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Design and application of task administration protocols for collaborative production and service systems

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  • Sang Ko, Hoo
  • Nof, Shimon Y.

Abstract

This research investigates the design of Task Administration Protocols (TAPs) for effective task allocation and administration in collaborative production/service systems. Customer-focused and concurrent engineering service systems process tasks more effectively as a result of the power of collaboration among multiple participants. In such environments, however, complex situations might arise that require decisions that cannot be handled by simple Coordination Protocols (CPs). To design an effective control mechanism to manage complex situations, this research identifies basic problems in collaborative task administration and proposes the design framework of protocols to solve the problems. In the framework, TAPs consist of three component-protocols: (1) Task Requirement Analysis Protocol, (2) Shared Resource Allocation Protocol, and (3) Synchronization and Time-Out Protocol. Each component protocol is activated to address priority-based allocation, resource-aware allocation, and task re-allocation at a different task administration context, ranging from task initialization, task allocation, to task monitoring, respectively. To analyze feasibility and effectiveness of the proposed design, TAPs are applied to two collaborative production/service systems. Simulations are conducted to evaluate the performance achieved by different TAPs and non-TAP CPs under various load conditions. The results show that there is a significant performance improvement by TAPs over CPs in most cases, e.g., 84% vs. 64% in terms of task completion ratio. The advantage of TAPs can be explained by their design with relatively higher level of collaborative intelligence, addressing more complex control logic than non-TAP CPs.

Suggested Citation

  • Sang Ko, Hoo & Nof, Shimon Y., 2012. "Design and application of task administration protocols for collaborative production and service systems," International Journal of Production Economics, Elsevier, vol. 135(1), pages 177-189.
  • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:177-189
    DOI: 10.1016/j.ijpe.2011.06.005
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    References listed on IDEAS

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    1. Anussornnitisarn, Pornthep & Nof, Shimon Y. & Etzion, Opher, 2005. "Decentralized control of cooperative and autonomous agents for solving the distributed resource allocation problem," International Journal of Production Economics, Elsevier, vol. 98(2), pages 114-128, November.
    2. Wellman, Michael P. & Walsh, William E. & Wurman, Peter R. & MacKie-Mason, Jeffrey K., 2001. "Auction Protocols for Decentralized Scheduling," Games and Economic Behavior, Elsevier, vol. 35(1-2), pages 271-303, April.
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    Cited by:

    1. Moghaddam, Mohsen & Nof, Shimon Y., 2014. "Combined demand and capacity sharing with best matching decisions in enterprise collaboration," International Journal of Production Economics, Elsevier, vol. 148(C), pages 93-109.
    2. Moghaddam, Mohsen & Nof, Shimon Y., 2016. "Real-time optimization and control mechanisms for collaborative demand and capacity sharing," International Journal of Production Economics, Elsevier, vol. 171(P4), pages 495-506.
    3. Yilmaz, Ibrahim & Yoon, Sang Won, 2020. "Dynamic-distributed decisions and sharing protocol for fair resource sharing in collaborative network," International Journal of Production Economics, Elsevier, vol. 226(C).
    4. Jahanpour, Ehsan & Ko, Hoo Sang & Nof, Shimon Y., 2016. "Collaboration protocols for sustainable wind energy distribution networks," International Journal of Production Economics, Elsevier, vol. 182(C), pages 496-507.
    5. Jayaram, Jayanth & Xu, Kefeng, 2013. "The relative influence of external versus internal integration on plant performance in China," International Journal of Production Economics, Elsevier, vol. 146(1), pages 59-69.
    6. Menéndez-Caravaca, Eloísa & Bueno, Salvador & Gallego, M. Dolores, 2021. "Exploring the link between free and open source software and the collaborative economy: A Delphi-based scenario for the year 2025," Technological Forecasting and Social Change, Elsevier, vol. 173(C).

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