Automated and Optimized Scheduling for CNC Machines
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| Publicat a: | Mathematics vol. 13, no. 16 (2025), p. 2621-2641 |
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| Autor principal: | |
| Altres autors: | , |
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MDPI AG
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| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2227-7390 | ||
| 024 | 7 | |a 10.3390/math13162621 |2 doi | |
| 035 | |a 3244045026 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231533 |2 nlm | ||
| 100 | 1 | |a Martins Guilherme Sousa Silva |u Centre of Mathematics, University of Minho, 4710-057 Braga, Portugal; pg52214@alunos.uminho.pt (G.S.S.M.); mfc@math.uminho.pt (M.F.P.C.) | |
| 245 | 1 | |a Automated and Optimized Scheduling for CNC Machines | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This work presents the design and implementation of an automated, digital, and modular system to address a real-world industrial challenge: the automation and optimization of production schedules for Computer Numerical Control (CNC) machines in a factory in Portugal. The goal is to replicate and enhance the existing manual scheduling process by integrating multiple data sources and formulating a general Mixed-Integer Linear Programming (MILP) model with constraints. This model can be solved using MILP optimization methods to produce efficient scheduling solutions that minimize machine downtime, reduce tool change frequency, and lower operator workload. The proposed system is implemented using open-source Python abstraction interfaces (Python-MIP), employing state-of-the-art of MILP optimization solvers such as CBC and HiGHS for solution validation. The system is designed to accommodate a wide range of constraints and operational factors, which can be switched on or off as needed, thereby enhancing its flexibility and decision-support capabilities. Additionally, a user-friendly graphical application is developed to facilitate the input of specific scheduling data and constraints, enabling flexible and efficient formulation of diverse scheduling scenarios. The proposed system is validated through multiple case studies, demonstrating its effectiveness in optimizing industrial CNC scheduling tasks and providing a scalable, practical tool for real-world factory operations. | |
| 653 | |a Mathematical programming | ||
| 653 | |a Scheduling | ||
| 653 | |a Software | ||
| 653 | |a Linear programming | ||
| 653 | |a Workers | ||
| 653 | |a Software development | ||
| 653 | |a Integer programming | ||
| 653 | |a Mathematical models | ||
| 653 | |a Modular systems | ||
| 653 | |a Numerical controls | ||
| 653 | |a Automation | ||
| 653 | |a Production scheduling | ||
| 653 | |a Optimization | ||
| 653 | |a Job shops | ||
| 653 | |a Mixed integer | ||
| 653 | |a Constraints | ||
| 653 | |a Optimization algorithms | ||
| 653 | |a Downtime | ||
| 653 | |a Factories | ||
| 700 | 1 | |a Costa M. Fernanda P. |u Centre of Mathematics, University of Minho, 4710-057 Braga, Portugal; pg52214@alunos.uminho.pt (G.S.S.M.); mfc@math.uminho.pt (M.F.P.C.) | |
| 700 | 1 | |a Alves Filipe |u DTx—Digital Transformation CoLAB, University of Minho, 4800-058 Guimarães, Portugal | |
| 773 | 0 | |t Mathematics |g vol. 13, no. 16 (2025), p. 2621-2641 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3244045026/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3244045026/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3244045026/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |