Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
Public and environmental health, Occupational health, Environmental sciences (social aspects
Abstract
Automatization, robotics and Industry 4.0 are deeply modifying the working condition with an expected reduction of the number of workers employed in traditional job and an increasing request of new professions. Despite these technologies could limit the involvement of workers, in some sectors humans are still widely employed, as in assembly line of manufacturing companies. As a consequence of this, the Human Factor (HF) will still have relevant influence in term efficiency, quality and safety performances.
This paper approached the HF analysis into the manufacturing field in an assembly line. This study was focused on the analysis of those human-skills that are mainly solicited by the workload of the task that a worker has to perform during his own working activity.
A set of practical test was designed and used to measure those skills during the real working activity. Results showed a wide range of performances reflecting different levels of skills between workers. This kind of information can support the human resources management because it allowed a worker classification based on their own skills. This classification can be directly applied to optimize the allocation of workers in assembly line with the using of Human Performance model and it can lead the way to a personalized risk assessment based on personal skills evaluation.
DOI
http://dx.doi.org/10.3850/978-981-14-8593-0_3914-cd
Recommended Citation
Comberti, Lorenzo & Demichela, Micaela & Leva, Maria. (2020). Human Skills Assessment as a Support to Human Factor Management. 2650-2655. 10.3850/978-981-14-8593-0_3914-cd.
Included in
Environmental Public Health Commons, Environmental Studies Commons, Occupational Health and Industrial Hygiene Commons
Publication Details
Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference.