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This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.

The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.

It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.

The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.

This paper aims to propose a stepwise method to improve the sustainability of manufacturing processes.

The proposed approach is based on an extensive literature review and research around the environmental, economic and social pillars of sustainability in manufacturing firms. Considering the lean approach, the manufacturing processes are mapped in a value stream and analyzed through the extensive identified sustainability criteria.

The findings reveal the consumption and waste of natural and nonrenewable resources, through going beyond the existing boundaries and focusing on relevant derived production pieces and tracing to their origins. The findings also present the effect of the time value of money on sustainability by using the cost–time profile as a sustainability criterion. This research finds out the employees’ impacts on sustainability improvement through an effective focus on technical, cultural and personal aspects.

The research outcomes provide operations managers and decision-makers in the field of sustainability with a practical platform to comprehend and assess the factors contributing to the manufacturing process sustainability and to plan relevant corrective actions accordingly.

The extended view of sustainability criteria in this research as well as its visual-analytical approach will help practitioners to assess and improve sustainability in their operations in a more holistic way.

Because of the COVID-19 pandemic and changing market demands, competition for manufacturing industries is increasing and they face numerous challenges. In such a case, it is necessary to use multiple strategies, technologies and practices to improve organizational performance and, as a result, to integrate them for ease of adoption. The purpose of this research is to identify advanced Industry 4.0 technologies, operational excellence (OPEX) strategies and reconfigurable manufacturing system (RMS) practices. The study also computes their weights, as well as identifies and prioritizes the performance metrics for the same.

A thorough review of relevant articles was conducted to identify 28 OPEX strategies, RMS practices and advanced technologies, as well as the 17-performance metrics. The stepwise weight assessment ratio analysis approach was used to compute the weights of the selected practices, while the WASPAS approach was used to prioritize the performance metrics. While developing the framework, the industry expert’s expertise was incorporated in the form of their opinions for pairwise comparison.

According to the study findings, advanced Industry 4.0 technologies were the most prominent for improving organizational performance. As a result, integrating Industry 4.0 technologies with OPEX strategies can assist in improving the performance of manufacturing organizations. The prioritized performance metrics resulted in the production lead time ranking first and the use of advanced technologies ranking second. This emphasizes the significance of meeting dynamic customer needs on time while also improving quality with the help of advanced technologies.

The developed framework can help practitioners integrate OPEX strategies and advanced technologies into their organizations by adopting them in order of importance. Furthermore, the ranked performance metrics can assist managers and practitioners in evaluating the manufacturing system and, as a result, strategic planning for improvement.

According to the authors, this is a novel approach for integrating OPEX strategies with advanced Industry 4.0 technologies, and no comparable study has been found in the current literature.

Industry 5.0 (I5.0) is eventually set to supersede Industry 4.0 (I4.0), despite the fact that I4.0 continues to gain ground in emerging nations like India. Now India is aspiring to be a global manufacturing hub, and I5.0 offers enormous potential to position India as a forerunner in intelligent and collaborative manufacturing systems. Therefore, this research article aims to understand the relationship between I5.0 and sustainable manufacturing (SM) thoroughly; pinpoint its impact and implementation challenges; analyze its impact on Triple-Bottom-Line (TBL) sustainability; and present an inclusive framework for I5.0 implementation for Indian manufacturing enterprises.

The coexistence of two industrial revolutions raises questions, which necessitates debates and explanations. Thus, the systematic literature review (SLR) approach is used to address this issue and this study used Web of Science, Scopus, Science Direct and Google Scholar databases. Following a critical SLR, 82 research papers have been cited in this article, and the majority of cited articles were published from 2010 to 2022, to ensure a focused analysis of pertinent and recent scholarly contributions.

I4.0 is considered to be technology-driven, however, I5.0 is perceived to be value-driven. I5.0 is not a replacement or a chronological continuation of the I4.0 paradigm. The notion of I5.0 offers a distinct perspective and emphasizes the necessity of research on SM within the TBL sustainability boundaries. I5.0 introduces a new TBL: resilience in value creation, human well-being and sustainable society. Indeed, I5.0 seems to be economically, socially, and environmentally sustainable while manufacturing products with high productivity.

Theoretical implications pertain to restructuring business models and workforce transformation, whereas practical implications underscore the significance for manufacturing enterprises to embrace I5.0 for their sustainable development. By understanding the nuanced relationship between I5.0 and SM, enterprises can navigate implementation challenges, maximize TBL sustainability and embrace an inclusive I5.0 framework for high productivity and resilience.

The existing literature presents the general notion of I5.0 but lacks in-depth TBL sustainability analysis. This research used a systematic and rigorous SLR approach that evaluates the existing literature, enables an in-depth understanding, identifies research gaps and provides evidence-based recommendations for the decision-making process. Furthermore, this research aims to stand on an unbiased assessment, exploring theoretical and practical implications of I5.0 implementation for manufacturing enterprises and suggesting future research avenues.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.

Sustainable production (SP) is an efficient and influential approach of production for Indian manufacturing industries as it preserves the social, environmental and economic aspects of production activities altogether. The objective of this research work is to investigate the implementation status of SP practices in Indian manufacturing industries by utilizing empirical survey methodology.

A questionnaire survey methodology was adapted, and the questionnaire was prepared by intense literature survey along with by opinions from experts in the field of SP. This questionnaire was sent to 753 different organizations at different locations across India. This study collected responses from manufacturing industries as per 2021 directory of Confederation of Indian Industries for the duration of 7 week. Top level managers were the target respondents. The study propagated with 242 responses which were observed complete in all respects.

The study identified that though the majority of the organizations are claiming to follow SP practices since long time, they actually are lagging in proper understanding SP practices. Majority of them are implementing it in specific departments in their organization. They are coming across multiple barriers in the implementation of SP practices among which unrecognized financial benefits and lack of proper government policies are prime. The study suggests that the Indian organizations needs feasible framework with adaptable guidelines.

This work is centered towards manufacturing organizations and targets only the leading industrial sectors in India. Thus, the outcomes of this study may not be generalized for all the sectors of Indian industries. Additionally, it can also be assumed that higher number of responses would have contributed to more clear visualization of implementation status of SP practices among Indian industries.

Sustainable approaches in production activities are very lucrative for industries worldwide, due to their advantages. Numerous researchers are also putting their efforts to explore more about various aspects of sustainability. Mostly they are focusing on single or few aspects of SP and its implementation in particular region or country. Very few research works are dedicated to knowing the implementation status of SP in Indian manufacturing industries and they are limited in various aspects. This study presents a dedicated approach to investigate the implementation status of SP practices in Indian manufacturing industries.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

Sustainability has become a priority for companies due to pressure from multiple stakeholders. In an overly competitive market, shareholders push for economic results, allowing lean manufacturing to establish itself as dominant paradigm in manufacturing. However, concerns grow regarding how lean implementation can allow companies to achieve sustainable development goals, or, if the resources required for a successful lean implementation can result in a detriment of environmental and social performance. This paper intends to help close the knowledge gap regarding the effects of lean manufacturing on sustainable performance from a triple bottom line perspective, and how operational, environmental and social outcomes interact between themselves.

Two models for the interaction between lean and sustainability were proposed. The first is called the “sand-cone” model, which poses that performance improvements derived from lean are cumulative on each one of the sustainability dimensions. The second is called the “trade-offs” approach. In this case, the resources required to improve one dimension of sustainability clash with those required by the others. Data were gathered from a sample of 133 Colombian metalworking companies and processed using structural equations models.

The results support the cumulative “sand-cone”, which follows a sequence of operational-environmental-social improvement in the presence of lean. For the “trade-offs” model, partial evidence suggests that they can occur in detriment of social performance.

The “sand-cone” and “trade-offs” are empirically tested for the first time in the context of sustainability, providing further knowledge into its interaction with lean manufacturing. The models’ results contribute to practitioners by providing a tested path for companies to improve their performance in a cumulative sequence that will provide better long-term results.

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.

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.