• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.61-70
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• 1993

The concept of producer's tolerance, in contrast to the consumer's tolerance, is a natural consequence of continuous loss functions. It is based on the premise that any unit product whose quality characteristic deviated from its traget value inflicts a loss, and that this less is a continuous monotonically increasing function of the magnitude of deviation. This concept of the emphasis on loss function to improve quality of products on the side of customer is introduced by Taguchi. This paper considers the problem of determining the optimum producer's tolerance by continous loss fuction of Taguchi and proposes a probablistic model for the problem. The difference between the proposed probablistic approach and the approach taken in Taguchi is also pointed out.

• 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 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.14 no.24
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• pp.133-139
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• 1991

If the specifications of product. in general. art determined too wide. the precision of product becomes diminished. Otherwise it costs dearly to keep the precision. Therefore, It is realistic to consider various factors in determining specification of qualify characteristics TAGUCH Idefines quality of an object as "Quality is the loss that a product causes to society after being shipped. other than any losses caused by its intrinsic function". Particularly, to improve the performances of product TAGUCHI focuses his attention on the product design and process design which enable the functional characteristics of product to he robust to noises. In this paper, by the TAGUCHI's loss function, the characteristics which affect the variation of a product performance are classified into the scrappable characteristics and the reworkable characteristics when the target values of functional characteristics have been determined. And we will determine the tolerance of each characteristic which minimize the quality cost by the cost function which considers the economic factors and probability features of each characteristic.cteristic.

• 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.

• International Journal of Quality Innovation
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• v.4 no.1
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• pp.191-204
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• 2003

The target costing technique, mathematically discussed by Sauers, only uses the $C_p index along with Taguchi loss function and $\bar{X}$-P control charts to setup goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p value to $\bar{X}$-P control charts to obtain goal control limits. Studies have shown that the point estimator of the $C_p index, $C_p, could vary from time to time due to the sampling error. The suggested approach is to use confidence intervals, especially the lower confidence intervals, to replace the point estimator. Therefore, an improvement on target costing technique is presented by applying the lower confidence interval of the $C_p index and using both Taguchi and Spiring's loss functions together with $\bar{X}$-P charts to make this technique more robust in practice. An example is also provided to illustrate how the improved target costing technique works.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.4
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• pp.10-15
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• 2007

Taguchi methods have been used for a long time to improve the product quality and process performance of a manufacturing system, Few researchers have applied this methodology in laser beam cutting (LBC) of sheet metals and found the considerable improvement in cut qualities. In all experimental investigations of LBC so far, the objective was to optimize the single quality characteristic at a time. In this paper the simultaneous optimization of multiple quality characteristics such as Kerf width and material removal rate (MRR) during pulsed Nd:YAG LBC of thin sheet of magnetic material (high Silicon-steel) has been presented using Taguchi's quality loss function. The results show the considerable improvement in multiple S/N ratio as compared to initial cutting condition. Also, the comparison of results from single and multi-objective optimization have been presented and it was found that the loss in quality is always possible shifting from single quality to multiple quality optimization.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.467-482
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• 2021

Purpose: The main theme of this study is to determine the optimal control limit of conditional variance investigation by mathematical approach. According to the determination approach of control limit presented in this study, it is possible with only one parameter to calculate the control limit necessary for budgeting control system or standard costing system, in which the limit could not be set in advance, that's why it has the advantage of high practical application. Methods: This study followed the analytical methodology in terms of the decision model of information economics, Bayesian probability theory and Taguchi's quality loss function concept. Results: The function suggested by this study is as follows; ${\delta}{\leq}\frac{3}{2}(k+1)+\frac{2}{\frac{3}{2}(k+1)+\sqrt{\{\frac{3}{2}(k+1)\}^2}+4$ Conclusion: The results of this study will be able to contribute not only in practice of variance investigation requiring in the standard costing and budgeting system, but also in all fields dealing with variance investigation differences, for example, intangible services quality control that are difficult to specify tolerances (control limit) unlike tangible product, and internal information system audits where materiality standards cannot be specified unlike external accounting audits.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.98-104
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• 2009

The objective of this paper is to investigate the effect of factors on the dynamic stiffness variation of boring bar. The experiment was carried out by Taguchi Method and Orthogonal array table. The results indicate that overhang was found out to be dominant factor with 95% confident intervals and feed rate and depth of cut were insignificant. In addition, analysis of loss function shows that loss value increased sharply from 3D to 4D(D is a shank diameter). Consequently, there is critical point which changes property of dynamic stiffness.

• International Journal of Quality Innovation
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• v.9 no.1
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• pp.41-54
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• 2008

The process capability indices have been widely used to measure process capability and performance. In this paper, we proposed a new process capability index which is based on an actual dollar loss by defects. The new index is similar to the Taguchi's loss function and fully incorporates the distribution of quality attribute in a process. The strength of the index is to apply itself to non-normal or asymmetric distributions. Numerical examples were presented to show superiority of the new index against $C_p$, $C_{pk}$, and $C_{pm}$ which are the most widely used process capability indices.