Earticle

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Product array approach which is used in the Taguchi parameter design has a number of advantages by considering the noise factor. Taguchi has an idea that mean and variation are handled simultaneously to reduce the expected loss in products and processes. Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design using desirability function without resorting to SN.

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Taguchi has an idea that mean and variation are handled simultaneously to reduce the expected loss in products and processes. In the Taguchi parameter design, the product-array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined-array approach, was studied. In these studies, only single quality characteristic (or response) was considered. In this paper we propose how to simultaneously optimize for multiple quality characteristics (or multiresponse) using desirability function when we used the combined-array approach to assign control and noise factors.

Each method for economic evaluation has its own characteristics. Therefore adoption of each of them in evaluation production investment project results in many problems. Hence combination & modification of them are required to perform more accurate evaluation about investment project. This paper discuss evaluation method of investment projects expansion and replacement investment on each line or individual in the production. Generally investment evaluation method has add to a few method by Subsidiary means with use a especial method. And then in this paper, a Taguchi Techniques is presented, which may be effective to the facilities appraisal or improvement. We propose a decision model to incorporates the values assigned by a group of experts on different factors in production. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for reducing production rate in production management.

Domestic industry has a long history, but it has been suffering for a long time due to its poor competitiveness in management ability, supply of materials, technological development, sales marketing, and distribution networks. Moreover, the industry has not established its strong presence in the world market but is exposed to increasingly greater agonies because of inactive domestic demands, increase rate of import versus export, diversified government policies, and non-selective introduction of high-quality and low-priced foreign named brands of ceramics into the country. Theses factors have partly contributed to consumers' low or negative recognition.

Since randomness and uncertainties of design parameters are inherent, the robust design has gained an ever increasing importance in mechanical engineering. The robustness is assessed by the measure of performance variability around mean value, which is called as standard deviation. Hence, constraints in robust optimization problem can be approached as probability constraints in reliability based optimization. Then, the FOSM (first order second moment) method or the AFOSM (advanced first order second moment) method can be used to calculate the mean values and the standard deviations of functions describing constraints and object. Among two methods, AFOSM method has some advantage over FOSM method in evaluation of probability. Nevertheless, it is difficult to obtain the mean value and the standard deviation of objective function using AFOSM method, because it requires that the mean value of function is always positive. This paper presented a special technique to overcome this weakness of AFOSM method. The mean value and the standard deviation of objective function by the proposed method are reliable as shown in examples compared with results by FOSM method.

This study uses a characteristic function to explain correlations between the objective function and design variables. For the use, structural analysis and buckling analysis are carried out. the dimensional change of an original overhead crane is made based on the table of orthogonal array. For two functions or more, the effectiveness of design change can be evaluated in accordance with change in design parameters. Also, the overhead crane's weight is reduced by up to 10.55 percent while its structural stability maintained.

A control design for flexible joint manipulator in the presence of nonlinearity and mismatched uncertainty is introduced. The control does not need the possible bound of uncertainty a priori. Only the existence of the bound is assumed. A state transformation is introduced via implanted control to tackle a mismatched system. The scheme utilizes the bounding function by combining states and parameters, which is to be estimated. Then an appropriate parameters update laws are designed to guarantee an asymptotic convergency by adopting Lyapunov approach. The control version shows that states converge to zero for the transformed system, and guarantees the uniform stability and boundness. This is also true for the original system in case either the gravitational force is absent or the system is coordinated such that the gravitational force converges to zero as link angles approach zero. The control performance is verified through experiments and shows an enhanced tracking performance for given references.

A general trend and one of the important strategies in the automotive industry is reducing the lead time of a new car development. In order to obtain this goal the efficient use of simulation software is needed to effectively design a hydroformed part. The stages of the design chain are integrated in one simulation tool. The outcome of this feasibility analysis is a virtual prototype saying that it is possible to produce the part. In fact one process point has been defined whereas when going into production a process window must be know to guarantee a stable production process. In order to achieve this latter we are suggesting a process performance analysis. Based on multiple simulations the influence and sensitivity various process parameters on the forming process can be identified. Besides combining the analysis with statistical process control evaluation the process capability (Cpk-values) can be defined. This design chain analysis will be applied on a hydroformed part. The process performance analysis is the identification of the process window and process capability in advance, so before any tool has been milled. This will be demonstrated on a second hydroformed part.

This paper describes the design of a sliding mode controller to control wheel slip. A yaw motion controller (YMC), which uses a PID control method, is also proposed for controlling the brake pressure of the rear and inner wheels to enhance lateral stability. It induces the yaw rate to track the reference yaw rate, and it reduces a slip angle on a slippery road. A nonlinear observer is also developed to estimate the vehicle variables difficult to measure directly. The braking and steering performances of the anti-lock brake system (ABS) and YMC are evaluated for various driving conditions, including straight, J-turn, and sinusoidal maneuvers. The simulation results show that developed ABS reduces the stopping distance and increases the longitudinal stability. The observer estimates velocity, slip angle, and yaw rate very well. The results also reveal that the YMC improves vehicle lateral stability and controllability when various steering inputs are applied. In addition, the YMC enhances the vehicle safety on a split-$\mu$ road.

The Taguchi parameter design in industry is an approach to reducing performance variation of quality characteristic in products and processes. In the Taguchi parameter design, the product array approach using orthogonal arrays is mainly used. It often requires an excessive number of experiments. An alternative approach, which is called the combined array approach, was studied. In these studies, only single response was considered. In this paper we propose how to simultaneously optimize multiresponse for the robust design using the combined array approach.

Taguchi's robust parameter design is an approach to reduce the performance variation of quality characteristics in products and processes. In robust design, the signal-to-noise ratio (SN ratio) was used to find the optimum condition to minimize the variation of quality characteristics as much as possible and bring the average of quality characteristics closer to the target value. In this paper, we propose a simultaneous optimization method based on a linear model of the SN ratio as a method to find the optimal condition of the control factor in case of multi-characteristics. In addition, the proposed method and the existing method were compared and studied by taking actual cases.

An automated injection molding design methodology has been developed to optimize multiple quality attributes, which are usually in conflict with each other, in injection molded parts. For the optimization, commercial CAE simulation tools and optimization techniques are integrated into the methodology. To decal with the multiple objective problem the relative closeness computed in TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) is used as a performance measurement index for optimization multiple part defects. To attain robustness against process variation, Taguchi's quadratic loss function is introduced in the TOPSIS. Also, the modified complex method is used as an optimization tool to optimize objective function. The verification of the developed design methodology was carried out on simulation software with an actual model. Applied to production this methodology will be useful to companies in reducing their product development time and enhancing their product quality.

In this study a method for a robust design of mechanisms is proposed. The method used in the experimental analysis and quality engineering is applied for mechanisms design. A mathematical model for a mechanism is estimated by the response surface analysis and the estimated model is used in minimization of the variance. Using this result, robust design can be carried out. The method can be applied for general mechansims. Furthermore because the method can be used in the design stage using the computer model, improved quality and lower cost of the product is achieved even in the design stage.

RMR은 육안적 방법으로 암반을 분류하는 비교적 간단한 방법이나 조사구간이 많아지면 번거로운 작업이된다. 본 연구에서는 RMR을 기계적으로 분류하고자 인공신경망에 의한 학습모델과 예측모델을 개발하였다. 강건설계에 의하여 총 3125개의 데이터를 25개의 학습자료로 최적화하였다. 두 방법에 의한 학습 후 테스트 결과는 서로 정확하게 일치하였다. 강건설계에 의하여 전체 경우의 수를 1% 이하로 축소한 학습자료로 전체자료와 동일한 학습효과를 얻었다는 것은 학습자료 습득에 드는 노력과 비용을 크게 절감할 수 있다는 의미이다. RMR 분류시스템의 완벽한예측을 위하여 1차 예측값들에 대하여 주어진 수준 범위 내에서 튜닝을 실시하였다. 그 결과 강건설계에 의한 25개의학습자료로 실제 3125개의 빅데이터의 RMR을 완벽하게 예측하는 RMR분류 ANN 시스템을 구현하였다.

Rock mass rating (RMR) is a relatively simple method for classifying rock mass with the naked eye; however, it becomes inconvenient when the number of survey sections is large. In this study, we developed a learning model and a prediction model using an artificial neural network (ANN) to classify RMR mechanically. Using robust design, 3125 big data were optimized into 25 learning data. The test results after learning through the two methods were exactly the same. Through robust design, the learning data obtained by reducing the total number of cases to less than 1% had the same learning effect as the whole data, which means that the effort and cost of acquiring the learning data can be greatly reduced. For the perfect prediction of the RMR classification system, we tuned the primary predictions within a given range of rating levels. As a result, we implemented an RMR classification ANN system that perfectly predicts the RMR of 3125 big data using 25 learning data through robust design.

The correlation between the object function and the design parameter is shown on this paper by using the characteristic function for the mixed result of the structural analysis, the buckling analysis and the table of orthogonal array according to the original overhead crane's dimensional change. About the above two functions, the effectiveness of design change according to the change of design parameters could be estimated. Also, the overhead crane's weight is reduced up to 10.55 percent maintaining the structural stability according to the thickness of plate.

In this paper, the robust controller design is performed for the speed control of the underwater vehicle diesel engine. Nonlinear model equations are acquired through the mathematical modeling using mean torque production model technique. It is very difficult to design the robust controller because those are high nonlinear and not expressed in terms of the matched uncertainty Therefore those are converted into the separable model into the linear nominal system and the nonlinear uncertainty term.

Input shaping technique has been used as a simple method of controlling the residual vibration of a flexible manipulator. With the conventional methods previously proposed by several authors, the frequency range that shows a good performance is restricted. When the designed frequency being different from the natural frequency of a system, the performance of control degrades remarkably. This paper introduced a new technique that designs input shaping with robustness in the z-domain.

The Robust Controller for scan-loop is designed using LQG/LTR Methodology. The design and analysis of spiral, rosette and conical scan patterns are discussed. The perfermance and robustness of the LQG/LTR controller are analyzed through experiments and cpmpared with those of the P-controller. Especially to improve the scan performance at large look angle, the cage coil output is linearized using a binomial equation. It is demonstrated that the scan-loop system by the LQG/LTR control is very robust to phase uncertainties.

A robust controller is proposed for regulating effectively the pressure of control cylinder of swash plate type variable displacement axial piston pump. In order to design a precise and robust pressure control system, a mathematical model for swash plate control system is identified by the signal compression method. Based on the identified mathematical model, an $H_{\infty}$ robust swash plate controller is designed which is robust to the variation of the load pressure. The precise and robust swash plate control characteristics are verified by experiments.