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doi:10.22028/D291-37258
Titel: | Workforce scheduling incorporating worker skills and ergonomic constraints |
VerfasserIn: | Rinaldi, Marta Fera, Marcello Bottani, Eleonora Grosse, Eric H. |
Sprache: | Englisch |
Titel: | Computers & Industrial Engineering |
Bandnummer: | 168 |
Verlag/Plattform: | Elsevier |
Erscheinungsjahr: | 2022 |
Freie Schlagwörter: | Ergonomics Human skill Human performance Workforce assignment Empirical study |
DDC-Sachgruppe: | 330 Wirtschaft |
Dokumenttyp: | Journalartikel / Zeitschriftenartikel |
Abstract: | In the last few decades, studies have demonstrated the correlation between worker well-being and the performance of production systems. This paper addresses the problem of assigning workers to tasks in a workshop system. In this context, recent researches have focused on the ergonomics assessment, often neglecting the evaluation of the workers’ performance. This study aims to formulate a mixed integer linear programming model to solve the workforce scheduling problem and improve the performance of the system integrating ergonomics and human skills. To overcome the complexity of the combinatorial problem, a constructive heuristic procedure is developed. Moreover, a novel approach is proposed to determine the workers’ skills. Human performance is modelled in terms of the time required to perform consecutive tasks, considering different sequences of tasks. In addition, the model was applied to a real case study to verify its feasibility. Different scenarios are tested, considering different levels of exposure to different risk factors. The results indicate that a limited increase in the makespan enables decreasing the risk level and the achievement of an excellent workload balance among workers in terms of time spent in performing tasks. Moreover, the heuristic procedure has demonstrated to perform well on instances of realistic size, and it could be adapted to many manufacturing systems to solve the problem in real industrial contexts. |
DOI der Erstveröffentlichung: | 10.1016/j.cie.2022.108107 |
URL der Erstveröffentlichung: | https://www.sciencedirect.com/science/article/abs/pii/S0360835222001772 |
Link zu diesem Datensatz: | urn:nbn:de:bsz:291--ds-372586 hdl:20.500.11880/33774 http://dx.doi.org/10.22028/D291-37258 |
ISSN: | 0360-8352 |
Datum des Eintrags: | 16-Sep-2022 |
Fakultät: | HW - Fakultät für Empirische Humanwissenschaften und Wirtschaftswissenschaft |
Fachrichtung: | HW - Wirtschaftswissenschaft |
Professur: | HW - Prof. Dr. Eric Grosse |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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