• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.66-78
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• 2002

Process capability indices are being used as indicators for measurements of process capability for SPC of quality assurance system in industries. In view of the enhancement of customer satisfaction, process capability indices in which loss functions are used to deal with the economic loss In the processes deviated from the target, are in an adequate representation of the customer's perception of quality In this connection, the loss function has become increasingly important in quality assurance. Taguchi uses a modified form of the quadratic loss function to demonstrate the need to consider the proximity to the target while assessing its quality. But this traditional quadratic loss function is inadequate to assessing the quality and quality improvement since different processes have different sets of economic consequences on the manufacturing, Thereby, a flexible approach to the development of the loss function needs to be desired. In this paper, we introduce an easily understood loss function, based on reflection of probability density function of the normal distribution. That is, the Reflected Normal Loss function can be adapted to an asymmetric loss as well as to a symmetric loss around the target. We propose that, instead of the process variation, a new capability index, CpI using the Reflected Normal Loss Function that can accurately reflect the losses associated with the process and a new capability index CpI Is compared with the classical indices as $C_{p}$ , $C_{pk}$, $C_{pm}$ and $C_{pm}$ $^{+}$.>.+/./.

• Journal of Korean Society for Quality Management
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• v.48 no.4
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• pp.535-552
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• 2020

Purpose: The main theme of this study is to derive a specific quality loss function with multiple characteristics according to the same analytical structure as the single characteristic quality loss function of Taguchi. In other words, it presents an analytical framework for measuring quality costs that can be controlled in practice. Methods: This study followed the analytical methodology through geometric, linear algebraic, and statistical approaches Results: The function suggested by this study is as follows; $$L(x_1,x_2,{\cdots},x_t)={\sum\limits_{i=1}^{t}}k_i\{x_i+{\sum\limits_{j=1}^{t}}\({\rho}_{ij}{\frac{d_i}{d_j}}\)x_j\}x_i$$ Conclusion: This paper derived the quality loss function with multiple quality characteristics to expand the usefulness of the Taguchi quality loss function. The function derived in this paper would be more meaningful to estimate quality costs under the practical situation and general structure with multiple quality characteristics than the function by linear algebraic approach in response surface analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.145-153
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• 2018

Taguchi regarded the concept of quality as 'total loss to society due to fluctuations in quality characteristics from the time of supplied to the customer.' The loss function is a representative tool that can quantitatively convert the loss that occurs due to the deviation of the quality characteristic value from the target value. This has been utilized in various studies with the advantage that it can change the social loss caused by fluctuation of quality characteristics to economic cost. The loss function has also been used extensively in the study of producer specification limits. However, in previous studies, only the second order loss function of Taguchi is used. Therefore, various types of losses that can occur in the process can't be considered. In this study, we divide the types of losses that can occur in the process considering the first and second loss functions and the Spiring's reflected normal loss function, and perform total inspection before delivering the customer to determine the optimal producer specification limit that minimizes the total cost. Also, we will divide the quality policy for the products beyond the specification limits into two. In addition, we will show the illustration of expected loss cost change of each model according to the change of major condition such as customer specifications and maximum loss cost.

• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.443-456
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• 2013

Purpose: Recently, many quality issues are aroused in military forces, such as failures in K-series weapons, combat boots defects and 40mm ammunition explosion accident. To address these problems, this paper suggests to use so called, Defense Quality Score, which is based on Taguchi loss function and developed in this research. Methods: Current defense specification states only the minimum requirement to produce the military supplies. Therefore, it is not easy to indue the continuous quality improvement of the supplies. This research suggests to use the defense quality score which measures the current status of defense supplies'quality characteristics. Results: We applied the defense quality score concept into the hot pepper sauce and long time stockpiled ammunition. We first categorize the quality characteristics into three categories, then assign the certain amount of score based on the importance of the characteristics. Lastly, we applied the modified Taguchi loss function to calculate the achieved score of the characteristics. The perfect score is 100 and the closer to the score, the better product it indicates. Conclusions: In this research, we developed the modified Taguchi loss function to apply into the korean defense supplies. The loss function is utilized to calculate the achieved level of satisfaction of the supplies based on the defense specifications. The application of defense quality score may help to stimulate the continuous quality improvement and encourage the good will quality competition among the military providers.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.119-130
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• 1997

In this paper, we analyze quality loss function(QLF) of Taguchi. Taguchi method of QLF gives more advanced measure process capability than classic capacity(i.e. Cp). We first discuss of QLF and Cp and give one good example of QLF. Because of simplicity of QLF, it is not good fit to a, pp.y in the real field. We suggest interval quantity-loss cost function and total loss cost(TLC) which modify QLF. Also we give one example which can be obtained in the real field.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.110-117
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• 2018

Machines and facilities are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. By the result of degeneration, non-conforming products and malfunction of machine occur. Therefore a periodic preventive resetting the process is necessary. This type of preventive action is called 'preventive maintenance policy.' Preventive maintenance presupposes that the preventive (resetting the process) cost is smaller than the cost of failure caused by the malfunction of machine. The process mean shift problem is a field of preventive maintenance. This field deals the interrelationship between the quality cost and the process resetting cost before machine breaks down. Quality cost is the sum of the non-conforming item cost and quality loss cost. Quality loss cost is due to the deviation between the quality characteristics from the target value. Under the process mean shift, the quality cost is increasing continuously whereas the process resetting cost is constant value. The objective function is total costs per unit wear, the decision variables are the wear limit (resetting period) and the initial process mean. Comparing the previous studies, we set the process variance as an increasing concave function and set the quality loss function as Cpm+ simultaneously. In the Cpm+, loss function has different cost coefficients according to the direction of the quality characteristics from target value. A numerical example is presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.203-212
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• 2018

Quality requirements of manufactured products or parts are given in the form of specification limits on the quality characteristics of individual units. If a product is to meet the customer's fitness for use criteria, it should be produced by a process which is stable or repeatable. In other words, it must be capable of operating with little variability around the target value or nominal value of the product's quality characteristic. In order to maintain and improve product quality, we need to apply statistical process control techniques such as histogram, check sheet, Pareto chart, cause and effect diagram, or control charts. Among those techniques, the most important one is control charting. The cumulative sum (CUSUM) control charts have been used in statistical process control (SPC) in industries for monitoring process shifts and supporting online measurement. The objective of this research is to apply Taguchi's quality loss function concept to cost based CUSUM control chart design. In this study, a modified quality loss function was developed to reflect quality loss situation where general quadratic loss curve is not appropriate. This research also provided a methodology for the design of CUSUM charts using Taguchi quality loss function concept based on the minimum cost per hour criterion. The new model differs from previous models in that the model assumes that quality loss is incurred even in the incontrol period. This model was compared with other cost based CUSUM models by Wu and Goel, According to numerical sensitivity analysis, the proposed model results in longer average run length in in-control period compared to the other two models.

• International Journal of Quality Innovation
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• v.6 no.2
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• pp.31-45
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• 2005

The target costing technique, mathematically discussed by Sauers, only uses the $C_p$ index along with Taguchi loss function and ${\bar{X}}-R$ control charts to set up goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p$ value to ${\bar{X}}-R$ control charts to obtain goal control limits. This study further considers the reflected normal loss function as well as the $C_{pk}$ index along with its lower confidence interval in forming goal control limits. With the use of lower confidence interval to replace the point estimator of the $C_{pk}$ index and reflected normal loss function proposed by Spiring to measure the loss to society, this modified and improved target costing technique would become more robust and applicable in practice. Finally, an example is provided to illustrate how this modified and improved target costing technique works.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.80-90
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• 1992

In industries, the capability indices $C_p$ and $C_{pk}$ can be used to provide measures of process potential capability and performance, respectively. The new approach advocated by Taguchi in quality control overcomes some problems in other approaches preventive management activities. Taguchi introduces the emphasis on loss function to improve quality of products on the side of customer. The proceeding concept of capability indices is not rational for the measurement of quality if the process mean is not equal to target value. The Taguchi approach is said to be more reasonable than the others in quality evaluation because of his loss function. However, the capability indices $C_{pm}{^+}$ and $C_{pn}$ using Taguchi's loss function only consider, acceptance cost for deviation from target value within specification limits. In other words, they do not include rejection cost for nonconformings that are failed to fall on the specification limits.

• Journal of Applied Reliability
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• v.1 no.1
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• pp.35-46
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• 2001

Replacement policy of a degradation system is investigated by incorporating the loss function. Loss function is defined by the deviation of the value of quality characteristic from its target value, which determines the loss cost. Cost function is comprised of the inspection cost, replacement cost and loss cost. Two cost minimization problems are formulated : 1)determination of an optimal inspection period given the state for the replacement and 2)determination of an optimal state for replacement under fixed inspection period. Simulation analysis is performed to observe the variation of total cost with respect to the variation of the parameters of loss function and inspection cost, respectively As a result, parameters of loss function are seen to be the most sensitive to the total cost. On the contrary, inspection cost is observed to be insensitive. This study can be applied to the replacement policy of a degradation system which has to produce the quality critical product.