Developing an Agent Based Heuristic Optimisation System for Complex Flow Shops with Customer-Imposed Production Disruptions

Tunde Victor Adediran, Ammar Al Bazi

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Abstract

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, customer demand changes in the required delivery date, sequence of delivery or cancellation of orders cause disruptions to supplier flow-shops that impact production processes and inventory control, calling for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system are developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process for automotive parts and components is adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of the total number of late orders, order delivery time, number of setups, and resource utilization, which provides useful information for the decision-making policies of manufacturers.
Original languageEnglish
Pages (from-to)291–322
Number of pages32
JournalJournal of Information and Communication Technology
Volume18
Issue number2
Publication statusPublished - 30 Apr 2018

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Inventory control
Process control
Decision making
Recovery
Experiments

Keywords

  • agent-based simulation
  • customer production disruptions
  • flow-shops
  • heuristic optimisation algorithm
  • manufacturing systems

Cite this

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abstract = "The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, customer demand changes in the required delivery date, sequence of delivery or cancellation of orders cause disruptions to supplier flow-shops that impact production processes and inventory control, calling for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system are developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process for automotive parts and components is adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of the total number of late orders, order delivery time, number of setups, and resource utilization, which provides useful information for the decision-making policies of manufacturers.",
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AB - The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, customer demand changes in the required delivery date, sequence of delivery or cancellation of orders cause disruptions to supplier flow-shops that impact production processes and inventory control, calling for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system are developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process for automotive parts and components is adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of the total number of late orders, order delivery time, number of setups, and resource utilization, which provides useful information for the decision-making policies of manufacturers.

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