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Third IEEE International Symposium on Object-Oriented Real-Time Distributed Computing
Intelligent Scheduling based on Start Time Adjustment for Advanced Sequential Control Systems
Newport Beach, California
March 15-March 17
ISBN: 0-7695-0607-0
Takeiki Aizono, Hitachi Ltd.
Tohru Kikuno, Osaka University
High productivity is required for industrial systems that are to produce large amounts of low-price products. Most industrial systems are sequentially controlled because materials and parts are processed and constructed step by step. A new method of sequential control is needed to increase productivity, and a new technique to schedule the start time of each process is also needed because of frequent adjustment of production lines and their equipment.Intelligent devices such as intelligent sensors and actuators used in the latest industrial systems have embedded high-performance processors and contain software modules. These devices cooperate and control processing robots and production lines. Advanced sequential control is proposed for sequential control systems consisting of distributed software modules.Processing time can be minimized and productivity increased by intelligent scheduling for advanced sequential control, and this paper describes a new method for adjusting the starting times of production processes automatically. This method shortens the time margin and decreases the total processing time. This paper also describes a Processing Flow Diagram that makes it easy to adjust the starting time of each process. The effectiveness of this intelligent scheduling and start-time-adjustment has been demonstrated by using them to optimize the operation of a system for testing disk plates.
Index Terms:
Sequential control, application module, process flow chart, distributed system, high productivity, industrial systems
Citation:
Takeiki Aizono, Tohru Kikuno, "Intelligent Scheduling based on Start Time Adjustment for Advanced Sequential Control Systems," isorc, pp.138, Third IEEE International Symposium on Object-Oriented Real-Time Distributed Computing, 2000
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