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Progress in Artificial Intelligence

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05.06.2018 | Regular Paper

A case study at the Nissan Barcelona factory to minimize the ergonomic risk and its standard deviation in a mixed-model assembly line

verfasst von: Joaquín Bautista-Valhondo, Rocío Alfaro-Pozo

Erschienen in: Progress in Artificial Intelligence | Ausgabe 4/2018

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Abstract

This work examines a balancing problem wherein the objective is to minimize both the ergonomic risk dispersion between the set of workstations of a mixed-model assembly line and the risk level of the workstation with the greatest ergonomic factor. A greedy randomized adaptive search procedure (GRASP) procedure is proposed to achieve these two objectives simultaneously. This new procedure is compared against two mixed integer linear programs: the MILP-1 model that minimizes the maximum ergonomic risk of the assembly line and the MILP-2 model that minimizes the average deviation from ergonomic risks of the set of workstations on the line. The results from the case study based on the automotive sector indicate that the proposed GRASP procedure is a very competitive and promising tool for further research.

Vorheriger Artikel Exploring the association between mobility behaviours and academic performances of students: a context-aware traj-graph (CTG) analysis

Nächster Artikel A refined method of forecasting based on high-order intuitionistic fuzzy time series data

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Titel: A case study at the Nissan Barcelona factory to minimize the ergonomic risk and its standard deviation in a mixed-model assembly line
verfasst von: Joaquín Bautista-Valhondo
Rocío Alfaro-Pozo
Publikationsdatum: 05.06.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Progress in Artificial Intelligence / Ausgabe 4/2018
Print ISSN: 2192-6352
Elektronische ISSN: 2192-6360
DOI: https://doi.org/10.1007/s13748-018-0153-9

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