The metal sector encompasses a variety of economic activities, such as metallurgy and the manufacturing of metallic elements. These activities represent great diversity in production processes. Worker-related characteristics are particularly important in these processes and the accident rate. In view of the metal sector's importance and that the latest annual report (2019) reveals the sector to be among the ten sectors with Spain's highest accident rates, the purpose of this study is to explore the evolution of work accidents in the metal-mechanical sector in Spain for the period of 2009–2019 and to analyse the relationship between the associated variables. Data for this study come from occupational accident reports, which are required to be sent to the relevant administrative bodies using the Spanish Delt@ (electronic declaration of injured workers) computer system. The study variables were selected from the official occupational accident data and classified into four groups: personal, business, material, and time period. The relationships between severity and other variables were explored via contingency tables in which the chi-squared value (χ2) was calculated. This study shows a slight improvement in the accident rate over the last decade, but a high percentage of serious and fatal accidents in the Spanish industrial sector remains. The Monday effect, meal breaks, and being near retirement age are the most important factors influencing the number of serious accidents in this sector.@en

Emerging risk models are still scarce and far from agreed upon. They are currently the focus of increasing interest in the occupational context. Consequently, frameworks that deal with emerging risk management in industrial contexts are very recent or, even still, in the development and maturation stage. Uncertainty should be considered as the main characteristic of emerging risk in this context. It is as such that the main objective of this paper is to develop a qualitative approach inspired by meta-learning lessons to the selection of strategies for emerging risk management, considering uncertainty as the main decision variable in occupational contexts. To this end, uncertainty has been integrated, as a combination of knowledge and understanding, in a theoretical framework on emerging risk. An emerging risk classification scheme has been developed with the results obtained. This scheme makes it possible to estimate the level of emerging risk and management strategies based on the combination of uncertainty and the potential consequences of emerging risk. Such approach has been applied to three case studies with different evolutionary degrees of emerging risk: exoskeletons; nanomaterials; and industrial automation. The proposed approach could be considered primarily as a qualitative tool applicable to the process of pre-assessment and communication of emerging risk.

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