Abstract
Along with the advent of mass production comes the problem of monitoring and maintaining the quality of the product, which stressed the need for the application of selected statistical and mathematical methods in the control process. The main objective of applying the methods of statistical control is continuous quality improvement through permanent monitoring of the process in order to discover the causes of errors. Shewart charts are the most popular method of statistical process control, which performs separation of controlled and uncontrolled variations along with detection of increased variations. This paper presents the example of Shewart mean control chart with application in managing industrial process.
Highlights
Along with the advent of mass production comes the problem of monitoring and maintaining the quality of the product, which stressed the need for the application of selected statistical and mathematical methods in the control process
This paper presents the example of Shewart mean control chart with application in managing industrial process
A Comparison of Shewhart Individuals Control Charts Based on Normal, Non-parametric, and Extreme-value Theory
Summary
Primena kontrolnih karata uglavnom se odnosi na otkrivanje neizvesnosti u samom procesu koji je predmet kontrole, ali i na posmatranje promena koje su neočekivano nastale. Na grafikonu Ševartove kontrolne karte na horizontalnoj osi se prikazuje vreme, a na vertikalnoj karakteristike dobijene procesom kontrole (pojedinačna merenja ili statistika, kao što je aritmetička sredina ili interval varijacije). Kontrolne granice omogućavaju laku proveru stabilnosti procesa, odnosno ukazuju na prisustvo posebnih uzroka. Horizontalna osa na Ševartovoj karti prikazuje podgrupe uzoraka, dok centralna linija ukazuje na prosek (očekivanu vrednost) ukupne statistike u slučaju kada se vrši kontrola procesa. Kontrolne granice su takođe određene veličinom uzorka podgrupe, pošto je standardna greška ukupne statistike funkcija veličine uzorka. U slučaju da se vrednosti određene na osnovu podataka iz uzorka nalaze između donje i gornje kontrolne granice, smatra se da je proizvodni proces u okviru kontrole. Tačka van kontrolne granice ukazuje na prisustvo posebnih uzroka varijacija, kada se smatra da je proizvodnja izvan kontrole. Kada grafikon ukaže na prisustvo posebnih uzroka, potrebno je preduzeti dodatne aktivnosti kako bi se problem otkrio i eliminisao
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