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Model of Production System Evaluation with the Influence of FDM Machine Reliability and Process-Dependent Product
Iwona Paprocka1, Wojciech M Kempa2
1Department of Engineering Processes Automation and Integrated Manufacturing Systems, Faculty of Mechanical Engineering, Silesian University of Technology, Konarskiego 18A Str., 44-100 Gliwice, Poland.
Materials (Basel, Switzerland)
|October 13, 2021
Summary
This study optimizes job shop scheduling with Fused Deposition Modeling (FDM) machine maintenance. An Ant-Colony Optimization (ACO) model balances production and predictive maintenance for improved efficiency and quality robustness.
Area of Science:
- Operations Research
- Manufacturing Engineering
- Industrial Engineering
Background:
- Job Shop Scheduling Problem (JSSP) is critical for manufacturing efficiency.
- Fused Deposition Modeling (FDM) machines introduce unique maintenance challenges.
- Predictive Maintenance (PdM) is essential for managing FDM machine reliability.
Purpose of the Study:
- To develop a scheduling model for JSSP incorporating FDM machine unavailability due to PdM.
- To minimize makespan, total tardiness, and machine idle time.
- To propose an FDM reliability model linked to process parameter deviations.
Main Methods:
- Ant-Colony Optimization (ACO) algorithm applied to JSSP with PdM constraints.
- Estimation of PdM periods using historical failure-free times and process parameter deviations.
- Development of an FDM reliability model based on weighted p-moving averages of parameter deviations.
Main Results:
- The proposed ACO model effectively schedules production and maintenance tasks.
- FDM machine reliability, influenced by process parameters, impacts production quality robustness.
- Quality robustness increases with FDM operational stability up to a point, then decreases.
Conclusions:
- Integrated scheduling of production and maintenance is crucial for FDM-based JSSP.
- The FDM reliability model provides insights into quality robustness based on process parameter monitoring.
- ACO offers a viable approach for optimizing complex scheduling problems with machine maintenance constraints.
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