Citation

Nowobilski T, Hoła B. Safety Sci. 2023; 157: e105945.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.ssci.2022.105945

PMID

unavailable

Abstract

Every year, there are several thousand occupational accidents on Polish construction sites. Many of them are related to the use of building scaffolding. Depending on the type of injury, accidents are classified as light, severe or fatal. This article presents a methodology, which is based on identified causes, for predicting the effects (severity) of falls from building scaffolding. The basis for the research was a set of 200 accidents that occurred on Polish construction sites in 2011. Information on the accidents was obtained from the archives of the National Labor Inspectorate. For each fall from scaffolding, the following were identified (in accordance with the Polish TOH methodology): technical (T), organizational (O) and human (H) causes of the accident, as well as its effects. The significance of the causes was assessed in each group using Pareto-Lorenz analysis and the ABC classification. Significant causes include those that were identified in over 80% of accidents. These causes were taken into account in the further analyzes. In order to define the relationship between the identified significant causes of an accident, and its effect, an original methodology of screening was proposed. It involved the assigning of the possible effects of accidents to each theoretical combination of accident causes. For this purpose, computational scripts in the Python programming language were developed. The test results allowed for the percentage determination of the probability of light, severe and fatal consequences of an accident for each of the combinations of significant causes. The conducted research is of great importance for science and engineering practice. The obtained test results can be used to estimate the occupational risk of work carried out on building scaffoldings. The developed computational models enable the consequences of accidents to be easily and quickly forecast, depending on the deficiencies and shortcomings identified "in situ" in the area of scaffolding assembly, work organization and human factors. Good identification of the factors influencing the severity of accidents allows high-risk factors to be distinguished and specific preventive measures to be developed.

Language: en

Keywords

Causes and effects of falls; Construction industry; Occupational risk; Occupational safety; Python; Scaffolding