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Jarsh Safety received an order of 500 units of its Model S helmet. However, the order must be delivered within 15 days. Jarsh Safety was founded by three engineering college peers, who conceptualized air-conditioned, industrial safety helmets. This innovative revolutionary product offered industrial workers not only safety but aesthetics and comfort. The founders hoped that the product could change the perception of safety helmets from mandatory wear to desired wear. The case details the production process, staffing, raw material required and procurement lead time.

Collaborative robotics and autonomous driving are fairly new disciplines, still with a long way to go to achieve goals, set by the research community, manufacturers and users. For technologies like collaborative robotics and autonomous driving, which focus on closing the gap between humans and machines, the physical, psychological and emotional needs of human individuals becoming increasingly important in order to ensure effective and safe human–machine interaction. The authors' goal was to conceptualize ways to combine experience from both fields and transfer artificial intelligence knowledge from one to another. By identifying transferable meta-knowledge, the authors will increase quality of artificial intelligence applications and raise safety and contextual awareness for users and environment in both fields.

First, the authors presented autonomous driving and collaborative robotics and autonomous driving and collaborative robotics' connection to artificial intelligence. The authors continued with advantages and challenges of both fields and identified potential topics for transferrable practices. Topics were divided into three time slots according to expected research timeline.

The identified research opportunities seem manageable in the presented timeline. The authors' expectation was that autonomous driving and collaborative robotics will start moving closer in the following years and even merging in some areas like driverless and humanless transport and logistics.

The authors' findings confirm the latest trends in autonomous driving and collaborative robotics and expand them into new research and collaboration opportunities for the next few years. The authors' research proposal focuses on those that should have the most positive impact to safety, complement, optimize and evolve human capabilities and increase productivity in line with social expectations. Transferring meta-knowledge between fields will increase progress and, in some cases, cut some shortcuts in achieving the aforementioned goals.

This paper aims to investigate the Occupational Safety and Health (OSH) management practices of construction companies in South Korea to ascertain specific components and practices that need improvement for successful OSH performance.

A quantitative research strategy was adopted. A close-ended questionnaire survey covering 45 OSH management practices was sent to 324 contractors; 108 responses were gathered, representing a response rate of 33.3%. Data were analysed using simple descriptive statistics (frequencies and percentages) and Pearson’s chi-square test.

The findings revealed that there is a moderate level of implementation of OSH management practices among construction firms in South Korea. However, there is a significant disparity in terms of implementation between large enterprises on the one hand and small to medium enterprises on the other. Furthermore, a few of the business characteristics (i.e. the size of companies and certification to OHSAS 18001) were closely associated with the extent of the implementation of OSH management practices.

This research uncovers the OSH management practices that are poorly implemented and lays the foundation for appropriate measures to improve OSH in South Korean construction companies. It suggests an effective strategy for communicating health and safety issues to workers, training safety managers, reviewing risk assessments, reviewing the health and safety plan, incentivising workers by rewarding good behaviour and having a penal mechanism for employees not adhering to the rules.

The study provides insights into an under-investigated South Korean construction industry topic. It offers additional insight into state-of-the-art health and safety management practices in the construction industry in South Korea. Furthermore, it establishes which components of OSH management practice require improvement in the Korean context. This is also one of the few studies in OSH which establishes the association between the construction business characteristics and OSH management in the South Korean construction domain.

Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.

The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.

The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.

The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.

Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China.

In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode.

The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency.

To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.

The purpose of this research is to establish a conceptual model to understand the impact of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) on the transition of a Circular Economy (CE). Also, the paper explores the combined impact of TPM, I4.0 and CE on the sustainability performance (SP) of manufacturing firms.

The conceptual model is proposed using the dynamic capability view (DCV) and empirically validated by partial least squares-structural equation modelling (PLS-SEM) using 304 responses from Indian manufacturing firms.

The results suggest that I4.0 positively impacts TPM, CE and SP, also showing TPM's positive impact on CE and SP. In addition, CE has a positive influence on the SP of manufacturing firms. Furthermore, CE partially mediates the relationship between I4.0 and SP with TPM and SP. The study also identifies TPM, I4.0 and CE as a new bundle of dynamic capabilities to deliver SP in manufacturing firms.

The present research adds to the knowledge and literature on DCV by identifying the importance of CE in the settings of I4.0 and TPM, especially in the context of sustainability. Also, the current study offers a new set of dynamic capabilities and provides some significant future recommendations for researchers and practitioners.

The emerging industrial revolution referred to as Industry 5.0 is focusing on leveraging human creativity with intelligent and autonomous systems to derive user-friendly work environment for the businesses. Industry 5.0 stresses on people centric work ecosystem, zero accident policy and the well-being of labour within the production processes. This approach of Industry 5.0 to obtain human-centric safety solutions through the deployment of digital technologies deduces workplace accidents and costs leading to the development of Safety 4.0. This chapter aims to investigate the opportunities and challenges of Safety 4.0 and its enabling technologies aspiring towards the greater impact on safety management. Further, we have proposed a framework for the role of human centric digital transformations concerning safety in the manufacturing industry propelling Safety 4.0. Concluding, we discuss the implications for managers and practitioners. We found that Safety 4.0 will strengthen industrial safety, and instead of reacting to accidents, the concept evolved towards a preventive and proactive approach for a healthy industrial ecosystem.

This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.

The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.

Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.

An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

This study aims to examine the long-term impact of leader–member exchange (LMX) on employee safety behavior. It proposes a conceptual model that includes the mediating role of job satisfaction (JS) in the relationship between LMX and safety behaviors, regarding safety compliance behavior (SCB) and safety participation behavior (SPB).

Data were collected from 325 health-care workers across public hospitals in Algeria at three waves. Data were analyzed with partial least square structural equation modeling.

The findings revealed that LMX positively influenced employees’ job satisfaction. However, the relationship between LMX and SCB was found to be mediated by job satisfaction. LMX was not directly related to both dimensions of safety behavior, whereas JS was positively associated with safety compliance and safety participation.

This is the first paper, to the best of the authors’ knowledge, to report on the significant mediating role of JS on the reciprocal process used to exchange resources between leaders and subordinates and safety behaviors among health-care workers, thereby filling an important research gap in existing literature.

The purpose is to identify and explore barriers to overcome for developing collaborative innovation between a global service supplier and two of its industrial customers in Sweden.

The research had an action-based research approach in which the researchers were interacting and collaborating with the practitioners in the companies. The empirical part includes primary data from multiple interviews, and two workshops with dialogues with participants from the involved companies. The use of complementary data collection methods gave rich input to understanding the context for collaborative innovation, and to uncovering barriers, to develop solutions for collaborative innovation. The empirical barriers were analysed using theoretically derived barriers from a literature review. The analysis generated four broad themes of barriers which were discussed and led to conclusions and theoretical and practical implications on: the customer's safety culture, the business model, the parties' understanding of innovation and the management of collaborative innovation in supply chains.

The thematic analysis generated four broad themes: the customer's safety culture, the business model, the parties' understanding of innovation and the management of collaborative innovation. These themes where analysed using theoretically derived barriers from a literature review. The industrial context, the understanding of innovation and its management created barriers.

The unique access to the service supplier and its two independent industrial customers adds a rich contextual framing to the process of identifying and exploring the barriers to collaborative innovation. The conclusion emphasizes the importance of an industrial business context, the business logic in terms of business models and for the understanding and management of collaborative innovation.