Worldwide, just under 5,800 people go to work every day and do not return because they die on the job. The groundbreaking Industry 4.0 paradigm includes innovative approaches to improve the safety in the workplace, but Small and Medium Enterprises (SMEs)—which represent 99% of the companies in the EU—are often unprepared to the high costs for safety. A cost-effective way to improve the level of safety in SMEs may be to just reassign employees to tasks, and assign hazardous tasks to the more cautious employees. This paper presents a multi-objective approach to reallocate the personnel of a company to the tasks in order to maximize the workplace safety, while minimizing the cost, and the time to learn the new tasks assigned. Pareto-optimal reallocations are first generated using the Non-dominated Sorting artificial Bee Colony (NSBC) algorithm, and the best one is then selected using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The approach was tested in two SMEs with 11 and 25 employees, respectively.

Artificial bee colony optimization to reallocate personnel to tasks improving workplace safety

Lazzerini, Beatrice
Primo
;
Pistolesi, Francesco
Secondo
2018

Abstract

Worldwide, just under 5,800 people go to work every day and do not return because they die on the job. The groundbreaking Industry 4.0 paradigm includes innovative approaches to improve the safety in the workplace, but Small and Medium Enterprises (SMEs)—which represent 99% of the companies in the EU—are often unprepared to the high costs for safety. A cost-effective way to improve the level of safety in SMEs may be to just reassign employees to tasks, and assign hazardous tasks to the more cautious employees. This paper presents a multi-objective approach to reallocate the personnel of a company to the tasks in order to maximize the workplace safety, while minimizing the cost, and the time to learn the new tasks assigned. Pareto-optimal reallocations are first generated using the Non-dominated Sorting artificial Bee Colony (NSBC) algorithm, and the best one is then selected using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The approach was tested in two SMEs with 11 and 25 employees, respectively.
978-3-319-72925-1
File in questo prodotto:
File Dimensione Formato  
MOD2017.pdf

embargo fino al 31/12/2019

Descrizione: Articolo principale
Tipologia: Documento in Post-print
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 615.39 kB
Formato Adobe PDF
615.39 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/889847
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact