Assignment (MSc)--Stellenbosch University, 2004. / ENGLISH ABSTRACT: The design of control charts refers to the selection of the parameters implied, including the
sample size n, control limit width parameter k, and the sampling interval h. The design of the
X -control chart that is based on economic as well as statistical considerations is presently one of
the more popular subjects of research. Two assumptions are considered in the development and
use of the economic or economic statistical models. These assumptions are potentially critical. It
is assumed that the time between process shifts can be modelled by means of the exponential
distribution. It is further assumed that there is only one assignable cause. Based on these
assumptions, economic or economic statistical models are derived using a total cost function per
unit time as proposed by a unified approach of the Lorenzen and Vance model (1986). In this
approach the relationship between the three control chart parameters as well as the three types of
costs are expressed in the total cost function. The optimal parameters are usually obtained by the
minimization of the expected total cost per unit time. Nevertheless, few practitioners have tried
to optimize the design of their X -control charts. One reason for this is that the cost models and
their associated optimization techniques are often too complex and difficult for practitioners to
understand and apply. However, a user-friendly Excel program has been developed in this paper
and the numerical examples illustrated are executed on this program. The optimization procedure
is easy-to-use, easy-to-understand, and easy-to-access. Moreover, the proposed procedure also
obtains exact optimal design values in contrast to the approximate designs developed by Duncan
(1956) and other subsequent researchers.
Numerical examples are presented of both the economic and the economic statistical designs of
the X -control chart in order to illustrate the working of the proposed Excel optimal procedure.
Based on the Excel optimization procedure, the results of the economic statistical design are
compared to those of a pure economic model. It is shown that the economic statistical designs
lead to wider control limits and smaller sampling intervals than the economic designs.
Furthermore, even if they are more costly than the economic design they do guarantee output of
better quality, while keeping the number of false alarm searches at a minimum. It also leads to
low process variability. These properties are the direct result of the requirement that the
economic statistical design must assure a satisfactory statistical performance.
Additionally, extensive sensitivity studies are performed on the economic and economic
statistical designs to investigate the effect of the input parameters and the effects of varying the bounds on, a, 1-f3 , the average time-to-signal, ATS as well as the expected shift size t5 on
the minimum expected cost loss as well as the three control chart decision variables. The
analyses show that cost is relatively insensitive to improvement in the type I and type II error
rates, but highly sensitive to changes in smaller bounds on ATS as well as extremely sensitive
for smaller shift levels, t5 .
Note: expressions like economic design, economic statistical design, loss cost and assignable
cause may seen linguistically and syntactically strange, but are borrowed from and used
according the known literature on the subject. / AFRIKAANSE OPSOMMING: Die ontwerp van kontrolekaarte verwys na die seleksie van die parameters geïmpliseer,
insluitende die steekproefgrootte n , kontrole limiete interval parameter k , en die
steekproefmterval h. Die ontwerp van die X -kontrolekaart, gebaseer op ekonomiese sowel as
statistiese oorwegings, is tans een van die meer populêre onderwerpe van navorsing. Twee
aannames word in ag geneem in die ontwikkeling en gebruik van die ekonomiese en ekonomies
statistiese modelle. Hierdie aannames is potensieel krities. Dit word aanvaar dat die tyd tussen
prosesverskuiwings deur die eksponensiaalverdeling gemodelleer kan word. Daar word ook
verder aangeneem dat daar slegs een oorsaak kan wees vir 'n verskuiwing, of te wel 'n
aanwysbare oorsaak (assignable cause). Gebaseer op hierdie aannames word ekonomies en
ekonomies statistiese modelle afgelei deur gebruik te maak van 'n totale kostefunksie per
tydseenheid soos voorgestel deur deur 'n verenigende (unified) benadering van die Lorenzen en
Vance-model (1986). In hierdie benadering word die verband tussen die drie kontrole
parameters sowel as die drie tipes koste in die totale kostefunksie uiteengesit. Die optimale
parameters word gewoonlik gevind deur die minirnering van die verwagte totale koste per
tydseenheid. Desnieteenstaande het slegs 'n minderheid van praktisyns tot nou toe probeer om
die ontwerp van hulle X -kontrolekaarte te optimeer. Een rede hiervoor is dat die kosternodelle
en hulle geassosieerde optimeringstegnieke té kompleks en moeilik is vir die praktisyns om te
verstaan en toe te pas. 'n Gebruikersvriendelike Excelprogram is egter hier ontwikkel en die
numeriese voorbeelde wat vir illustrasie doeleindes getoon word, is op hierdie program
uitgevoer. Die optimeringsprosedure is maklik om te gebruik, maklik om te verstaan en die
sagteware is geredelik beskikbaar. Wat meer is, is dat die voorgestelde prosedure eksakte
optimale ontwerp waardes bereken in teenstelling tot die benaderde ontwerpe van Duncan (1956)
en navorsers na hom.
Numeriese voorbeelde word verskaf van beide die ekonomiese en ekonomies statistiese
ontwerpe vir die X -kontrolekaart om die werking van die voorgestelde Excel optimale
prosedure te illustreer. Die resultate van die ekonomies statistiese ontwerp word vergelyk met
dié van die suiwer ekomomiese model met behulp van die Excel optimerings-prosedure. Daar
word aangetoon dat die ekonomiese statistiese ontwerpe tot wyer kontrole limiete en kleiner
steekproefmtervalle lei as die ekonomiese ontwerpe. Al lei die ekonomies statistiese ontwerp tot
ietwat hoër koste as die ekonomiese ontwerpe se oplossings, waarborg dit beter kwaliteit terwyl
dit die aantal vals seine tot 'n minimum beperk. Hierbenewens lei dit ook tot kleiner prosesvartasie. Hierdie eienskappe is die direkte resultaat van die vereiste dat die ekonomies
statistiese ontwerp aan sekere statistiese vereistes moet voldoen.
Verder is uitgebreide sensitiwiteitsondersoeke op die ekonomies en ekonomies statistiese
ontwerpe gedoen om die effek van die inset parameters sowel as van variërende grense op a,
1- f3 , die gemiddelde tyd-tot-sein, ATS sowel as die verskuiwingsgrootte 8 op die minimum
verwagte kosteverlies sowel as die drie kontrolekaart besluitnemingsveranderlikes te bepaal. Die
analises toon dat die totale koste relatief onsensitief is tot verbeterings in die tipe I en die tipe II
fout koerse, maar dat dit hoogs sensitief is vir wysigings in die onderste grens op ATS sowel as
besonder sensitief vir klein verskuiwingsvlakke, 8.
Let op: Die uitdrukkings ekonomiese ontwerp (economic design), ekonomies statistiese ontwerp
(economic statistical design), verlies kostefunksie (loss cost function) en aanwysbare oorsaak
(assignable cause) mag taalkundig en sintakties vreemd voordoen, maar is geleen uit, en word so
gebruik in die bekende literatuur oor hierdie onderwerp.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/49865 |
| Date | 12 1900 |
| Creators | Ghebretensae Manna, Zerai |
| Contributors | Van Deventer, P. J. U., Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Statistics and Actuarial Science. |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | 82 p. |
| Rights | Stellenbosch University |
Page generated in 0.0031 seconds