@misc{Hryniewicz_Olgierd_(1948–_)_Process_2013,
 author={Hryniewicz, Olgierd (1948– ) and Karpiński, Janusz},
 copyright={Creative Commons Attribution BY 4.0 license},
 address={Warszawa},
 journal={Raport Badawczy = Research Report},
 howpublished={online},
 year={2013},
 publisher={Instytut Badań Systemowych. Polska Akademia Nauk},
 publisher={Systems Research Institute. Polish Academy of Sciences},
 language={eng},
 abstract={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.},
 type={Text},
 title={Process control using predicted quality data},
 URL={http://rcin.org.pl./Content/109187/PDF/RB-2013-46.pdf},
 keywords={Data mining, Eksploracja danych, Quality assessment, Ocena jakości, Process control, Kontrola procesu},
}