Tytuł:

Process control using predicted quality data

Inny tytuł:

Raport Badawczy = Research Report ; RB/46/2013

Twórca:

Hryniewicz, Olgierd (1948– ) ; Karpiński, Janusz

Wydawca:

Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences

Miejsce wydania:

Warszawa

Data wydania/powstania:

2013

Opis:

23 pages ; 21 cm ; Bibliography p. 23

Temat i słowa kluczowe:

Data mining ; Eksploracja danych ; Quality assessment ; Ocena jakości ; Process control ; Kontrola procesu

Abstrakt:

SPC procedures are usually designed to control stability of directly observed parameters of a process. However, when quality parameters of interest are related to reliability characteristics it is practically hardly possible to monitor such characteristics directly. Instead, some training data was used to build a model that is used for the prediction of the value of an unobservable variable of inter­est basing on the values of observed explanatory variables. The article considers the model of a process when traditionally applied assumptions are violated. It has been shown that in this case some non-statistical prediction models proposed in the area of data-mining, such as Quinlan’s C4.5 decision tree, perform better than popular linear prediction models. However, new problems have to be considered when shifts in the levels of process parameters may influence the performance of applied classification algorithms.

Czasopismo/Seria/cykl:

Raport Badawczy = Research Report

Typ zasobu:

Text

Szczegółowy typ zasobu:

Report

Źródło:

RB-2013-46

Język:

eng

Język streszczenia:

eng

Prawa:

Creative Commons Attribution BY 4.0 license

Zasady wykorzystania:

Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -

Digitalizacja:

Systems Research Institute of the Polish Academy of Sciences

Lokalizacja oryginału:

Library of Systems Research Institute PAS

Dofinansowane ze środków:

Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.

Dostęp:

Open