With the advent of lean-six sigma era, an extensive use of analytic tools such as control charts is required in the field of manufacturing. In relation to statistical quality control (SQC) or process control (SPC), the Korean standards have undergone a meaningful change. In this study, the theoretic backgrounds for evaluating the control limits in connection with the variable control charts are examined in view of better understanding the related constants and coefficients. This paper is intended to help the quality control practitioners understand the mathematical backgrounds by comparing related quality control constants and also to encourage them to make use of and to take the advantage of the variable control charts which are very useful for implementing the concept of lean-six sigma in many industrial sites.

In this paper, we have considered the modeling and analyses of categorical data. We modeled binary data with categorical predictors, using logistic regression to develop a statistical method. We found that ANOVA-type analyses often performed unsatisfactory, even when using arcsine-square-root transformations. We concluded that such methods are not appropriate, especially in cases where the fractions were close to 0 or 1. The logistic transformation of fraction data could be a promising alternative, but it is not desirable in the statistical sense. The major purpose of this paper is to demonstrate that logistic regression with an ANOVA-model like parameterization aids our understanding and provides a somewhat different, but sound, statistical background. We examined a simple real-world example to show that we can efficiently test the significance of regression parameters, look for interactions, estimate confidence intervals, and calculate the difference between the mean values of the referent and experimental subgroups. This paper demonstrates that precise confidence interval estimates can be obtained using the proposed ANOVA-model like approach. The method discussed here can be extended to any type of fraction data analysis, particularly for experimental design.

An estimation of indices for potential process capability (Cpk) and/or overall process performance (Ppk) is considered in order to gain insight into the statistical process control. The similarity and the difference of the two indices are discussed in some detail to clarify the meaning and usage of the two indices. It is demonstrated that the short term variance can be estimated within the framework of analysis of variance (ANOVA). Theoretic background is examined and followed by a simple numerical example, with a view to the implementation of the concept in the industrial fields.

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.

An attempt is given to the problem of analyzing the two-way binary attribute data using the logistic regression model in order to find a sound statistical methodology. It is demonstrated that the analysis of variance (ANOVA) may not be good enough, especi

In this paper, an evaluation of a product replacement ratio of irreparable items to the normally working ones is performed with a view to a warranty analysis. It is demonstrated that the replacement ratio during the warranty period can be estimated from t

In this paper, an attempt is given to the problem of short-term forecasting of domestic demand for mineral water in Korean market. The seasonal regression models are taken into consideration in model building and in making the forecast. As it turned out, the model performance is satisfactory for the use of production planning. A modeling procedure as well as a few fitted models are presented in some detail in order to discuss on the modeling procedure and forecasting performance.

In this paper, an analysis of two-way binary attribute data is performed using the logistic regression model in order to find a sound statistical methodology. It is demonstrated that the ANOVA may not be enough, especially for the case that the proportion is very low or high. The logistic transformation of proportion data could be a help, but not sound in the statistical sense. The adoption of generalized least squares(GLS) method entails much to estimate the variance-covariance matrix. On the other hand, the logistic regression methodology provides sound statistical background in estimating model parameters and related confidence intervals. The efficiencies of estimates are ensured with a simulated data with a view to demonstrate the usefulness of the methodology.

In this study, a reliability analysis method is discussed for the evaluation of the withdrawal ratio of non-repairable items to the normally working items of a controller product model. Although the analysis method is rather straightforward, one can estimate the probability of withdrawal and present the management a useful information on the appropriateness of the warranty period, exploiting the collected data, which is commonplace in the industrial site. For the methodology is to be refined, more systematic collection of data and adoption of more sophisticated analysis method are yet to be desired.

For the last two decades, remanufacturing has drawn attention for its expected economic and environmental benefits and becomes a matter of strategic importance not only for manufacturers, but also for nations, as can be seen in such advanced countries as the US and some other European countries. In light of the experiences of those countries, it is highly recommended that Korean manufacturing companies as well as the government take into consideration the remanufacturing of their products, with a view to making contribution to global society by reducing the carbon-foot-prints of their products. This paper shows that the implications of remanufacturing the laser multi-function peripherals(MFPs) can provide with a good start in discussing and implementing the concept of remanufacturing a variety of different industrial products.

전 세계적으로 대량생산, 대량소비의 결과로 발생된 폐기물의 감량과 재활용을 확대하려는 법적 규제가 강화되고 있다. 그와 동시에 제조업도 환경 친화적으로 변모하고 있으며 이와 병행하여 공급사슬도 자원 순환형으로 변화하고 있다. 공급사슬의 분석, 설계, 운영, 통제 등의 경영관 리 기법도 변화를 거듭하고 있는데 과거의 환경산업이나 재제조산업은 정부의 규제법규를 준수하는 범위 내에서 비용 최소화의 목적으로 진행되었으나 현재에는 적극적으로 사용 후 회수된 재활 용 제품의 부가가치를 회복시켜 수익을 창조하는 수익사업으로 여겨지고 있다. 본 논문에서는 EU 국가와 미국 등 선진국에서 역공급사슬 개념의 형성과정과 순환형 공급사슬이 되기까지의 변천과정 또한 그 과정에서 발생된 중요한 개념들을 살펴보고 이와 관련하여 경영, 경제, 산업공학과 관련한 선진국에서의 연구 분야에 대하여 조사하여 앞으로의 연구 방향을 모색해 보고자한다.

In this paper, an effort is exerted to the problem of short-term domestic demand forecasting of mineral water. The seasonal ARIMA models are considered in model building and in making the forecast. As it turned out, the model fits well into the given time-series data in so far as modeling procedures are relevant. A fitted model as well as modeling procedure is presented in some detail.