Human fallibility in working environments contributes to majority of incidents and accidents in high-risk systems, while it affects the quality and productivity in low-risk systems. Over the years, the human factor has attracted more and more attention, and different aspects of the work have been taken into account to prevent and/or reduce the number of accidents and incidents and improve human performance in industrial systems. The selection of adequate work-rest policies through the introduction of appropriate breaks is a very efficient approach even if it is not widely applied. It is well known that introducing breaks is a key intervention to provide recovery after fatiguing physical work, prevent the growth of accident risks during working activities, and improve human reliability and productivity for individuals engaged in either mental or physical tasks. This paper focuses on the simulator for human error probability analysis (SHERPA) model for the break scheduling problems. This model aims to predict the human error probability (HEP) and assess the impact of the context via performance shaping factors. The main focus of SHERPA is modeling and simulation of rest breaks in every working context and conditions in order to reduce errors and increase productivity and efficiencies. As shown in the case study, the model is useful in assessing the impact of different work-break policies, with different placement and duration of breaks, on human performance (HEP and recovery after the break) and on the overall system performance in terms of percentage of compliant performed tasks and economic results.

A model for break scheduling assessment in manufacturing systems

Di Pasquale, Valentina;Fruggiero, Fabio;Iannone, Raffaele;Miranda, Salvatore
2017-01-01

Abstract

Human fallibility in working environments contributes to majority of incidents and accidents in high-risk systems, while it affects the quality and productivity in low-risk systems. Over the years, the human factor has attracted more and more attention, and different aspects of the work have been taken into account to prevent and/or reduce the number of accidents and incidents and improve human performance in industrial systems. The selection of adequate work-rest policies through the introduction of appropriate breaks is a very efficient approach even if it is not widely applied. It is well known that introducing breaks is a key intervention to provide recovery after fatiguing physical work, prevent the growth of accident risks during working activities, and improve human reliability and productivity for individuals engaged in either mental or physical tasks. This paper focuses on the simulator for human error probability analysis (SHERPA) model for the break scheduling problems. This model aims to predict the human error probability (HEP) and assess the impact of the context via performance shaping factors. The main focus of SHERPA is modeling and simulation of rest breaks in every working context and conditions in order to reduce errors and increase productivity and efficiencies. As shown in the case study, the model is useful in assessing the impact of different work-break policies, with different placement and duration of breaks, on human performance (HEP and recovery after the break) and on the overall system performance in terms of percentage of compliant performed tasks and economic results.
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Descrizione: 0360-8352/Ó 2017 Elsevier Ltd. All rights reserved. Link editore: http://dx.doi.org/10.1016/j.cie.2017.05.017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4707859
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