Title :
New framework for dynamic scheduling of production systems
Author :
Nakasuka, Shinichi ; Yoshida, Taketoshi
Author_Institution :
IBM Res., Tokyo, Japan
Abstract :
A concept for dynamic scheduling in manufacturing systems is proposed. The scope of `dynamic scheduling´ treated includes online dynamic change of some scheduling parameters such as rules for part dispatching, machine selection, or routing. IF-THEN-type heuristic operators are utilized to perform this online real-time rule selection, and offline machine learning is used to obtain more detailed and powerful heuristics than those implemented by human experts or programmers. A learning algorithm has been developed to formulate operators that can treat quantity-type as well as quality-type information. A prototype computer program named learning aided dynamic scheduler (LADS) has been developed. A simulation study using LADS indicates good results for dynamic scheduling
Keywords :
digital simulation; expert systems; production control; scheduling; IF-THEN-type heuristic operators; LADS; dynamic scheduling; learning aided dynamic scheduler; learning algorithm; machine selection; manufacturing systems; offline machine learning; online dynamic change; part dispatching; production systems; prototype computer program; quality-type information; quantity-type; real-time rule selection; routing; scheduling parameters; simulation study; Dispatching; Dynamic scheduling; Humans; Job shop scheduling; Machine learning; Machine learning algorithms; Manufacturing systems; Production systems; Programming profession; Routing;
Conference_Titel :
Industrial Applications of Machine Intelligence and Vision, 1989., International Workshop on
Conference_Location :
Tokyo
DOI :
10.1109/MIV.1989.40559
