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Titolo:
An approximate summarization method of process data for acquiring knowledge to improve product quality
Autore:
Shigaki, I; Narazaki, H;
Indirizzi:
Osaka Inst Technol, Dept Ind Management, Asahi Ku, Osaka 535, Japan Osaka Inst Technol Osaka Japan 535 anagement, Asahi Ku, Osaka 535, Japan Kobe Steel Ltd, Elect & Informat Technol Res Lab, Nishi Ku, Kobe, Hyogo, Japan Kobe Steel Ltd Kobe Hyogo Japan ol Res Lab, Nishi Ku, Kobe, Hyogo, Japan
Titolo Testata:
PRODUCTION PLANNING & CONTROL
fascicolo: 4, volume: 12, anno: 2001,
pagine: 379 - 387
SICI:
0953-7287(200106)12:4<379:AASMOP>2.0.ZU;2-5
Fonte:
ISI
Lingua:
ENG
Keywords:
machine learning; knowledge acquisition; ID3 method;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
4
Recensione:
Indirizzi per estratti:
Indirizzo: Shigaki, I Osaka Inst Technol, Dept Ind Management, Asahi Ku, Omiya 5-16-1, Osaka 535, Japan Osaka Inst Technol Omiya 5-16-1 Osaka Japan 535 aka 535, Japan
Citazione:
I. Shigaki e H. Narazaki, "An approximate summarization method of process data for acquiring knowledge to improve product quality", PROD PLAN C, 12(4), 2001, pp. 379-387

Abstract

This paper describes a machine learning approach for a manufacturing database. The method is presented in the Nb-Ti superconducting wire domain. A Nb-Ti superconducting wire is produced by iterating the drawing and heat treatment operations. The purpose is to obtain approximate summarization of process data that describes how a production schedule can be improved for better product quality. The method consists of the following steps: First, der ne a ranking function for a production schedule. Then, generate `positive' and `negative' instances for improving a production schedule by comparing apair of schedules and their ranking values in the database. Using a machine learning technique, called `ID3', a `modification patterns' are obtained that generalize the data for better production quality. The final step is to extract approximate information from the induced patterns, which is both desirable for easier understanding by human experts and necessary to avoid being too much influenced by excessive details or disturbances. Two criteria are proposed, correctness and applicability indices, for this approximation.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 02/07/20 alle ore 21:38:12