New framework for dynamic scheduling of production systems

Author

Nakasuka, Shinichi ; Yoshida, Taketoshi

Author_Institution

IBM Res., Tokyo, Japan

fYear

1989

fDate

10-12 Apr 1989

Firstpage

253

Lastpage

258

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Applications of Machine Intelligence and Vision, 1989., International Workshop on

Conference_Location

Tokyo

Type

conf

DOI

10.1109/MIV.1989.40559

Filename

40559