A service-oriented simulation integration platform for hierarchical manufacturing planning and control

Dong Xu, Sai Srinivas Nageshwaraniyer and Young-Jun Son

International Journal of Production Research, 2016, vol. 54, issue 23, 7212-7230

Abstract: In this paper, a coherent and comprehensive distributed simulation platform is proposed to support hierarchical manufacturing planning and control. This platform enables integration of various hardware and software components within and across supply chain members, such as manufacturing equipment, physics-based process simulators, system-dynamic, agent-based and discrete-event simulators (DESs), and databases via web services technology. At the shop level, a DES model may run in a stand-alone mode, or in conjunction with other simulators (e.g. process or agent-based simulators) and/or hardware (e.g. robots and machines). At the enterprise level, multiple shop floor simulators (each representing a factory) are integrated into a geographically dispersed environment. Exemplary models simulating aircraft drill and assembly on the shop floor are developed in widely used packages, such as Arena®, Simio®, Anylogic® and ESPRIT®, and then integrated. The proposed platform with the hardware-in-the-loop capability is successfully implemented and demonstrated for an automated manufacturing cell in the Computer Integrated Manufacturing and Simulation lab at the University of Arizona. Experiments are conducted using the proposed platform to test (1) reduction in estimated variance of part cycle time given variations in order arrival rate, effectiveness of materials processers and material handlers, and (2) computational time performance of web services. The experimental results reveal that the proposed platform is viable to enable both vertical (shop simulator to equipment level process simulators and/or equipment) as well as horizontal (e.g. multiple shop level simulators) integrations.

Date: 2016
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1221535 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:54:y:2016:i:23:p:7212-7230

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2016.1221535

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().