• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1537-1545
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• 2015

Support vector quantile regression (SVQR) can be obtained by applying support vector machine with a check function instead of an e-insensitive loss function into the quantile regression, which still requires to solve a quadratic program (QP) problem which is time and memory expensive. In this paper we propose an SVQR whose objective function is composed of an asymmetric quadratic loss function. The proposed method overcomes the weak point of the SVQR with the check function. We use the iterative procedure to solve the objective problem. Furthermore, we introduce the generalized cross validation function to select the hyper-parameters which affect the performance of SVQR. Experimental results are then presented, which illustrate the performance of proposed SVQR.

• 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 of Industrial and Systems Engineering
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• v.19 no.40
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• pp.233-240
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• 1996

A fixed amount compensator is proposed for a process with a linear tool wear function. A Cost model is constructed which involve process adjustment cost and quality loss. Symmetric and asymmetric quadratic functions of the deviation of a quality measurement from the nominal target value are considered as the quality loss functions. Methods of finding optimal values of initial setting and compensation limit are presented and a numerical example is given.

• Journal of Korean Society for Quality Management
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• v.38 no.4
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• pp.540-548
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• 2010

We consider the problem of selecting the most profitable initial process mean and length of production cycle for manufacturing processes subject to a constant linear trend during the same cycle that varies after resetting the processes. Assuming that the quality characteristic of interest is normally distributed, the optimum initial process mean and the length of production cycle are jointly obtained by minimizing the expected loss per unit time. We assume that the quality loss function due to the deviation from the target value is quadratic and resetting loss is constant. We consider both cases of symmetric and asymmetric quality loss function. An illustrative example is given and sensitivity analysis performed.