Publication
Sustainable short-term production planning optimization
| dc.contributor.author | Zanella, Fernando | |
| dc.contributor.author | Vaz, Clara B. | |
| dc.date.accessioned | 2024-02-15T14:58:38Z | |
| dc.date.available | 2024-02-15T14:58:38Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | This study proposes a framework for short-term production planning of a Portuguese company operating as a tier 2 supplier in the automotive sector. The framework is intended to support the decision-making process regarding a single progressive hydraulic press, which is used to manufacture cold-stamped parts for exhaust systems. The framework consists of two sequential levels: (1) a Mixed-Integer Linear Programming (MILP) model to determine the optimal production quantities per week while minimizing the total cost; (2) a dynamic production sequencing rule for scheduling operations on the hydraulic press. The two levels are combined and implemented in Excel, where the MILP model is solved using the Solver add-in, and the second level uses the optimal production quantities as inputs to determine the production sequence using a dynamic priority rule. To validate the framework, a proposed optimal plan was compared to a real plan executed by the company, and it was found that the framework could save up to 22.1% of the total cost observed in reality while still satisfying demand. To address uncertainties, the framework requires a rolling weekly planning horizon. | pt_PT |
| dc.description.sponsorship | This work has been supported by Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Zanella, Fernando; Vaz, Clara B. (2023). Sustainable short-term production planning optimization. SN Computer Science. ISSN 2662-995X. 4:6, p. 1-12 | pt_PT |
| dc.identifier.doi | 10.1007/s42979-023-02261-7 | pt_PT |
| dc.identifier.eissn | 2661-8907 | |
| dc.identifier.issn | 2662-995X | |
| dc.identifier.uri | http://hdl.handle.net/10198/29487 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Springer Nature | pt_PT |
| dc.relation | LA/P/0007/2021 | pt_PT |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Mixed-integer linear programming | pt_PT |
| dc.subject | Short-term production planning | pt_PT |
| dc.subject | Responsible production | pt_PT |
| dc.title | Sustainable short-term production planning optimization | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT | |
| oaire.citation.endPage | 12 | pt_PT |
| oaire.citation.issue | 6 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | SN Computer Science | pt_PT |
| oaire.citation.volume | 4 | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Vaz | |
| person.givenName | Clara B. | |
| person.identifier | R-001-FQC | |
| person.identifier.ciencia-id | 9611-3386-E516 | |
| person.identifier.orcid | 0000-0001-9862-6068 | |
| person.identifier.rid | F-1519-2016 | |
| person.identifier.scopus-author-id | 56352045500 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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