubitably, reducing the intensity of the resonant effect revolves around lowering the coefficient of “a,” thereby restricting/eliminating the link among risks. Therefore, the suggested resonant impact model might thus serve as “a road map”. In light of the aforementioned considerations, it is advisable that supply chain executives employ supply chain management tactics namely avoidance, prediction, and postponement, but only after meticulous consideration the costs and benefits of adopting such strategies.

The service-oriented manufacturing supply chain features and advantages have been analysed and explained throughout the article. The data gathered during the COVID-19 pandemic is a captivating and topical point of this paper.

This paper examines the nexus between supply chain social capital (relational social capital and structural social capital), supply chain responsiveness (operations system responsiveness and supplier network responsiveness) and firm performance. Additionally, the study examines the mediating role of supply chain responsiveness on the relationship between supply chain social capital and firm performance.

The authors test their hypotheses on a sample of 120 firms operating in Ghana. The measurement model and hypothesized paths were assessed using partial least squares structural equation modelling.

The findings revealed that structural social capital had a significant direct effect on firm performance, but relational social capital did not. It was also revealed that both relational and structural social capital have significant effects on operations system responsiveness and supplier network responsiveness. Additionally, operations system responsiveness fully mediated the effect of relational social capital on firm performance and partially mediated the effect of structural social capital on firm performance. Supplier network responsiveness, on the other hand, partially mediated the effect of both relational and structural social capital on firm performance.

This study contributes to the limited literature on supply chain social capital by unearthing the mechanisms through which supply chain social capital enhances firm performance. Specifically, the study demonstrates the intervening role of operations system responsiveness and supplier network responsiveness in the supply chain social capital–firm performance link.

With the emergence of the different Industry 4.0 technologies and the interconnectedness between the physical and cyber components within manufacturing systems, the manufacturing environment is becoming more susceptible to unexpected disruptions, and manufacturing systems need to be even more resilient than before. Hence, the purpose of this work is to explore how does incorporating Industry 4.0 into current manufacturing systems affects (positively or negatively) its resiliency.

A Systematic Literature Review (SLR) was performed with a focus on studying the manufacturing system’s resilience when applying Industry 4.0 technologies. The SLR is composed of four phases, which are (1) questions formulation, (2) determining an adequate search strategy, (3) publications filtering and (4) analysis and interpretation.

From the SLR results’ analysis, four potential research opportunities are proposed related to conducting additional research within the research themes in this field, considering less studied Industry 4.0 technologies or more than one technology, investigating the impact of some technologies on manufacturing system’s resilience, exploring more avenues to incorporate resiliency to preserve the state of the system, and suggesting metrics to quantify the resilience of manufacturing systems.

Although there are a number of publications discussing the resiliency of manufacturing systems, none fully investigated this topic when different Industry 4.0 technologies have been considered. In addition to determining the current research state-of-art in this relatively new research area and identifying potential future research opportunities, the main value of this work is in providing insights about this research area across three different perspectives/streams: (1) Industry 4.0 technologies, (2) resiliency and (3) manufacturing systems and their intersections.