Improving Just-in-Time Delivery Performance of IoT-Enabled Flexible Manufacturing Systems with AGV Based Material Transportation

Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex na...

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Veröffentlicht in:Sensors (Basel, Switzerland) Jg. 20; H. 21; S. 6333
Hauptverfasser: Yao, Fengjia, Alkan, Bugra, Ahmad, Bilal, Harrison, Robert
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 06.11.2020
MDPI
Schlagworte:
autonomous guided vehicles
Decision making
Decision support systems
Efficiency
Flexibility
Flexible manufacturing systems
Flooring
Genetic algorithms
Heuristic
industry 4.0
Internet of Things
Linear programming
Logistics
Materials handling
Mathematical programming
Production planning
Productivity
Schedules
Scheduling
shop-floor logistics
ISSN:1424-8220, 1424-8220
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Zusammenfassung:Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex nature associated with the multiple part types and alternate material transfer routings. This paper presents a decision support system capable of supporting shop-floor decision-making activities during the event of manufacturing disruptions by automatically adjusting both AGV and machine schedules in Flexible Manufacturing Systems (FMSs). The proposed system uses discrete event simulation (DES) models enhanced by the Internet-of-Things (IoT) enabled digital integration and employs a nonlinear mixed integer programming Genetic Algorithm (GA) to find near-optimal production schedules prioritising the just-in-time (JIT) material delivery performance and energy efficiency of the material transportation. The performance of the proposed system is tested on the Integrated Manufacturing and Logistics (IML) demonstrator at WMG, University of Warwick. The results showed that the developed system can find the near-optimal solutions for production schedules subjected to production anomalies in a negligible time, thereby supporting shop-floor decision-making activities effectively and rapidly.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s20216333