Production scheduling in a reconfigurable manufacturing system benefiting from human-robot collaboration

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F24%3A00364330" target="_blank" >RIV/68407700:21730/24:00364330 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1080/00207543.2023.2173503" target="_blank" >https://doi.org/10.1080/00207543.2023.2173503</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/00207543.2023.2173503" target="_blank" >10.1080/00207543.2023.2173503</a>

Result language

angličtina

Original language name

Production scheduling in a reconfigurable manufacturing system benefiting from human-robot collaboration

Original language description

Nowadays, the manufacturing sector needs higher levels of flexibility to confront the extremely volatile market. Accordingly, exploiting both machine and workforce reconfigurability as two critical sources of flexibility is advantageous. In this regard, for the first time, this paper explores an integrated production scheduling and workforce planning problem in a Reconfigurable Manufacturing System (RMS) benefiting from reconfigurable machines and human-robot collaboration. A new Mixed-Integer Linear Programming (MILP) model and an efficient Constraint Programming (CP) model are developed to formulate the problem, minimising the makespan as the performance metric. Due to the high complexity of the problem, the MILP model cannot handle large-sized instances. Hence, to evaluate the performance of the CP model in large-sized instances, a lower bound is derived based on the relaxation of the problem. Finally, extensive computational experiments are carried out to assess the performance of the devised MILP and CP models and provide general recommendations for managers dealing with such a complex problem. The results reveal the superiority of the CP model over the MILP model in small- and medium-sized instances. Moreover, the CP model can find high-quality solutions for large-sized instances within a reasonable computational time.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EF15_003%2F0000466" target="_blank" >EF15_003/0000466: Artificial Intelligence and Reasoning</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

International Journal of Production Research

ISSN

0020-7543

e-ISSN

1366-588X

Volume of the periodical

62

Issue of the periodical within the volume

3

Country of publishing house

GB - UNITED KINGDOM

Number of pages

17

Pages from-to

767-783

UT code for WoS article

000931027300001

EID of the result in the Scopus database

2-s2.0-85147801644