Paper
9 October 1998 Intelligent task scheduling, planning, and control for manufacturing work cells
Mumin Song, Tzyh-Jong Tarn, Ning Xi
Author Affiliations +
Proceedings Volume 3517, Intelligent Systems in Design and Manufacturing; (1998) https://doi.org/10.1117/12.326934
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States
Abstract
This paper presents a novel approach for solving the challenging problem in intelligent control of manufacturing systems, i.e. the integration of low-level system sensing and simple control with high-level system behavior and perception. The proposed Max-Plus Algebra model combined with event-based planning and control provides a mechanism to efficiently integrate task scheduling, sensing, planning and real-time execution so that task scheduling, which usually deals with discrete types of events, as well as action planning, which usually deals with continuous events, can be treated systematically in a unified analytical model. More importantly, the unique feature of this approach is that interactions between discrete and continuous events can be considered in a unified framework. This feature allows the manufacturing system to intelligently cope with unexpected events and uncertainties so that the efficiency and reliability of the task schedule and action plan can increase significantly. A robotic manufacturing system is used to illustrate the proposed approach. The experimental results clearly demonstrate the advantages of the proposed approach.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mumin Song, Tzyh-Jong Tarn, and Ning Xi "Intelligent task scheduling, planning, and control for manufacturing work cells", Proc. SPIE 3517, Intelligent Systems in Design and Manufacturing, (9 October 1998); https://doi.org/10.1117/12.326934
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Cited by 1 scholarly publication.
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KEYWORDS
Control systems

Manufacturing

Sensing systems

System integration

Intelligence systems

Reliability

Robotic systems

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