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Quality control charts under random fuzzy measurements

Includes bibliographical references. .

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Bibliographic Details
Main Author: Thoutou, Sayi Mbani
Other Authors: Guo, Renkuan
Format: Thesis
Language:English
Published: Department of Statistical Sciences 2016
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access_status_str Open Access
author Thoutou, Sayi Mbani
author2 Guo, Renkuan
author_browse Guo, Renkuan
Thoutou, Sayi Mbani
author_facet Guo, Renkuan
Thoutou, Sayi Mbani
author_sort Thoutou, Sayi Mbani
collection Thesis
description Includes bibliographical references. .
format Thesis
id oai:open.uct.ac.za:11427/19140
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:32:45.765Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2016
publishDateRange 2016
publishDateSort 2016
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:11427/19140 Quality control charts under random fuzzy measurements Thoutou, Sayi Mbani Guo, Renkuan Statistical Sciences Includes bibliographical references. . We consider statistical process control charts as tools that statistical process control utilizes for monitoring changes; identifying process variations and their causes in industrial processes (manufacturing processes) and which help manufacturers to take the appropriate action, rectify problems or improve manufacturing processes so as to produce good quality products. As an essential tool, researchers have always paid attention to the development of process control charts. Also, the sample sizes required for establishing control charts are often under discussion depending on the field of study. Of late, the problem of Fuzziness and Randomness often brought into modern manufacturing processes by the shortening product life cycles and diversification (in product designs, raw material supply etc) has compelled researchers to invoke quality control methodologies in their search for high customer satisfaction and better market shares (Guo et al 2006). We herein focus our attention on small sample sizes and focus on the development of quality control charts in terms of the Economic Design of Quality Control Charts; based on credibility measure theory under Random Fuzzy Measurements and Small Sample Asymptotic Distribution Theory. Economic process data will be collected from the study of Duncan (1956) in terms of these new developments as an illustrative example. or/Producer, otherwise they are undertaken with respect to the market as a whole. The techniques used for tackling the complex issues are diverse and wide-ranging as ascertained from the existing literature on the subject. The global ideology focuses on combining two streams of thought: the production optimisation and equilibrium techniques of the old monopolistic, cost-saving industry and; the new dynamic profit-maximising and risk-mitigating competitive industry. Financial engineering in a new and poorly understood market for electrical power must now take place in conjunction with - yet also constrained by - the physical production and distribution of the commodity. 2016-04-22T13:37:38Z 2016-04-22T13:37:38Z 2007 Master Thesis Masters MSc http://hdl.handle.net/11427/19140 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town
spellingShingle Statistical Sciences
Thoutou, Sayi Mbani
Quality control charts under random fuzzy measurements
thesis_degree_str Master's
title Quality control charts under random fuzzy measurements
title_full Quality control charts under random fuzzy measurements
title_fullStr Quality control charts under random fuzzy measurements
title_full_unstemmed Quality control charts under random fuzzy measurements
title_short Quality control charts under random fuzzy measurements
title_sort quality control charts under random fuzzy measurements
topic Statistical Sciences
url http://hdl.handle.net/11427/19140
work_keys_str_mv AT thoutousayimbani qualitycontrolchartsunderrandomfuzzymeasurements