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This work presents a sustainability assessment approach to evaluate technological innovations in secondary steel production making use of Electric Arc Furnace (EAF) technology. The assessment covers the environmental, social, and economic dimensions of sustainability by combining different tools (Life Cycle Assessment and Analytic Hierarchy Process), and also provides an integrated assessment of the overall sustainability. The approach, which can also be used to support decision-making, has been applied to a real case study of a steel plant located in Northern Italy. In the case study, environmental sustainability is positively impacted mainly by increased metal yield and reduced furnace energy consumption. The greatest social sustainability benefits are mainly related to improved ergonomic and safety conditions for workers (reduced demand for physical effort, manual handling and repetitiveness, and lower risk of accidents), as a consequence of the introduction of Industry 4.0 technologies. Regarding economic sustainability, a positive impact related to reduced cycle time, increased metal yield and quality yield, reduced maintenance and quality control costs was observed. The integrated assessment of the overall sustainability has proven to be a viable approach to manage trade-offs between the different dimensions of sustainability.

This paper investigates the usage of a systemic neutralized taxonomy for understanding human factors to foster a restorative culture when studying adverse events. The available studies supporting accident analysis from a system‐theoretic perspective with human factors‐based methods are grounded on error taxonomies and do not reinforce the non‐judgemental dimension that is encouraged by modern safety science. We propose a methodology to integrate the system‐theoretic accident analysis technique, Causal Analysis based on System Theory, with a neutralized taxonomy of human explanatory factors. The proposed methodology has been applied to an aviation accident involving a military aircraft and a glider. This case revealed various critical interactions among system components, which require dedicated safety recommendations that go beyond the identification of single points of failures and root causes, leading to a deeper understanding of socio‐technical orchestrations. Despite the use case in aviation, the proposed methodology remains suitable for various types of safety occurrences in diverse domains and industrial settings. It also represents the basis for supporting future proactive safety‐related decision‐making processes. [ABSTRACT FROM AUTHOR]

Objective. In the steel industry, performing activities in confined spaces where potential oxygen displacement can occur may expose workers to fatal consequences. To the best of our knowledge, no quantitative exposure assessment of oxygen deficiency in steel industry confined spaces is available in the literature. To overcome this gap, we performed oxygen deficiency hazard (ODH) assessments in real confined spaces using two existing models to identify the most critical parameters responsible for ODH, and suggest controls for mitigating the asphyxiation risk. Methods. We applied a well-mixed model and a near field–far field approach to estimate the indoor oxygen level with time during and following release of simple asphyxiants. Model inputs were mainly gathered thanks to audits and instrumental tests in three firms. Results. The most severe ODH exposures are posed in spaces with restricted volume and where accidental releases of inert gases can occur. Such exposures can be controlled through early release detections and augmented reality systems. Conclusions. ODH assessments in confined spaces of steel firms allow the identification of the most critical parameters from an oxygen depletion perspective, focusing on which data need careful measurement, and help to establish controls compatible with the operations conducted in these areas. [ABSTRACT FROM AUTHOR]

The experience gathered from normal industrial operations allows us to associate its degrading conditions with the potential for an accident. Such association is the basis for the definition of the system risk and appropriate safety measures. If a skilled operator observes further degrading conditions, his/her mind quickly learns from this new experience, derives an updated risk level, and tunes the safety measures. Similarly, safety management techniques aim to construct a risk model while learning from past and new observations with the purpose to warn of an imminent accident. However, the model can be tested only in hindsight, after the occurrence (or the missed occurrence) of an accident. How can we generalise and model the risk analysis learning process? How can we optimise its configuration towards new observations? This study discusses these issues of meta-learning for safety management by considering the case study of a drive-off scenario involving an oil and gas drilling rig, for which a risk assessment approach based on machine learning is developed. The results indicate the way forward for a generalisation of risk analysis learning processes and their optimisation. [ABSTRACT FROM AUTHOR]

Occupational safety is traditionally managed distinctly from process safety. The former puts the emphasis on high frequency and low consequence incidents, and refers to hazards that could provoke human consequences. In contrast, the latter focuses on releases of chemicals, energy, or hazardous materials, leading to low likelihood but high consequence accidents with severe negative effects to people, environment, assets, and/or business. However, neither personal safety nor process safety should be compromised, and their common priority should remain the elimination and mitigation of adverse consequences for workers. The aim of this paper is to provide an overview of existing approaches for harmonising the assessments of personal and process safety risks, pointing out the main challenges to be addressed for developing a future enhanced framework. To achieve this aim, a systematic literature review in databases of scientific publications was carried out. The review returned 14 studies, most of which propose a new method or tool (e.g., risk index). The critical analysis of these results indicated the strengths and weaknesses of each approach that represent helpful starting points for an enhanced framework. Such a framework should systematically identify hazards, hazardous events, and exposure conditions that cause harm to employees, and should establish a ranking of the risks according to their criticality for prioritising risk management efforts. [ABSTRACT FROM AUTHOR]