Predictive Models of Accidents at Work in the Steel Sector as a Framework for Sustainable Safety - Tomasz Małysa; Bożena Gajdzik (Energies, 2020)
Work safety can be a component of the broadly understood sustainable enterprise approach that goes beyond the idea of sustainable development. Sustainability in an unpredictable and turbulent environment has many constellations, many aspects and many fields of the enterprise’s activity and it complements the rationality of the business. The aim is to understand the sustainability of safety, because this is the term we have adopted for rationality in occupational safety management, in the context of the analysis of work accidents in the Polish steel industry, with particular emphasis on the methodology of forecast assessment in the studied area, proposed by us. The realized forecasts were used for the creation of a combined model which formed the basis for formulating conclusions from the analysis. The publication presents the modeling of the victims of work accidents in the steel sector in Poland. Based on the research of the forecasts obtained, a downward trend is recorded in the number of persons injured in accidents at work in the steel sector. In order to select the optimal model, it was proposed to set combined forecasts. In order to select the optimal model, it was proposed to set combined forecasts. The obtained values of ex-ante forecasts in the combined model also confirmed the forecasted trends determined within the adaptation models. The study is a proposal to extend the combined forecasting methods used to assess occupational safety. We consciously chose to include the methodology of combined forecasting of the number of people injured in accidents in the interpretation of sustainability, because we see the possibility of interpreting accident rates in sustainable business in the future. In the publication, we propose the framework of the sustainable safety model as an element of work safety management in an enterprise. We are trying to answer the question about the place of accident prediction in sustainable safety.