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The causes of occupational accidents from the perspective of human factors have been a subject which has received little attention into the field of scientific research. The aim of this research was to identify and classify the human factors that influence human errors and failures that cause accidents and injuries specifically on hands. Available studies related to the topic have been developed mainly for aerospace applications and are found insufficient to explain accidents causalities in the manufacturing industry. This research was developed in the assembly industry of automotive harnesses and was conducted following a mixed Cognitive Anthropological approach. This study was developed in two phases. During the first qualitative phase, participants freely listed their knowledge to identify elements of the cultural domain, then and in the second phase they performed the successive pile sort technique for the collection data to classify elements in the cultural domain. Statistical models like Cluster Analysis and Multidimensional Scaling were applied for results' validation purposes. As results, 70 different human factors were identified and in the second phase they were classified into 4 main categories which were: human error, unsafe conditions, individual factors, and organizational factors. Statistical methods validated these results.

Human factors identification and classification related to accidents’causality on hand injuries in the manufacturing industry