• 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 Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.57-64
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• 1989

An Economic selection of specification limits is considered for a given target value in a complete inspection plan. Each item is inspected, and if it meets the specification, it is accepted. Items less than the lower specification limit are scrapped or sold at a reduced price, and those greater than the upper specification limit are reworked. Cost factors to be considered are economic loss caused by quality deviations, rework cost and scrapping cost. Methods for finding the optimal specification limits are given for the cases of piecewise linear loss function and quadratic loss function with illustrative examples.

• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.28-39
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• 1994

This study is concerned with determination of an optimal target value in a filling process. Complete inspection procedures are widely used to improve outgoing quality of products. In many cases, however, it may be impossible or noneconomical to measure the quality characteristic, performance variable, directly. In such cases, it is a common practice to select an easily measurable variable which is highly correlated with the performance variable and perform screening products for the variable. This study proposes a model to determine the target value and the inspection rule based on the screening variable. This, study deals with the cases in which rejected products would be scrapped and sold at a reduced price in secondary markets.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.916-921
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• 2014

In this paper, an improved small-scaled blade prototype was designed with the flap-driving mechanism classified as an active vibration reduction method, in order to reduce vibratory load in the helicopter. In detail, the previous Active Trailing-Edge Flap based on piezoelectric actuator, called SNUF(Seoul National University Flap), failed to achieve the target value (${\pm}4^{\circ}$) of the flap deflection angle. Therefore, the flap-driving mechanism design was improved, and a new piezoactuator was selected to accomplish the target value of the flap deflection angle in both static and rotating situations.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.3
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• pp.504-509
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• 1987

In this paper a characteristics of image which can be segmented based on the thresholding technique using a histogram was investigated employing 3 parameters: the variance of pixel value, the average mean difference between target and background and the target size. The threshold value for the histogram segmentation was determined by applying the hypothesis testing theory. The performance of the selected threshold was evaluated by computing a probability of error. Since a priori probability can be easily obtained from the histogram, it was found that the Bayes decision rule which theoretically guarantees the minimum probability of error works better than the minimax criterion rule.

• Journal of the Korea Safety Management & Science
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• v.1 no.1
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• pp.101-110
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• 1999

QFD is a market driven design and development methodology for products and services to meet or exceed customer's needs and expectations, This method enables to specify clearly the customer's needs and then evaluate the product capability in terms of its impact on meeting those needs. Process of satisfying customers begins with effectively soliciting their different needs and wants which may be non-technical and imprecise in nature. Although the HoQ is a comprehensive tool for showing the relationships between attributes, it lacks the flexibility to deal with the inherent inexactness and vagueness in the voice of customer. In this paper, fuzzy theory is introduced to overcome this limitation. Qualitative customer requirements are interpreted quantitative data through fuzzy inference procedure, and then target value is determined.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.67-76
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• 2000

We consider the determinant of the most economical target value through the sampling inspection by two consecutive machines. The machine sequence is fixed as products have to be processed by machine 1 first and then by machine 2 next, In this paper we assume that if quality of a unit is lower than inspection lower specification limited then the goods is not accepted, otherwise it is accepted. And we assume that the quality characteristics is larger-the-better characteristics and its distribution is the normal distribution whose standard deviation is known. This paper ends up with an numerical example by using the total expected profit function model that consider the scales profits inspection costs and material costs. And we analyze the variation of the total expected profit by changing coefficients of the functions.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.371-383
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• 1997

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input-output pair. First, a method of linear fuzzy regression analysis is described by interpreting the reliability of each input-output pair as its membership values. Next, an architecture of fuzzy neural networks with fuzzy weights and fuzzy biases is shown. The fuzzy neural network maps a crisp input vector to a fuzzy output. A cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is illustrated by computer simulations on numerical examples.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.275-285
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• 1995

In recent years there has been increasing interest in the issue of process centering in manufacturing process, The traditional process capability indices Cp, Cpk and Cpu are used to provide measure of process performance, but these indices do not represent the issue of process centering. A new measure of the process capability index Cpm is proposed that takes into account the proximity to the target value as well as the process variation when assessing process performance. However, Cpm only considers acceptance cost for deviation from target value within specification limits, do not includes economic consideration for rejected items. This paper proposes flexible process performance measures that considered quadratic loss function caused by quality deviation within specification limits, rejection cost associated with the disposition of rejected items, and inspection cost. In this model disposition of rejected items are considered under perfect corrective procedures and the absence of perfect corrective procedures.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.7-13
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• 1999

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input -output pair. First, an architecture of fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding