Praćenje procesa kontrolnim kartama za varijable

master's thesis

• Title (english): Process monitoring with control charts for variables
• Author: Dominik Grizelj
• Mentor: Vedran Šimunović (mentor)
• Granter: University of Zagreb; Faculty of Mechanical Engineering and Naval Architecture; Zagreb
• Defense date and country: 2024-12-05, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Mechanical Engineering; Production Mechanical Engineering

Abstract

Kvaliteta proizvoda postala je ključni faktor u konkurentnosti i poslovnom uspjehu. Poboljšanje kvalitete uključuje smanjenje varijabilnosti procesa što rezultira smanjenjem kvarova i povećanjem stabilnosti. Statistička kontrola procesa (SPC) važan je alat za postizanje stabilnosti i poboljšanja kvalitete koristeći sedam osnovnih alata. Kontrolne karte pomažu u praćenju procesa i identifikaciji odstupanja. One omogućuju prepoznavanje problema u proizvodnji i pružaju informacije za poboljšanje procesa. Proces kontrole podrazumijeva dvije faze gdje se prva koristi za postavljanje stabilnih kontrolnih granica dok druga služi za praćenje procesa i otkrivanje manjih odstupanja. U radu je objašnjena statistička osnova 𝑥̅ i R univarijantne kontrolne karte te Hottelingova multivarijantna kontrolna karta. U diplomskom radu osmišljeni su različiti primjeri kojima je pokazano kako se analizom istih mjernih podataka mogu dobiti drugačija rješenja statističke kontrole ovisno dali se karakteristike kvalitete gledaju pojedinačno ili skupno. Kontrolne karte su izrađene u programu Excel.

Abstract (english)

The quality of a product has become a key factor in competitiveness and business success. Improving quality involves reducing process variability which results in fewer defects and increased stability. Statistical Process Control (SPC) is an important tool for achieving stability and improving quality using the seven basic tools. Control charts help monitor processes and identify deviations. They enable the recognition of problems in production and provide information for process improvement. The control process involves two phases. The first is used to set stable control limits, while the second is for monitoring the process and detecting minor deviations. This paper explains the statistical foundation of the x̅ and R univariate control charts, as well as the Hotteling multivariate control chart. Examples of these charts are provided to demonstrate how certain data can lead to different statistical control solutions depending on whether quality characteristics are viewed individually or collectively. The control charts are constructed and presented in Excel.

• Keywords: statistička kontrola procesa; 𝑥̅ i R kontrolne karte; Hottelingova multivarijantna kontrolna karta
• Keywords (english): statistical process control; 𝑥̅ i R control charts; Hotelling multivariate control chart
• Language: croatian
• URN:NBN: urn:nbn:hr:235:029318
• Study programme: Title: Mechanical Engineering; specializations in: Design, Process and Energy Engineering, Production Engineering, Engineering Modelling and Computer Simulation, Marine Engineering, Industrial Engineering and Management, Materials Engineering, Mechanics and Robotics, Autonomous Systems, Mechatronics and Robotics; Course: Materials Engineering; Study programme type: university; Study level: graduate; Academic / professional title: sveučilišni/a magistar/magistra inženjer/inženjerka strojarstva (sveučilišni/a magistar/magistra inženjer/inženjerka strojarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-12-04 10:14:10