2023
DOI: 10.1109/tase.2022.3156384
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Cooperative Product Agents to Improve Manufacturing System Flexibility: A Model-Based Decision Framework

Abstract: Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this contr… Show more

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Cited by 20 publications
(2 citation statements)
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References 71 publications
(178 reference statements)
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“…It enables optimization of manufacturing processes and addresses the challenges posed by dynamic production environments and customer demands [17,18]. Existing agent architectures propose a part agent that is responsible for scheduling and resource allocation, utilizing model-based reasoning for production goals and cooperative scheduling [19,20].…”
Section: Related Workmentioning
confidence: 99%
“…It enables optimization of manufacturing processes and addresses the challenges posed by dynamic production environments and customer demands [17,18]. Existing agent architectures propose a part agent that is responsible for scheduling and resource allocation, utilizing model-based reasoning for production goals and cooperative scheduling [19,20].…”
Section: Related Workmentioning
confidence: 99%
“…Based on the processing energy characteristics in resource-constrained processing environments, Li et al [24] proposed a comprehensive solution to minimize the energy consumption and completion time of resource-constrained. Kovalenko et al [25] proposed a multi-intelligent control strategy to improve the flexibility of manufacturing systems. Kung and Liao [26] consider the optimization of joint predictive maintenance and job scheduling problems to minimize total shortage losses and develop a heuristic algorithm based on the Tabu search.…”
Section: Low-carbon Manufacturing Scheduling Optimizationmentioning
confidence: 99%