Application of decision trees for quality management support

Rafal Cupek; Adam Ziebinski; Marek Drewniak

doi:10.1007/978-3-319-98446-9_7

Application of decision trees for quality management support

Rafal Cupek
, Adam Ziebinski
, Marek Drewniak

Katedra Systemów Rozproszonych i Urządzeń Informatyki (RAU/RAU8)

AIUT

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

1 Cytowanie z bazy Scopus

Abstrakt

The quality management process is one of the most important manufacturing activities. Although it can be implemented in a dedicated IT system, because of the easy access to production data in Manufacturing Execution Systems, it seems that an MES is a particularly convenient place for its implementation. This paper describes the concept of using decision tree methods to analyse the relationship between the production path and quality problems. The proposed method is based on an information model that is compliant with the ISA95 standard. Because of this, it can be applied not only in the case presented in the research part, but is also applicable for the problem of quality analysis in other types of discrete production. The authors present the information model that was used, the proposed method of analysis and the results for the simulation data. The simulation scenario was created as a simplification of the actual production process of electronic devices performed by AIUT company.

Język oryginału	angielski
Tytuł publikacji goszczącej	Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings
Redaktorzy	Ngoc Thanh Nguyen, Bogdan Trawinski, Ngoc Thanh Nguyen, Elias Pimenidis, Zaheer Khan
Wydawca	Springer Verlag
Strony	67-78
Liczba stron	12
ISBN (drukowany)	9783319984452
Identyfikatory DOI	https://doi.org/10.1007/978-3-319-98446-9_7
Status publikacji	Opublikowano - 2018
Wydarzenie	10th International Conference on Computational Collective Intelligence, ICCCI 2018 - Bristol, Wielka Brytania Czas trwania: 5 wrz 2018 → 7 wrz 2018

Seria publikacji

Nazwa	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Tom	11056 LNAI
ISSN (drukowany)	0302-9743
ISSN (elektroniczny)	1611-3349

Konferencja

Konferencja	10th International Conference on Computational Collective Intelligence, ICCCI 2018
Kraj/Terytorium	Wielka Brytania
Miejscowość	Bristol
Okres	5/09/18 → 7/09/18

Cele SDG ONZ

Ten wynik przyczynia się do realizacji następujących celów zrównoważonego rozwoju

Cel 9 Przemysł, innowacje i infrastruktura

Obszary tematyczne ASJC Scopus

Informatyka teoretyczna
Informatyka ogólna

Uzyskaj dostęp do dokumentu

10.1007/978-3-319-98446-9_7

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

Cupek, R., Ziebinski, A., & Drewniak, M. (2018). Application of decision trees for quality management support. W N. T. Nguyen, B. Trawinski, N. T. Nguyen, E. Pimenidis, & Z. Khan (Red.), Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings (str. 67-78). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Tom 11056 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-98446-9_7

Cupek, Rafal ; Ziebinski, Adam ; Drewniak, Marek. / Application of decision trees for quality management support. Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings. redaktor / Ngoc Thanh Nguyen ; Bogdan Trawinski ; Ngoc Thanh Nguyen ; Elias Pimenidis ; Zaheer Khan. Springer Verlag, 2018. str. 67-78 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{ef838813ec454a249826f5ec808b44cb,

title = "Application of decision trees for quality management support",

abstract = "The quality management process is one of the most important manufacturing activities. Although it can be implemented in a dedicated IT system, because of the easy access to production data in Manufacturing Execution Systems, it seems that an MES is a particularly convenient place for its implementation. This paper describes the concept of using decision tree methods to analyse the relationship between the production path and quality problems. The proposed method is based on an information model that is compliant with the ISA95 standard. Because of this, it can be applied not only in the case presented in the research part, but is also applicable for the problem of quality analysis in other types of discrete production. The authors present the information model that was used, the proposed method of analysis and the results for the simulation data. The simulation scenario was created as a simplification of the actual production process of electronic devices performed by AIUT company.",

keywords = "Decision trees, ISA95 (IEC 62264), Information model, Manufacturing Execution System (MES), Quality management",

author = "Rafal Cupek and Adam Ziebinski and Marek Drewniak",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 10th International Conference on Computational Collective Intelligence, ICCCI 2018 ; Conference date: 05-09-2018 Through 07-09-2018",

year = "2018",

doi = "10.1007/978-3-319-98446-9\_7",

language = "English",

isbn = "9783319984452",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "67--78",

editor = "Nguyen, \{Ngoc Thanh\} and Bogdan Trawinski and Nguyen, \{Ngoc Thanh\} and Elias Pimenidis and Zaheer Khan",

booktitle = "Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings",

address = "Germany",

}

Cupek, R , Ziebinski, A & Drewniak, M 2018, Application of decision trees for quality management support. w NT Nguyen, B Trawinski, NT Nguyen, E Pimenidis & Z Khan (red), Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), tom 11056 LNAI, Springer Verlag, str. 67-78, 10th International Conference on Computational Collective Intelligence, ICCCI 2018, Bristol, Wielka Brytania, 5/09/18. https://doi.org/10.1007/978-3-319-98446-9_7

Application of decision trees for quality management support. / Cupek, Rafal ; Ziebinski, Adam; Drewniak, Marek.
Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings. red. / Ngoc Thanh Nguyen; Bogdan Trawinski; Ngoc Thanh Nguyen; Elias Pimenidis; Zaheer Khan. Springer Verlag, 2018. str. 67-78 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Tom 11056 LNAI).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

T1 - Application of decision trees for quality management support

AU - Cupek, Rafal

AU - Ziebinski, Adam

AU - Drewniak, Marek

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018

Y1 - 2018

N2 - The quality management process is one of the most important manufacturing activities. Although it can be implemented in a dedicated IT system, because of the easy access to production data in Manufacturing Execution Systems, it seems that an MES is a particularly convenient place for its implementation. This paper describes the concept of using decision tree methods to analyse the relationship between the production path and quality problems. The proposed method is based on an information model that is compliant with the ISA95 standard. Because of this, it can be applied not only in the case presented in the research part, but is also applicable for the problem of quality analysis in other types of discrete production. The authors present the information model that was used, the proposed method of analysis and the results for the simulation data. The simulation scenario was created as a simplification of the actual production process of electronic devices performed by AIUT company.

AB - The quality management process is one of the most important manufacturing activities. Although it can be implemented in a dedicated IT system, because of the easy access to production data in Manufacturing Execution Systems, it seems that an MES is a particularly convenient place for its implementation. This paper describes the concept of using decision tree methods to analyse the relationship between the production path and quality problems. The proposed method is based on an information model that is compliant with the ISA95 standard. Because of this, it can be applied not only in the case presented in the research part, but is also applicable for the problem of quality analysis in other types of discrete production. The authors present the information model that was used, the proposed method of analysis and the results for the simulation data. The simulation scenario was created as a simplification of the actual production process of electronic devices performed by AIUT company.

KW - Decision trees

KW - ISA95 (IEC 62264)

KW - Information model

KW - Manufacturing Execution System (MES)

KW - Quality management

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U2 - 10.1007/978-3-319-98446-9_7

DO - 10.1007/978-3-319-98446-9_7

M3 - Conference contribution

AN - SCOPUS:85053166192

SN - 9783319984452

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 67

EP - 78

BT - Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings

A2 - Nguyen, Ngoc Thanh

A2 - Trawinski, Bogdan

A2 - Nguyen, Ngoc Thanh

A2 - Pimenidis, Elias

A2 - Khan, Zaheer

PB - Springer Verlag

T2 - 10th International Conference on Computational Collective Intelligence, ICCCI 2018

Y2 - 5 September 2018 through 7 September 2018

ER -

Cupek R , Ziebinski A, Drewniak M. Application of decision trees for quality management support. W Nguyen NT, Trawinski B, Nguyen NT, Pimenidis E, Khan Z, redaktorzy, Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings. Springer Verlag. 2018. str. 67-78. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-98446-9_7

Application of decision trees for quality management support

Abstrakt

Seria publikacji

Konferencja

Cele SDG ONZ

Obszary tematyczne ASJC Scopus

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