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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.

Lean management tools are becoming increasingly applied in different types of organizations around the world. These tools have shown their significant contribution to improving business performance. In this vein, the purpose of this paper is to examine the influence of lean management on both occupational safety and operational excellence in Tunisian companies.

A survey was conducted among Tunisian companies, and it resulted in the collection of 62 responses that were analyzed using the software SPSS. In addition, a conceptual model linking the practices of the three basic concepts was designed to highlight the hypotheses of the research. Subsequently, factor analysis and structural equation method analysis were conducted to assess the validation of the assumptions.

The results obtained have shown that lean management has a significant impact on occupational safety. Similarly, occupational safety has a significant impact on operational excellence. However, lean management does not have a significant impact on operational excellence.

This work highlighted the involvement of small and medium-sized enterprise’s managers from emerging economies in the studied concepts’ practices. Likewise, it testified to the impacts of lean management on occupational safety and operational excellence in the Tunisian context.

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.

Inventory models are quantitative ways of calculating low-cost operating systems. These models can be either deterministic or stochastic. A deterministic model hypothesizes variable quantities like demand and lead time, as certain. However, various types of research have revealed that the value of demand and lead time is still ambiguous and vary unanimously. The main purpose of this research piece is to reduce the uncertainties in such a dynamic environment of Industry 4.0.

The current study tackles the multiperiod single-item inventory lot-size problem with varying demands. The three lot sizing policies – Lot for Lot, Silver–Meal heuristic and Wagner–Whitin algorithm – are reviewed and analyzed. The suggested machine learning (ML)–based technique implies the criteria, when and which of these inventory models (with varying demands and safety stock) are best fit (or suitable) for economical production.

When demand surpasses a predicted value, variance in demand comes into the picture. So the current work considers these things and formulates the proper lot size, which can fix this dynamic situation. To deduce sufficient lot size, all three considered stochastic models are explored exclusively, as per respective protocols, and have been analyzed collectively through suitable regression analysis. Further, the ML-based Classification And Regression Tree (CART) algorithm is used strategically to predict which model would be economical (or have the least inventory cost) with continuously varying demand and other inventory attributes.

The ML-based CART algorithm has rarely been seen to provide logical assistance to inventory practitioners in making wise-decision, while selecting inventory control models in dynamic batch-type production systems.

This study aims to identify the factors to food safety certification adoption among farmers in Malaysia.

This study was conducted qualitatively using a method of interviewing with unstructured questions. To identify the factors that influence and prevent the adoption of food safety certification among Malaysian farmers, nine (n = 9) agricultural industrial experts were randomly chosen.

Based on data analysis using thematic analysis, the respondent highlighted 14 factors to food safety certification. Specifically, the most frequent determinant highlighted by the respondent is enforcement (12). Additionally, it has been proven that the identified factors aligned with existing theories: technology, organization and environment (TOE) framework and eco-innovation theory. These theories help researchers to create effective strategies and produce significant findings from their research.

To the best of the authors’ knowledge, this study is the first to investigate food safety certification adoption among farmers in the Malaysian agriculture industry using the integration of the TOE framework and eco-innovation theory. The stakeholder is expected to receive the benefits of creating efficient campaigns to encourage more farmers to obtain food safety certification. This study provides further knowledge by improving the understanding of the processes involved in certification adoption, providing context-specific insights, best practices, policy guiding development and emphasizing the effects of certification on sustainability and competitiveness.

Saudi Arabia's 2030 vision targets an increase of 34% in non-oil revenue participation in the GDP, thus the need for automation and digital transformation. The Company ER is a market leader producing high-quality dairy products in the Kingdom and is a pioneer in the production industry. The company has recently increased the capacity of its milk factory to meet its vision. An investment was made to automate the pallet handling procedures at the milk factory to provide increased production for daily consumption. The new automation transition in Company ER's milk factory provides a unique opportunity to utilize lean management tools to improve the current automated processes before commercialization.

OEE (overall equipment effectiveness) will monitor losses for different operational losses in the new automated system and indicate system improvements, with 85% as the target. Based on DMADV (design, measure, analyze, design and validate) methodology, this study analyzes the entire automated pallet handling system. It uses lean tools to identify areas for improvement, identify waste elements and propose solutions to achieve Company ER's OEE targets.

In this paper, the outcomes will be presented as documented solutions that address the losses encountered in the production system, showing a 12.8% increase in the system's OEE.

Owing the time and resource constraint, this study only involved automated pallet handling procedures in a milk production facility. Hence, the generalization of the result is slightly limited. More studies in several different processes and sectors are required.

This study provided a valuable tool for researchers for gaining deeper understanding regarding the lean manufacturing and its implementation. For practitioners, it is useful to evaluate the degree of lean manufacturing tools in their material handling systems.

This study is the first attempt to develop lean manufacturing constructs for evaluating the automated pallet handling procedures in a milk production facility.

Building industrial clusters is getting much more political attention and strategic orientation in all developing countries. This study started by revising the conceptual and theoretical frameworks for industrial clusters, followed by some insights and contributions about empirical bases for clusters' dynamics and processes. The study focused on the case of Agadir Agreement between four Arab countries (Egypt, Jordon, Morocco, and Tunisia), which was initiated after the Euro-Mediterranean partnerships, and the rationale of the agreement was based on the concept of cumulative value-added origin. The study based its methodology on analyzing the international and bilateral trade flows of six industrial goods from the automotive sector among the four countries and with the EU countries to detect the degree of industrial collaboration and the achieved success of each country in this sector. The study indicated that the four countries used the concept of industrial clusters for economic development, but the results of the analysis showed that till now Agadir Agreement only achieved a shallow integration, while failed to deeply integrate as one big collaborative industrial cluster.

Despite the contributions of both the oil and gas and construction industries to the gross domestic product (GDP) of the country, both industries are still marred by incessant accidents. Therefore, the aim of this study is to compare the health and safety practises of the construction and oil and gas industries in Nigeria in order to suggest the best approach to health and safety practices.

A survey questionnaire was developed and administered to professionals working in the construction and oil and gas industries. Data were analysed using the relative importance index (RII). An independent sample t-test was also conducted to determine whether there was a significant difference in the construction and oil and gas industries.

The study revealed that the rate at which health and safety are practised in the oil and gas industry is comparatively high compared to how they are practised in the construction industry. Proper site layout and planning, provision of a safe working environment, proper health and safety risk assessment were more predominantly practised in the oil and gas industry, while proper site layout and planning, disallowing unauthorised entry into site and the provision of a safe working environment were predominantly practised in the construction industry.

This study is the first to compare the health and safety practises of the construction and oil and gas industries in Nigeria. This study was significant because it would provide insight into construction and oil and gas managers, as well as other decision-makers in both industries, on how to improve health and safety practices.

Although there are several established frameworks for health and safety in construction, there are inadequate health and safety conditions at informal construction sites, and no framework has been designed to address this problem. The purpose of this paper is to develop a validated framework for health and safety risk management (HSRM) in informal construction sites with the aim of supporting Sustainable Development Goals 3, 8 and 11 of the 2030 Agenda, which are to ensure everyone enjoys a healthy life and to create inclusive, secure, robust and sustainable cities and human settlements, respectively.

The study is based on HSRM questionnaire survey and interviews with construction workers working on informal construction sites in Tanzania. A total of 13 health and safety specialists in construction were specifically chosen to validate the proposed framework for HSRM in informal construction to determine its applicability, efficacy and adaptation.

The validation results demonstrated that all of the suggested metrics within the framework for HSRM in informal construction scored higher than the test value, proving the framework’s feasibility

This research adds to the body of knowledge on the issue in a never-before-seen setting. To the best of the authors’ knowledge, this study is the first empirical study in Tanzania to develop and validate a framework for HSRM in informal construction.

The aim of this paper is to review and analyze the research literature on the health and safety issues of migrant workers in the construction industry from 2000 to 2022.

5 steps method is used to conduct a systematic review to achieve the objectives. After scanning two authoritative search engines “Web of Science” and “Scope”, 60 articles are selected from 225 publications for identification and review. These identified articles are classified by research fields, countries and time span.

The review finds that with the increasing influence of migrant construction workers, the number of publications on the health and safety of migrant workers has shown a rapid upward trend. Moreover, language barriers are the most dominant safety risk factors encountered by on-site migrant workers. This systematic literature review also summarizes the definition of migrant workers and solutions to reduce safety risk factors.

The research data on the health and safety issues and risk factors of migrant workers in the construction industry is still limited. This literature review summarizes the research trends and contributions of the literature in this field in the past 22 years and provides theoretical support for future research on the safety management of the migration construction field.