Masters Degrees (Statistics and Actuarial Science)
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Browsing Masters Degrees (Statistics and Actuarial Science) by Author "Contardo, Ivona"
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- ItemA report on the development of the control chart(Stellenbosch : Stellenbosch University, 2007-03) Contardo, Ivona; Van Deventer, P. J. U.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Statistics and Actuarial Science.ENGLISH ABSTRACT: The goal of quality control as stated by Feigenbaum (1961) is to provide a product or service into which quality Is designed, built, marketed and maintained at the lowest economical cost which simultaneously allows for full customer satisfaction. Statistical process control techniques, specifically control charts, are widely employed to achieve this goal. Walter A. Shewhart developed the control chart in 1924 in order to differentiate between random causes of variation and assignable causes of variation. In situations where assignable causes occur, a corrective action should be taken to return the process to the in-control state. A process should be able to operate in the in-control state for a relatively long period before an assignable cause will come about. The heuristic design of Shewhart however, was not guaranteed to be economically optimal. In 1956 Duncan proposed that the design parameters of control charts should be chosen in a manner that minimises the economic costs associated. Since then various developments in the economic design of control charts have taken place. Some research has been done to increase the power of the control chart and consequently the statistical design of control charts has been presented. The statistical design of control charts is designed in a manner as to place constraints on the control chart. Saniga in ( 1989) proposed to combine the economic and statistical designs in the economic statistical design in an attempt to minimise the economic costs of the control charts under some statistical constraints. Results obtained by various authors show that the economic statistical designs perform best in the sense of achieving the desired statistical properties while simultaneously minimising the associated costs. Various cost models have been developed under different distributions and the expressions for the expected cycle time and expected cycle cost have been derived. In 2005 Yang and Rahim developed a cost model for the economic statistical design of control charts for a process with multiple quality characteristics under a Weibull shock model. The development of this model will be discussed in detail.