• Korean Journal of Computational Design and Engineering
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• v.16 no.6
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• pp.397-406
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• 2011

Since tolerance allocation in a mobile phone camera manufacturing process greatly affects production cost and reliability of optical performance, a systematic design methodology for allocating optimal tolerances is required. In this study, we proposed the tolerance optimization procedure for determining tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices. We employed Latin hypercube sampling for evaluating the reliabilities of optical performance and a function-based sequential approximate optimization technique that can reduce computational burden and well handle numerical noise in the tolerance optimization process. Using the suggested tolerance optimization approach, the optimal production cost was decreased by 30.3 % compared to the initial cost while satisfying the two constraints on the reliabilities of optical performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.452-460
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• 2001

Most of researches of tolerance optimization have used a simple sum of tolerance-cost functions with several constraint equations as an optimization model. However, if there is a machining sequence with more than one processes to complete a part, and machining failure, i.e., out-of-tolerance occurs at one of the intermediate processes, the tolerance-cost of this process should be added by the machining cost of all the previous processes already completed on the part. In this study, an accumulated scrap cost model(ASCM) is proposed considering the scrapped machining cost, and applied to a simple assembly example. The result of tolerance optimization using ASCM is compared with that of using a traditional optimization model to confirm its effectiveness.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.45-52
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• 2000

The purpose of this research was developing an integrated way to solve two typical tolerance optimization problem i.e. optimal tolerance allotment and design centering. A new problem definition design centering-tolerance allotment problem (DCTA) was proposed here for the first time and solved. Genetic algorithm and coarse Monte Carlo simulation were used to solve the stochastic optimization problem. Optimal costs were compared with the costs from the previous optimization strategies Significant cost reductions were achieved by DCTA scheme.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1600-1604
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• 2010

This paper presents the optimum design of the brushless motor to maximize the output power per weight considering the design parameter tolerance. The optimization is proceeded by commercial software that is adopted the scatter-search algorithm and the characteristic analysis is conducted by FEM. The stochastic optimum design results are compared with those of the deterministic optimization method. We can verify that the results of the stochastic optimization is superior than that of deterministic optimization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.905-913
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• 2003

Generally, most of optimization have been performed with fixed sizes and variables. But, the optimum value considering tolerance of design variables and material properties, might be useless owing to exist in infeasible region. It is needed that the tolerance of design variables and material properties is considered for a real design problem. A deterministic optimal solution can be in the feasible region by performing robust optimization considering tolerance. In the paper, robust design is suggested to gain an optimum insensitive to variation of design variables and it is applied for optimization problem of caliper disc brakes for vehicles.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1063-1068
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• 2008

A lens system of a camera module for mobile phones is comprised of the composition and design of various shapes of lens. To improve responses such as the modular transfer function (MTF), a lens system should always be constructed by considering uncertainty that can be caused by manufacturing and assembly error. In this study, tolerance optimization using the Latin Hypercube Sampling (LHS) technique is performed. In order to reduce the computational burden of the tolerance optimization process and decrease the influence from numerical noise effectively, we use the Progressive Quadratic Response Surface Modeling (PQRSM), which is one of Sequential Approximate Optimization (SAO) techniques. Using this method, we achieved optimal tolerance for each lens and obtained reliability for satisfying user‘s requirements. In addition, through the design process the manufacturing and assembly cost of a lens system was reduced.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.58-67
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• 2002

Since the inception of off-line quality control, it has drawn a particular attention from research community and it has been implemented in a wide variety of industries mainly due to its extensive applicability to numerous real situations. Emphasizing design issues rather than control issues related to manufacturing processes, off-line quality control has been recognized as a cost-effective approach to quality improvement. It mainly consists of three design stages: system design, parameter design, and tolerance design which are implemented in a sequential manner. Utilizing experimental designs and optimization techniques, off-line quality control is aimed at achieving product performance insensitive to external noises by reducing process variability. In spite of its conceptual soundness and practical significance, however, off-line quality control has also been criticized to a great extent due to its heuristic nature of investigation. In addition, it has also been pointed out that the process optimization procedures are inefficient. To enhance the current practice of off-line quality control, this study proposes an integrated optimization model by utilizing a well-established statistical tool, so called response surface methodology (RSM), and a tolerance - cost relationship.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.903-912
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• 2009

This study is focused on simulation-based dimensional tolerance optimization process (DTOP) to minimize vehicle pulls by reduction of dimensional variation in front suspension system. In previous studies, the effect of tires and wheel alignment sensitivity have mainly been investigated to eliminate vehicle pulls in nominal design condition without allocating optimal tolerance level for selected components, among various factors regarding vehicle pulls such as vehicle design parameters, vehicle weight balance, tires, and environmental factors. Unfortunately, there are wide variations in the real vehicle, and these have impacted actual vehicle pulls, especially wheel alignment effects from suspension geometry variation has not been considered in the previous studies. In the tolerance design of suspension, tolerance variables with the uncertainty such as parts dimensional variation, assembly process, datum position and direction, and assembly tool tolerance has a great influence on the variation of the suspension dimensional performances. This study introduces total vehicle pull prediction model in considering major key factors for vehicle pull sensitivity. The Monte Carlo-based tolerance analysis model using Taguchi robust method is developed to optimize dimensional tolerance parameters, satisfying on the target variation level.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1437-1443
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• 2003

Most optimization problems do not consider tolerance of design variables and design parameters. Ignorance of these tolerances may not fit for the practical problems and can lead to an unexpected conclusion. That is why we suggest robust optimization considering tolerances in both design variables and problem parameters. Using robust optimization, we designed minimum weight annular finned heat transfer tube subject to constraints on limitation of pressure difference and minimum value of total heat transfer. Consequently, robust optimization satisfies tolerance considered practical problems.