Work

Jobs scheduling within Industry 4.0 with consideration of worker’s fatigue and reliability using Greedy Randomized Adaptive Search Procedure

Year: 2019

Type: article

Abstract: The agility and the reactivity of the emerging Industry 4.0 work paradigm will probably lead to work intensification. Hence, in order to ensure an effective and safe human machine systems, jobs scheduling must be addressed with consideration of human factors. Following this trend, this paper details a new integer programming model for jobs scheduling with consideration of worker fatigue and reliability. Using Greedy Randomized Adaptive Search Procedure (GRASP), this model can be used in real-time to support manufacturing execution system in Factories of the Future to achieve efficient and safe jobs scheduling.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2019.12.114

Authors: I. El Mouayni, G. Demesure, H. Bril-El Haouzi, P. Charpentier, A. Siadat

Institutions: CRAN, Université de Lorraine, Arts et Métiers, Laboratoire de Conception Fabrication Commande

Language: English

Topic: Scheduling and Optimization Algorithms

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Decent work and economic growth, Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W2997754356

FWCI: 1.058

Cites: 26

Cited by: 20

Related to: 10