Sustainable Short-Term Production Planning Optimization
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Published:2023-10-28
Issue:6
Volume:4
Page:
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ISSN:2661-8907
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Container-title:SN Computer Science
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language:en
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Short-container-title:SN COMPUT. SCI.
Author:
Zanella Fernando,
Vaz Clara BentoORCID
Abstract
AbstractThis 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.
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Computer Networks and Communications,Computer Graphics and Computer-Aided Design,Computational Theory and Mathematics,Artificial Intelligence,General Computer Science
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