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This study addresses the production optimization of a cellular manufacturing system (CMS) in magnetic production enterprises. Magnetic products and raw materials are more critical to transport than general products because the attraction or repulsion between magnetic poles can easily cause traffic jams. This study needs to address a method to promote the scheduling efficiency of the problem.

To address this problem, this study formulated a mixed-integer linear programming (MILP) model to describe the problem and proposed an auction and negotiation-based approach with a local search to solve it. Auction- and negotiation-based approaches can obtain feasible and high-quality solutions. A local search operator was proposed to optimize the feasible solutions using an improved conjunctive graph model.

Verification tests were performed on a series of numerical examples. The results demonstrated that the proposed auction and negotiation-based approach with a local search operator is better than existing solution methods for the problem identified. Statistical analysis of the experiment results using the Statistical Package for the Social Sciences (SPSS) software demonstrated that the proposed approach is efficient, stable and suitable for solving large-scale numerical instances.

An improved auction and negotiation-based approach was proposed; The conjunctive graph model was also improved to describe the problem of CMS with traffic jam constraint and build the local search operator; The authors’ proposed approach can get better solution than the existing algorithms by testing benchmark instances and real-world instances from enterprises.

The advent of Industry 4.0 (I4.0) and the requirements imposed on companies still need to be clarified. Companies still strive to understand I4.0 requirements and technological, organizational, operational and management challenges. Current literature on I4.0 underlies the importance of a roadmap with structured steps to achieve the benefits of I4.0, mainly focused on augmenting operational performance. Therefore, this paper proposes a roadmap to implement I4.0 focused on operational management concepts, mainly aiming to augment operational performance and bridge the gap between theory and practice regarding roadmaps focused on the operational management dimension.

This paper follows a research approach divided into the following stages: a literature review to analyze the I4.0 roadmaps and identify the main components of I4.0; development of the proposed I4.0 roadmap presented; field research to test the roadmap by collecting data from a manufacturing company in the automotive industry; validation of the roadmap through modeling and simulation.

The authors presented a production line design with real-time control, fast response, shop floor coordination and predictive capacity. The results prove that the proposed I4.0 roadmap augments operation performance in the investigated automotive company. The main results were work in process reduction, lead time reduction, output increase, real-time control, shop floor coordination and fast response.

The main novelty of the proposed roadmap is to move toward I4.0 implementation with a focus on the operational management dimension. The roadmap has an innovative combination of the two approaches – lean manufacturing and factory physics – a straightforward roadmap with only three steps: (1) requirements, (2) real-time control and (3) predictive capacity, a structured definition of the approaches and operational management concepts fundamental in each step.

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.

Following the imperative for human-centric digital innovation brought by the paradigm of Industry 5.0, the article aims to integrate the dispersed and multi-disciplinary literature on individual risks for workers to define, explain and predict individual risks related to Industry 4.0 technologies.

The paper follows the question, “What is the current knowledge and evidence base concerning risks related to Industry 4.0 technologies, and how can this inform digital innovation management in the manufacturing sector through the lens of the Industry 5.0 paradigm?” and uses the method of systematic literature review to identify and discuss potential risks for individuals associated with digital innovation. N = 51 contributions met the inclusion criteria.

The literature review indicates dominant trends and significant gaps in understanding risks from a human-centric perspective. The paper identifies individual risks, their interplay with different technologies and their antecedents at the social, organizational and individual levels. Despite this, the paper shows how the literature concentrates in studying risks on only a limited number of categories and/or concepts. Moreover, there is a lack of consensus in the theoretical and conceptual frameworks. The paper concludes by illustrating an initial understanding of digital innovation via a human-centered perspective on psychological risks.

Findings yield practical implications. In investing in the adoption, generation or recombination of new digital technologies in organizations, the paper recommends managers ensure to prevent risks at the individual level. Accordingly, the study’s findings can be used as a common starting point for extending the repertoire of managerial practices and interventions and realizing human-centric innovation.

Following the paradigm of Industry 5.0, the paper offers a holistic view of risks that incorporates the central role of the worker as crucial to the success of digital innovation. This human-centric perspective serves to inform the managerial field about important factors in risk management that can result in more effective targeted interventions in risk mitigation approaches. Lastly, it can serve to reinterpret digital innovation management and propose future avenues of research on risk.

Despite its potential, warehouse managers still struggle to successfully assimilate autonomous mobile robots (AMRs) in their operations. This paper means to identify the moderating factors of AMR assimilation for production warehouses that influence the digital transformation of their intralogistics via AMRs.

Drawing on innovation of assimilation theory (IAT), this study followed an explorative approach using the principles of the case study method in business research. The cases comprised of four AMR end users and six AMR service providers. Data were collected through semi-structured interviews.

Four clusters of moderators that affect each stage of AMR assimilation were identified. These clusters include organizational attributes of end users (i.e. production warehouses), service attributes of service providers, technology attributes of AMRs and relational attributes between the AMR service providers and the AMR end users.

The authors extend the IAT framework by identifying various moderating factors between different stages of the AMR assimilation process. To the authors' knowledge, this is the first study to introduce the perspective of AMR end users in conjunction with AMR service providers to the “Industry 4.0” technology assimilation literature. The study propositions regarding these factors guide future intralogistics and AMR research.

This paper proposes strategies for adopting Industry 4.0 in achieving sustainable manufacturing, by overcoming barriers in the Sri Lankan manufacturing sector.

A conceptual model of sustainable manufacturing and Industry 4.0 was proposed based on a comprehensive literature review and validated through experts' inputs. The model was illustrated using three case studies to assess the relationships between sustainable manufacturing and Industry 4.0 in the Sri Lankan manufacturing context. Furthermore, possible strategies were proposed to overcome current barriers identified from case studies.

The case studies showcase that there is a considerable gap in Industry 4.0-enabled sustainable manufacturing in the Sri Lankan manufacturing sector due to several barriers. Thus, experts' knowledge-based strategies to overcome those barriers are proposed.

The conceptual model provides a holistic view of maturity levels of sustainable manufacturing measures directly connected with Industry 4.0 technologies. The study was limited to investigating the application of Industry 4.0 for sustainable manufacturing in leading apparel manufacturing organisations in Sri Lanka.

The conceptual model can be used as a framework to guide practitioners in implementing Industry 4.0-enabled sustainable manufacturing. The proposed strategies in addressing barriers to Industry 4.0 adoption towards sustainable manufacturing can be directly applied to achieving better sustainable manufacturing performance.

This study is an informative guide to encourage the Sri Lankan manufacturing industry to adopt Industry 4.0 technologies in achieving sustainable manufacturing, using the knowledge of relationships between Industry 4.0 and three dimensions of sustainable manufacturing, possible barriers and strategies.

The purpose of this paper is to illustrate the growing role of robots in the logistics industry.

Following an introduction, which identifies key challenges facing the industry, this paper discusses robotic applications in warehouses, followed by sections covering transportation and delivery and conclusions.

The logistics industry faces a number of challenges that drive technological and operational changes. Robots are already playing a role within the warehouse sector and more complex applications have recently arisen from developments in artificial intelligence-enabled vision technology. In the transportation sector, autonomous trucks are being developed and trialled by leading manufacturers. Many major logistics companies are involved and limited services are underway. Last-mile delivery applications are growing rapidly, and trials, pilot schemes and commercial services are underway in Europe, the USA and the Far East. The Chinese market is particularly buoyant, and in 2019, a delivery robot was launched that operates on public roads, based on Level-4 autonomous driving technology. The drone delivery sector has been slower to develop, in part due to regulatory constraints, but services are now being operated by drone manufacturers, retailers and logistics providers.

This paper provides details of existing and future applications of robots in the logistics industry.

Lean Six Sigma 4.0 has brought about a paradigm shift in customization, automation, value creation and digitalization to achieve excellence in human factors, operations and sustainable development. Despite its potential, LSS 4.0 is still in its nascent stage, with researchers striving to identify the key and relevant components of LSS in relation to Industry 4.0. The present study aims to address this knowledge gap through a literature review and subsequently provide a conceptual framework for LSS within the context of digital transformation.

In this study, the authors have conducted a thorough review of reputable articles published between 2011 and 2022, focusing on the integration of Lean Six Sigma (LSS) and Industry 4.0 (I4.0). By using appropriate keywords, the authors identified around 85 relevant articles. The main objective of this integrative literature review was to analyze and extract valuable knowledge from the existing literature on LSS and I4.0. Based on the authors’ findings, a conceptual framework was developed.

The review revealed the motivators, building blocks, tools and challenges of LSS 4.0. The conceptual framework delves into the key aspects of LSS 4.0, focusing on the dimensions of people, process and technology, as well as their subdimensions. These subdimensions serve as the building blocks for developing LSS 4.0 capabilities. The proposed framework visually represents the conceptualization and the relationships among its components.

Only a few conceptual approaches to LSS are developed that include the concepts, new roles and elements of I4.0. As a result, this research investigates the gap in current LSS models preceding I4.0 and develops a conceptual framework to provide a novel and comprehensive summary of the new concepts and components driving nascent and current LSS practices in the digital era.

This study offers practical guidance for implementing LSS in the context of I4.0, emphasizing digital transformation. The findings highlight motivators, building blocks, tools, challenges and spread of LSS 4.0 practices, and present a conceptual framework of LSS 4.0. These insights can help organizations enhance their LSS capabilities and achieve excellence in human factors, operations and sustainable development.

This study aims to make a significant contribution to the model-building efforts of researchers focusing on LSS 4.0. By offering practical guidance, the points discussed in this study help enhance the implementation efforts of practitioners and organizations in the context of I4.0, with a specific focus on digital transformation. The guidance provided takes into account the perspectives of people, processes and technology, providing valuable insights for successful integration.

Maintenance represents an indispensable role in the productive sector of the steel industry. The increasing use of operating with a high level of precision makes hydraulic systems one of the issues that require a high level of attention. This study aims to explore an empirical investigation for decreasing the occurrences of corrective maintenance of hydraulic systems in the context of Lean 4.0.

The maintenance model is developed based on action-research methodology through an empirical investigation, with nine stages. This approach aims to build a scenario to analyze and interpret the occurrences, seeking to implement and evaluate the actions to be performed. The undertaken initiatives demonstrate that this approach can be applied to optimize the maintenance of an organization.

The main contribution of this paper is to demonstrate that the applied method allows the overviewing results, with a qualitative approach concerning the maintenance actions and management processes to be considered, allowing a holistic understanding and contributing to the current literature. The results also indicated that Lean 4.0 has direct and mediating effects on maintenance performance.

This research intends to propose an evaluation framework with an interdimensional linkage between action research methodology and Lean 4.0, to explore an empirical investigation and contributing to understanding the actions to reduce the occurrences of hydraulic systems corrective maintenance in a production line in the steel industry.

The introduction of robots as value-adding “workers” on the shop floor triggers complex changes to manufacturing work. Such changes involve highly entangled relationships between technology, organisation and people. Understanding such entanglements requires a holistic assessment of contemporary robotised manufacturing work, to anticipate the dynamically emerging opportunities and risks of robotised work.

A systematic literature review of 87 papers was conducted to capture relevant themes of change in robotised manufacturing work. The literature was analysed using a thematic analysis approach, with Checkland’s soft systems thinking as an analytical framework.

Based on the literature analysis, the authors present a systemic conceptualisation of robotised manufacturing work. Specifically, the conceptualisation highlights four entangled themes of change: work, organisation of labour, workers’ (experiences) and the firm’s environment. Moreover, the authors discuss the complex patterns of interactions between these objects as relationships that defy straightforward cause–effect models.

The findings draw attention to complex interactions between robotisation and manufacturing work. It can, therefore, inform strategic decisions and support projects for robotisation from a holistic perspective.

The authors present a novel approach to studying and designing robotised manufacturing work as a conceptual system. In particular, the paper shifts the focus towards crucial properties of the system, which are subject to complex changes alongside the introduction of robot technology in manufacturing. Soft systems thinking enables new research avenues to explain complex phenomena at the intersection of robotisation and manufacturing work.