• Journal of Korean Society for Quality Management
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• v.36 no.2
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• pp.20-27
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• 2008

Tolerance design has been identified as an important research area and a number of models have been proposed in the literature. This paper investigates the effect of limited capacity on tolerance design for products with nominal-the-best type (N-type) quality characteristics. The model is developed under the assumption that the reprocessed and nonreprocessed items are produced by the same manufacturing process and therefore their quality characteristics are identically and independently distributed. Profit models are constructed which involve four price/cost components; selling price, cost incurred by imperfect quality, reprocessing and quality inspection costs. Methods of finding the optimal tolerance limits are presented, and a numerical example is given. Sensitivity analyses are also performed to study the effect of a process standard deviation on this model.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.4
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• pp.243-247
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• 2010

Every products, which made by mass production, is not identical in their size but have variations in some intervals specified by tolerance dimensions. Tolerances play major role in standardization of part and its quality, and also make a huge impact on manufacturing cost. The optimal condition for tolerances is giving the values as loose as possible for low production cost while satisfying quality specification, which usually demand tight control of tolerances. Tolerance analysis is necessary to get an optimal solution for this conflict situation. This paper have studied tolerance analysis for universal joint assembly of vehicle steering system and tried to find useful results of the study for product design and quality control.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.81-87
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• 2004

This paper deals with a new approach to tolerance optimization problems. Optimal tolerance allotment problems can be formulated as stochastic optimization problems. Most schemes to solve the stochastic optimization problems have been found to exhibit difficulties in multivariate integration of the probability density function. As a typical example of stochastic optimization the optimal tolerance allotment problem has the same difficulties. In this stochastic model, manufacturing system is represented by Gauss-Markov stochastic process and the manufacturing unit availability is characterized for realistic optimization modeling. The new algorithm performed robustly for a large deviation approximation. A significant reduction in computation time was observed compared to the results obtained in previous studies.

• IE interfaces
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• v.16 no.spc
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• pp.39-44
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• 2003

As one of many design variables, the role of dimension tolerances is to restrict the amount of size variation in a manufactured feature while ensuring functionality. In this study, a nonlinear integer model has been modeled to allocate the optimal tolerance to each individual feature at a minimum manufacturing cost. While a normal distribution determines statistically worst tolerances with its symmetrical property in many previous tolerance allocation studies, a asymmetrical distribution is more realistic because its mean is not always coincident with a process center. A nonlinear integer model is modeled to allocate the optimal tolerance to a feature based on a beta distribution at a minimum total cost. The total cost as a function of tolerances is defined by machining cost and quality loss. After the convexity of manufacturing cost is checked by the Hessian matrix, the model is solved by the Complex Method. Finally, a numerical example is presented demonstrating successful model implementation for a nonlinear design case.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1305-1310
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• 2010

In a practical design process, the method of extracting the design space information of the complex system for verifying, improving, and optimizing the design process by taking into account the design variables and their shape tolerance is very important. Finite element analysis has been successfully implemented and integrated with design of experiment such as D-Optimal array; thus, a response surface model and optimization tools have been obtained, and design variables can be optimized by using the model and these tools. Then, to guarantee the robustness of the design variables, a robust design should be additionally performed by taking into account the statistical variation of the shape tolerance of the optimized design variables. In this study, a new approach based on the use of the response surface model is proposed; in this approach, the standard normal distribution of the shape tolerance is considered. By adopting this approach, it is possible to simultaneously optimize variables and perform a robust design. This approach can serve as a means of efficiently modeling the trade-off among many conflicting goals in the applications of finite element analysis. A case study on the robust optimal design of disc brakes under thermal loadings was carried out to solve multiple objective functions and determine the constraints of the design variables, such as a thermal deformation and weight.

• Proceedings of the Optical Society of Korea Conference
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• 2009.10a
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• pp.290-291
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• 2009

• Proceedings of the KWS Conference
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• 2007.11a
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• pp.300-302
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• 2007

• Proceedings of the Optical Society of Korea Conference
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• 2004.02a
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• pp.200-201
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• 2004

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.917-918
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• 2011

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.571-572
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• 2011