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Interval-valued Uncertainty Capability Indices with South African Industrial Applications

Includes bibliographical references.

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Bibliographic Details
Main Author: Gyekye, Kwame Boakye
Other Authors: Guo, Renkuan
Format: Thesis
Language:English
Published: Department of Statistical Sciences 2015
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access_status_str Open Access
author Gyekye, Kwame Boakye
author2 Guo, Renkuan
author_browse Guo, Renkuan
Gyekye, Kwame Boakye
author_facet Guo, Renkuan
Gyekye, Kwame Boakye
author_sort Gyekye, Kwame Boakye
collection Thesis
description Includes bibliographical references.
format Thesis
id oai:open.uct.ac.za:11427/12947
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:31:54.917Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2015
publishDateRange 2015
publishDateSort 2015
publisher Department of Statistical Sciences
publisherStr Department of Statistical Sciences
record_format dspace
source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/12947 Interval-valued Uncertainty Capability Indices with South African Industrial Applications Gyekye, Kwame Boakye Guo, Renkuan Statistical Sciences Includes bibliographical references. Since the advent of statistical quality control and process capability analysis, its study and application has gained tremendous attention both in academia and industry. This attention is due to its ability to describe the capability of a complex process adequately, simply (i.e. using a unitless index) and also in some instances to compare different manufacturing processes. However, the application of statistical quality control has come under intense criticism, notably in one car manufacturing industry where the actual number of non-conforming units considerably exceeded expectation, although probabilistic control measures were in place. This failure led to a large recall of their vehicles and also left a dent on the image of the company. One of the reasons for this unfortunate instance is that in classical quality control measures, human judgement is ignored and since in process engineering there is considerable expert intuition in decision making, this element cannot be undermined. Hence the research study applies the uncertainty theory proposed by Baoding Liu (2007) to enable us to incorporate human judgement into process capability analysis. The major findings of the thesis is that the uncertain process capability indices under an uncertainty environment are interval-valued and their relevant characteristics. The study further developed the "sampling" uncertainty distributions and thus the "sampling" impacts on the newly defined uncertain process capability indices under Liu's uncertain normal distribution assumptions. In order to reach the main purpose of the thesis, a thoroughgoing literature review on probabilistic process capability indices is necessary. 2015-05-28T04:11:46Z 2015-05-28T04:11:46Z 2014 Master Thesis Masters MSc http://hdl.handle.net/11427/12947 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town
spellingShingle Statistical Sciences
Gyekye, Kwame Boakye
Interval-valued Uncertainty Capability Indices with South African Industrial Applications
thesis_degree_str Master's
title Interval-valued Uncertainty Capability Indices with South African Industrial Applications
title_full Interval-valued Uncertainty Capability Indices with South African Industrial Applications
title_fullStr Interval-valued Uncertainty Capability Indices with South African Industrial Applications
title_full_unstemmed Interval-valued Uncertainty Capability Indices with South African Industrial Applications
title_short Interval-valued Uncertainty Capability Indices with South African Industrial Applications
title_sort interval valued uncertainty capability indices with south african industrial applications
topic Statistical Sciences
url http://hdl.handle.net/11427/12947
work_keys_str_mv AT gyekyekwameboakye intervalvalueduncertaintycapabilityindiceswithsouthafricanindustrialapplications