• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.44-52
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• 2000

In this paper we apply VSS X chart to the case when two assignable causes effect the process mean shift. We compare the case when two compound assignable causes effect the process mean with another one which effects individually. For the practical use of VSS $\bar{X}$ chart we propose the sample size which minimizes the average number of samples until the signal is given in out-of-control state.

• Journal of Korean Society for Quality Management
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• v.37 no.1
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• pp.29-39
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• 2009

This article investigates economic-statistical design of VSSI(variable sampling size and interval) cause-selecting charts considering two assignable causes. We consider a process which is composed of two dependent sub-processes. In each sub-process, two kinds of assignable cause may exist. We propose a procedure for designing VSSI cause-selecting charts, based on Lorenzen and Vance model. Computational experiments show that the VSSI cause-selecting chart is superior to the FSSI cause-selecting chart in the economic-statistical characteristics, even under two assignable causes.

• International Journal of Quality Innovation
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• v.2 no.1
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• pp.69-86
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• 2001

The economic design of control charts has been researched for over four decades since Duncan proposed the concept in 1956. Few studies, however, have focused attention on the economic design of a moving average (MA) control chart. An MA control chart is more effective than the Shewhart chart in detecting small process shifts [9]. This paper provides an economic model for determining the optimal parameters of an MA control chart with multiple assignable causes and two failures in the production process. These parameters consist of the sample size, the spread of the control limit and the sampling interval. A numerical example is shown and the sensitivity analysis shows that the magnitude of shift, rate of occurrence of assignable causes and increasing cost when the process is out of control have a more significant effect on the loss cost, meaning that one should more carefully estimate these values when conducting an economic analysis.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.156-168
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• 2004

This research investigates the statistical efficiency of variable sampling size & sampling interval(VSSI) $\bar{X}$ charts under two assignable causes. Algorithms for calculating the average run length(ARL) and average time to signal(ATS) of the VSSI $\bar{X}$ chart are proposed by employing Markov chain method. States of the process are defined according to the process characteristics after the occurrence of an assignable cause. Transition probabilities are carefully derived from the state definition. Statistical properties of the proposed chart are also investigated. A simple procedure for designing the proposed chart is presented based on the properties. Extensive sensitivity analyses show that the VSSI $\bar{X}$ chart is superior to the VSS or VSI $\bar{X}$ chart as well as to the Shewhart $\bar{X}$ chart in statistical sense, even tinder two assignable causes.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.549-555
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• 2009

The research proposes two calculation methods for estimating the overall, within and between standard deviation of population. These standard deviations can be used to evaluate the process capability and performance indexes. The guidelines for using $C_{PK}$ and $P_{PK}$ according to the pattern of common and assignable causes are presented.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.87-98
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• 2005

This research investigates economic-statistical characteristics of variable sampling size and interval (VSSI)$\bar{X}$charts under two assignable causes. A Markov chain approach is employed in order to calculate average run length (ARL) and average time to signal (ATS). Six transient states are derived by carefully defining the state. A steady state cost rate function is constructed based on Lorenzen and Vance(1986) model. The cost rate function is optimized with respect to six design parameters for designing the VSSI $\bar{X}$ charts. Computational experiments show that the VSSI $\bar{X}$ chart is superior to the Shewhart $\bar{X}$ chart in the economic-statistical sense, even under two assignable causes. A comparative study shows that the cost rate may increase up to almost 30% by overlooking the second cause. Critical input parameters are also derived from a sensitivity study and a few guideline graphs are provided for determining the design parameters.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.507-512
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• 2004

This research investigates economic-statistical characteristics of variable sampling size & interval(VSSI) X charts under two assignable causes. We propose the procedure for designing VSSI X charts, based on Lorenzen and Vance model. Computational experiments show that the VSSI X chart Is superior to the Shewhart X chart in the economic-statistical sense, even under two assignable causes

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.64-69
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• 2004

This research investigates statistical characteristics of variable sampling size & interval(VSSI) X charts under two assignable causes. Algorithms for calculating the average run length(ARL) and average time to signal(ATS) of the VSSI X chart are proposed by employing Markov chain method. Extensive sensitivity analysis shows that the VSSI. X chart is superior to the VSS or VSI X chart as well as to the Shewhart X chart in statistical sense, even under two assignable causes.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.139-147
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• 2009

Control charts are used to distinguish between chance and assignable causes in the variability of quality characteristics. When a control chart signals that an assignable cause is present, process engineers must initiate a search for the assignable cause of the process disturbance. Identifying the time of a process change could lead to simplifying the search for the assignable cause and less process down time, as well as help to reduce the probability of incorrectly identifying the assignable cause. The change point estimation by likelihood theory and the built-in change point estimation in a control chart have been discussed until now. In this article, we discuss two kinds of process change point estimation when the CUSUM ($\bar{x}$, s) control chart for monitoring process mean and variance simultaneously is operated. Throughout some numerical experiments about the performance of the change point estimation, the change point estimation techniques in the CUSUM ($\bar{x}$, s) control chart are considered.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.1-8
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• 2002

At present, company has to produce a product that consumer like with a competitive price, a good quality, and a fitting time to supply. Process control and qualify control are very important to supply with a product uniformly and inexpensively In this paper, the characteristic of product quality is monitored by control chart during the machining process and construction of quality control cycle is considered to divide into two types in this case that different assignable causes lead to shifts having different magnitudes. Then we are intended to find a process shift magnitude which has economical quality cost policy and are considered to quality cost functions to find a process shift magnitude. Those costs are categorized into the well-known categories of prevention, appraisal, and internal failure and external failure. This paper ends with numerical examples that demonstrate the usefulness of the model.