Vše

Co hledáte?

Vše
Projekty
Výsledky výzkumu
Subjekty

Rychlé hledání

  • Projekty podpořené TA ČR
  • Významné projekty
  • Projekty s nejvyšší státní podporou
  • Aktuálně běžící projekty

Chytré vyhledávání

  • Takto najdu konkrétní +slovo
  • Takto z výsledků -slovo zcela vynechám
  • “Takto můžu najít celou frázi”

Evaluation of Robustness and Efficiency of Control Charts

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F17%3A10237948" target="_blank" >RIV/61989100:27360/17:10237948 - isvavai.cz</a>

  • Výsledek na webu

  • DOI - Digital Object Identifier

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Evaluation of Robustness and Efficiency of Control Charts

  • Popis výsledku v původním jazyce

    Control chart is the basic tool of the statistical process control (SPC). It aims to an early detection of errors in the process and thereby ensures compliance with the required level of stability. The statistical process control is an integral part of the production management necessary for achieving a high product quality. Just the quality of the product decides the customer satisfaction and thus the success of the whole company. Classical Shewhart control charts can be used only if there are met certain basic assumptions. These assumptions include, for example, data normality, their independence and constant mean and variance. In practice, such as the metallurgical industry, those assumptions about the data are not necessarily always met. In the case that these conditions are not met, there may be used non-parametric and robust control charts. This paper presents some of these non-traditional control charts. This article aims to define the difference between robust and non-parametric methods. Another aim of this article is to present the possibility of evaluating the robustness, and the evaluation of effectiveness based of individual control charts. Particular evaluation methods are complemented by practical examples from the metallurgical process. Conclusion of the article includes comparisons of the used control charts, both in terms of robustness and effectiveness. During preparation of this article accessible pieces of knowledge on the issue were compared, including the use of SPC in the metallurgical industry. This article is the basis for further examination of the problem, including a more detailed processing of the software support.

  • Název v anglickém jazyce

    Evaluation of Robustness and Efficiency of Control Charts

  • Popis výsledku anglicky

    Control chart is the basic tool of the statistical process control (SPC). It aims to an early detection of errors in the process and thereby ensures compliance with the required level of stability. The statistical process control is an integral part of the production management necessary for achieving a high product quality. Just the quality of the product decides the customer satisfaction and thus the success of the whole company. Classical Shewhart control charts can be used only if there are met certain basic assumptions. These assumptions include, for example, data normality, their independence and constant mean and variance. In practice, such as the metallurgical industry, those assumptions about the data are not necessarily always met. In the case that these conditions are not met, there may be used non-parametric and robust control charts. This paper presents some of these non-traditional control charts. This article aims to define the difference between robust and non-parametric methods. Another aim of this article is to present the possibility of evaluating the robustness, and the evaluation of effectiveness based of individual control charts. Particular evaluation methods are complemented by practical examples from the metallurgical process. Conclusion of the article includes comparisons of the used control charts, both in terms of robustness and effectiveness. During preparation of this article accessible pieces of knowledge on the issue were compared, including the use of SPC in the metallurgical industry. This article is the basis for further examination of the problem, including a more detailed processing of the software support.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    20501 - Materials engineering

Návaznosti výsledku

  • Projekt

  • Návaznosti

    S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2017

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    METAL 2017: conference proceedings : 26th International Conference on Metallurgy and Materials : (reviewed version) : May 24th-26th 2017, Hotel Voroněž I, Brno, Czech Republic, EU

  • ISBN

    978-80-87294-79-6

  • ISSN

  • e-ISSN

    neuvedeno

  • Počet stran výsledku

    6

  • Strana od-do

    2304-2309

  • Název nakladatele

    Tanger

  • Místo vydání

    Ostrava

  • Místo konání akce

    Brno

  • Datum konání akce

    24. 5. 2017

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku