Recently, the production cycle in manufacturing process has been getting shorter and different types of product have been produced in the same process line. In this case, the control chart using coefficient of variation would be applicable to the process. The theory that random variables are located in the three times distance of the deviation from mean value is applicable to the control chart that monitor the process in the manufacturing line, when the data of process are changed by the type of normal distribution. It is possible to apply to the control chart of coefficient of variation too.  ,  estimates that taken in the coefficient of variation have just used all of the data, but the upper control limit, center line and lower control limit have been settled by the effect of abnormal values, so this control chart could be in trouble of detection ability of the assignable value. The purpose of this study was to present the robust control chart than coefficient of variation control chart in the normal process. To perform this research, the location parameter, xα, sα were used. The robust control chart was named Tim-CV control chart. The result of simulation were summarized as follows; First, P values, the probability to get away from control limit, in Trim-CV control chart were larger than CV control chart in the normal process. Second, ARL values, average run length, in Trim-CV control chart were smaller than CV control chart in the normal process. Particularly, the difference of performance of two control charts was so sure when the change of the process was getting to bigger. Therefore, the Trim-CV control chart proposed in this paper would be more efficient tool than CV control chart in small quantity batch production.

Control charts are generally used for process control, but the role of traditional control charts have been limited in case of a contaminated process. Traditional x control charts have not been activated well for such a problem because of trying to control processes as center line and control limits changed by the contaminated value. This paper is to propose robust x control charts which is considering a location parameter in order to respond to contaminated process. In this paper, we consider x, that is trimmed rate; typically ten percent rate is used. By comparing with p, ARL value, the responding results are decided. The comparison resultant results of proposed two control charts are shown and are well contrasted.

When it comes to designing a product or a process, the robust parameter design (RPD) methodology devised by Taguchi is recognized as a way to produce products or processes with less variability, while the specifications of products or processes are met, so that the ratio of nonconforming products can be as minimized as possible. Nevertheless, as a matter of fact, there have been many pros and cons concerning the RPD method, mainly because of the use of signal to noise ratio as the measure of quality characteristic. Meanwhile, the variability analysis method has been highly recommended as an alternative of the RPD in the literature. In this paper, it is demonstrated that RPD can also be implemented within the framework of the variability analysis, which is sounder in the statistical sense. In light of an example of RPD approach, the modeling and estimation procedure is discussed in some detail with a view to a comparison of the two methods.

The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this study, First, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Second, to solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics. Third, this paper propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision of characteristic. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision of characteristic.