Dynamic Scheduling and Preventive Maintenance in Small-Batch Production: A Flexible Control Approach for Maximising Machine Reliability and Minimising Delays
Single- and small-batch production requires flexible production control to maximise machine reliability and minimise delivery delays. Existing planning approaches often do not take into account the dynamic production conditions of these environments, where machine breakdowns, variable order volumes...
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MDPI AG
2025-04-01
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| Online Access: | https://www.mdpi.com/2076-3417/15/8/4287 |
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| author | Alexandra Maierhofer Sebastian Trojahn Frank Ryll |
| author_facet | Alexandra Maierhofer Sebastian Trojahn Frank Ryll |
| author_sort | Alexandra Maierhofer |
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| description | Single- and small-batch production requires flexible production control to maximise machine reliability and minimise delivery delays. Existing planning approaches often do not take into account the dynamic production conditions of these environments, where machine breakdowns, variable order volumes and short-term changes lead to inefficiencies. This paper presents an enhanced job-shop scheduling model that integrates preventive maintenance strategies directly into production control. Using a mixed-integer programming approach, machine allocation and maintenance measures are optimised simultaneously in order to reduce unplanned downtimes and make efficient use of free time slots. The model is implemented in Python with Pyomo (Python 3.13.0 and Pyomo Version: 6.8.0) and validated using a scenario. The results show that an adaptive maintenance strategy contributes significantly to reducing machine downtimes without compromising production output. Visualisations support users in their decision-making by clearly presenting machine availability, maintenance slots and production orders. The approach is specifically designed for production and maintenance planners who need efficient and adaptable scheduling in volatile production environments. Compared to traditional maintenance models, this approach improves schedule adherence and optimises resource utilisation by dynamically linking production control and maintenance planning. |
| format | Article |
| id | doaj-art-9c898e3e9cc04e18a243b5ad31356ec6 |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-9c898e3e9cc04e18a243b5ad31356ec62025-08-20T03:14:17ZengMDPI AGApplied Sciences2076-34172025-04-01158428710.3390/app15084287Dynamic Scheduling and Preventive Maintenance in Small-Batch Production: A Flexible Control Approach for Maximising Machine Reliability and Minimising DelaysAlexandra Maierhofer0Sebastian Trojahn1Frank Ryll2Department of Economics, Anhalt University of Applied Sciences, Strenzfelder Allee 28, 06406 Bernburg, GermanyDepartment of Economics, Anhalt University of Applied Sciences, Strenzfelder Allee 28, 06406 Bernburg, GermanyFraunhofer Institute for Factory Operation and Automation IFF, Sandtorstrasse 22, 39106 Magdeburg, GermanySingle- and small-batch production requires flexible production control to maximise machine reliability and minimise delivery delays. Existing planning approaches often do not take into account the dynamic production conditions of these environments, where machine breakdowns, variable order volumes and short-term changes lead to inefficiencies. This paper presents an enhanced job-shop scheduling model that integrates preventive maintenance strategies directly into production control. Using a mixed-integer programming approach, machine allocation and maintenance measures are optimised simultaneously in order to reduce unplanned downtimes and make efficient use of free time slots. The model is implemented in Python with Pyomo (Python 3.13.0 and Pyomo Version: 6.8.0) and validated using a scenario. The results show that an adaptive maintenance strategy contributes significantly to reducing machine downtimes without compromising production output. Visualisations support users in their decision-making by clearly presenting machine availability, maintenance slots and production orders. The approach is specifically designed for production and maintenance planners who need efficient and adaptable scheduling in volatile production environments. Compared to traditional maintenance models, this approach improves schedule adherence and optimises resource utilisation by dynamically linking production control and maintenance planning.https://www.mdpi.com/2076-3417/15/8/4287machine reliabilityoptimisation modelpreventive maintenanceproduction schedulingsmall-batch manufacturingsustainable manufacturing |
| spellingShingle | Alexandra Maierhofer Sebastian Trojahn Frank Ryll Dynamic Scheduling and Preventive Maintenance in Small-Batch Production: A Flexible Control Approach for Maximising Machine Reliability and Minimising Delays Applied Sciences machine reliability optimisation model preventive maintenance production scheduling small-batch manufacturing sustainable manufacturing |
| title | Dynamic Scheduling and Preventive Maintenance in Small-Batch Production: A Flexible Control Approach for Maximising Machine Reliability and Minimising Delays |
| title_full | Dynamic Scheduling and Preventive Maintenance in Small-Batch Production: A Flexible Control Approach for Maximising Machine Reliability and Minimising Delays |
| title_fullStr | Dynamic Scheduling and Preventive Maintenance in Small-Batch Production: A Flexible Control Approach for Maximising Machine Reliability and Minimising Delays |
| title_full_unstemmed | Dynamic Scheduling and Preventive Maintenance in Small-Batch Production: A Flexible Control Approach for Maximising Machine Reliability and Minimising Delays |
| title_short | Dynamic Scheduling and Preventive Maintenance in Small-Batch Production: A Flexible Control Approach for Maximising Machine Reliability and Minimising Delays |
| title_sort | dynamic scheduling and preventive maintenance in small batch production a flexible control approach for maximising machine reliability and minimising delays |
| topic | machine reliability optimisation model preventive maintenance production scheduling small-batch manufacturing sustainable manufacturing |
| url | https://www.mdpi.com/2076-3417/15/8/4287 |
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