Among service industries of knowledge based economic era, the roles of educational service field are becoming more important and standard of educational service makes a direct effect on economic development and social growth. Therefore, accurate measurement of service quality is the most important assignment and the measurement of the service quality remains difficult assignment. So, this researcher classified quality attributes applying weighted value and found potential satisfaction level(PSL) and potential customer demand improvement index(PCDI) for trainees participating in national manpower business so as to suggest measurement of service quality and easiness of use and then, calculated satisfaction position and opportunity cost by quality factor with Taguchi’s loss fraction. And, improvable satisfaction level was measured, opportunity cost by degree of customer dissatisfaction was quantitatively measured, and a model that can indicate with economic factors was suggested. In addition, methodology of measuring quality cost that can be reduced by quality improvement and direction of strategic decision-making for deciding items to be improved preferentially were suggested with qualitative index that can indicate the degree of customers’ dissatisfaction by loss.

Process quality control, which prevents problems and risks that may occur in products and processes, has been recognized as an important issue, and SPC techniques have been used for this purpose. Process Capability Index (PCI) is useful Statistical Process Control (SPC) tool that is measure of process diagnostic and assessment tools widely use in industrial field. It has advantage of easy to calculate and easy to use in the field. Cp and Cpk are traditional PCIs. These traditional Cp and Cpk were used only as a measure of process capability, taking into account the quality variance or the bias of the process mean. These are not given information about the characteristic value does not match the target value of the process and this has the disadvantage that it is difficult to assess the economic losses that may arise in the enterprise. Studies of this process capability index by many scholars actively for supplement of its disadvantage. These studies to evaluate the capability of situation of various field has presented a new process capability index. Cpm is considers both the process variation and the process deviation from target value. And Cpm + is considers economic loss for the process deviation from target value. In this paper we developed an improved Expected Loss Capability Index using Reflected Normal Loss Function of Spring. This has the advantage that it is easy to realistically reflect the loss when the specification is asymmetric around the target value. And check the correlation between existing traditional process capability index (Cpk) and new one. Finally, we propose the criteria for classification about developed process capability index.

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally x-R control chart or x-s control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

Control chart is representative tools of statistical process control (SPC). It is a graph that plotting the characteristic values from the process . It has two steps (or Phase). First step is a procedure for finding a process parameters. It is called PhaseⅠ. This step is to find the process parameters by using data obtained from in-controlled process. It is a step that the standard value was not determined. Another step is monitoring process by already known process parameters from PhaseⅠ. It is called Phase Ⅱ. These control chart is the process quality characteristic value for management, which is plotted dot whether the existence within the control limit or not. But, this is not given information about the economic loss that occurs when a product characteristic value does not match the target value. In order to meet the customer needs, company not only consider stability of the process variation but also produce the product that is meet the target value. Taguchi’s quadratic loss function is include information about economic loss that occurred by the mismatch the target value. However, Taguchi’s quadratic loss function is very simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. Also, it can be well explained by only on condition that the normal process. Spiring proposed an alternative loss function that called reflected normal loss function (RNLF). In this paper, we design a new control chart for overcome these disadvantage by using the Spiring’s RNLF. And we demonstrate effectiveness of new control chart by comparing its average run length (ARL) with x-R control chart and expected loss control chart (ELCC).

Control chart is a graph of plotting dot in the process characteristic values. It is a statistical technique that can be known whether or not the in-control state in this step. In many companies have use as a statistical process control(SPC) tool. Control chart is the management process quality characteristic value, which is plotted dot is whether the existence within the control limits. But, this is not given information about the economic loss that occurs when a product is produced characteristic value does not match the target value of the process. In that sence, expected loss control chart(EL control chart) is very effective process control tool. Because it is a process control chart in consideration to economic loss. The EL control chart is using the quadratic loss function of Taguchi. However, Taguchi’s quadratic loss function is simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. In this paper, we design a new control chart using the reflected normal loss function(RNLF). And we demonstrate its effectiveness by using the control chart performance comparison of EL control chart.

Process Capability Index (PCI) is useful Statistical Process Control (SPC) tool that is measure of process diagnostic and assessment tools widely use in industrial field. It has advantage of easy to calculate and easy to use in the field. Cp and Cpk are traditional PCIs. These are only considers of process variation. These are not given information about the characteristic value does not match the target value of the process. Studies of this process capability index by many scholars actively for supplement of its disadvantage. These studies to evaluate the capability of situation of various field has presented a new process capability index. Cpm is considers both the process variation and the process deviation from target value. And Cpm + is considers economic loss for the process deviation from target value. In this paper development of new process capability index that is Taguchi's quadratic loss function by applying the expected loss. And check the correlation between existing traditional process capability index (Cpk) and new one. Finally, we propose the criteria for classification about developed process capability index.

Process Capability Index(PCI) is useful Statistical Process Control(SPC) tool that is measure of process diagnostic and assessment tools widely use in industrial field. It has advantage of easy to calculate and easy to use in the field. Cp and Cpk are traditional PCIs. These are only considers of process variation. These are not given information about the characteristic value does not match the target value of the process. Studies of this process capability index by many scholars actively for supplement of its disadvantage. These studies to evaluate the capability of situation of various field has presented a new process capability index. Cpm is considers both the process variation and the process deviation from target value. And Cpm+ is considers economic loss for the process deviation from target value. In this paper development of new process capability index that is Taguchi's quadratic loss function by applying the expected loss. And check the correlation between existing traditional process capability index(Cpk) and new one. Finally, we propose the criteria for classification about developed process capability index.

Control chart is representative tool of Statistical Process Control (SPC). But, it is not given information about the economic loss that occurs when a product is produced characteristic value does not match the target value of the process. In order to manage the process, we should consider not only stability of the variation also produce products with a high degree of matching the target value that is most ideal quality characteristics. There is a need for process control in consideration of economic loss. In this paper, we design a new control chart using the quadratic loss function of Taguchi. And we demonstrate effectiveness of new control chart by compare its ARL with   control chart.

Control chart is a graph of plotting dot about the process characteristic values. It is a statistical technique that can be known whether or not the in-control state in this step. In many companies have use as a statistical process control(SPC) tool. Control chart is the management process quality characteristic value, which is plotted dot is whether the existence within the control limits. This is not given information about the economic loss that occurs when a product is produced characteristic value does not match the target value of the process. In order to manage the process, we should consider not only stability of the variation also produce products with a high degree of matching the target value that is most ideal quality characteristics. There is a need for process control in consideration of economic loss. In this paper, we design a new control chart using the quadratic loss function of Taguchi. Use the control chart performance comparison of x-R, which is a traditional control chart, we demonstrate its effectiveness.

The traditional process capability indices Cp, Cpk, Cpm, Cpm+ have been used to characterize process performance on the basis of univariate quality characteristics. Cp, Cpk consider the process variation, Cpm considers both the process variation and the p

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for multiple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index MCpm using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other.

Among the costs composing the life-cycle cost of nuclear containment, the expected loss due to leakage of radioactive material is usually exorbitant, and it takes large amount in the evaluation of life-cycle cost. This study presents a process to determine optimal target reliability for nuclear containments, mainly focuses on its expected loss. It is estimated considering the surrounding environment of nuclear containment. Target reliability of containments having different lifespan can be determined by revising the expected loss estimated from the 20, 40 and 60 years of operation.