Optimization model for production scheduling taking into account preventive maintenance in an uncertainty-based
Plamen Penchev1, Pavel Vitliemov1, Ivan Georgiev2,3
1Department of Business and Management, University of Ruse, Studentska 8, 7017, Ruse, Bulgaria.
Heliyon
|July 7, 2023
Summary
This study introduces an optimization model for manufacturing, enhancing production schedules and maintenance plans. The model efficiently allocates production orders, minimizes machine usage, and improves overall operational efficiency.
Area of Science:
- Operations Research
- Industrial Engineering
- Manufacturing Systems
Background:
- Industry 4.0 presents dynamic challenges for industrial manufacturing.
- Optimization of production schedules and maintenance plans is critical for efficiency.
- Existing models may not fully address real-world manufacturing complexities.
Purpose of the Study:
- To present a mathematical model for optimizing production schedules.
- To integrate preventive maintenance and planner preferences into scheduling.
- To provide flexibility for real-time schedule adjustments.
Main Methods:
- Development of a mathematical optimization model.
- Incorporation of constraints for maintenance and planner preferences.
- Verification through quasi-real and real-life experiments.
Main Results:
- The model successfully generates valid production schedules.
- Optimized production line usage, including non-use of unnecessary machines (e.g., 4 of 12 lines unused).
- Demonstrated improvements in order execution times and overall efficiency.
Conclusions:
- The model enhances production planning by optimizing machine usage and product allocation.
- Significant cost savings and increased efficiency are achievable.
- Integration with Enterprise Resource Planning (ERP) systems can streamline scheduling.
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