Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation( max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

This research introduced a command-filtered backstepping control of mirror system to maintain laser communication between satellite and ground station. This requires a 2 degree of freedom gimbal mirror system using DC motors for target acquisition, pointing, and tracking (APT) system. This APT system is used for laser communication between satellite and ground stations. To track these desired angles, we have to control DC motors using introduced command-filtered backstepping controller (CFBSC) with disturbance. Command filtered backstepping controller has second order filter instead differentiation for simple and fast calculation. Introduced command-filtered backstepping control gives a smooth control signal for intermediate states. Simulation results verify that CFBSC outperforms SMC in terms of tracking error and disturbance rejection.

This paper describes the design of H-infinity controller for robust control of a DC motor system. The suggested controller can ensure robustness against disturbance and model uncertainty by minimizing H-infinity norm of the transfer function from exogenous input to performance output and applying the small gain theorem. In particular, the controller was designed to reduce the effects of disturbance and model uncertainty simultaneously by formalizing these problems as a mixed sensitivity problem. The validity of the proposed controller was demonstrated by computer simulations and real experiments. Moreover, the effectiveness of the proposed controller was confirmed by comparing its performance with PI controller, which was tested under the same experimental condition as the H-infinity controller.

The most time consuming job in the sheet metal forming process is compensating for springback. Factors such as uneven material properties and process conditions generate noise, which in turn create springback. The springback is very sensitive to the process and noise conditions, and the main effects of the design variables cannot be obtained from mean analysis. Therefore, to achieve minimal springback, an effective design countermeasure must be put in place to reduce noise effects. In this study, two robust design methods to achieve minimal springback in U-channel forming, including compensation process, are proposed. The effectiveness of the proposed methods is shown with an example of the sidewall curl springback. The proposed methods consistently outperform our previous work, indicating that the complex method is more preferable to the mean analysis, if there is no evidence of additivity of effects.

A robust adaptive control approach is proposed for underactuated surface ship linear path-tracking control system based on the backstepping control method and Lyapunov stability theory. By employing T-S fuzzy system to approximate nonlinear uncertainties of the control system, the proposed scheme is developed by combining “dynamic surface control” (DSC) and “minimal learning parameter” (MLP) techniques. The substantial problems of “explosion of complexity” and “dimension curse” existed in the traditional backstepping technique are circumvented, and it is convenient to implement in applications. In addition, an auxiliary system is developed to deal with the effect of input saturation constraints. The control algorithm avoids the singularity problem of controller and guarantees the stability of the closed-loop system. The tracking error converges to an arbitrarily small neighborhood. Finally, MATLAB simulation results are given from an application case of Dalian Maritime University training ship to demonstrate the effectiveness of the proposed scheme.

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally x-R control chart or x-s control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

Recently, the production cycle in manufacturing process has been getting shorter and different types of product have been produced in the same process line. In this case, the control chart using coefficient of variation would be applicable to the process. The theory that random variables are located in the three times distance of the deviation from mean value is applicable to the control chart that monitor the process in the manufacturing line, when the data of process are changed by the type of normal distribution. It is possible to apply to the control chart of coefficient of variation too.  ,  estimates that taken in the coefficient of variation have just used all of the data, but the upper control limit, center line and lower control limit have been settled by the effect of abnormal values, so this control chart could be in trouble of detection ability of the assignable value. The purpose of this study was to present the robust control chart than coefficient of variation control chart in the normal process. To perform this research, the location parameter, xα, sα were used. The robust control chart was named Tim-CV control chart. The result of simulation were summarized as follows; First, P values, the probability to get away from control limit, in Trim-CV control chart were larger than CV control chart in the normal process. Second, ARL values, average run length, in Trim-CV control chart were smaller than CV control chart in the normal process. Particularly, the difference of performance of two control charts was so sure when the change of the process was getting to bigger. Therefore, the Trim-CV control chart proposed in this paper would be more efficient tool than CV control chart in small quantity batch production.

The most time consuming operation during the tryout of new parts is the compensation of geometric deviations induced by springback. The variation of springback due to the noise factors such as material properties and forming conditions increase the difficulties of the compensation operation. If the forming process includes a drawing operation followed by a restriking operation, a robust design for springback compensation is needed for both operations. In this study, a new 2-stage procedure for robust springback compensation using Taguchi's orthogonal array experiments combined with the Pick-the-Winner rule and the design space reduction method is proposed. The effectiveness of the proposed method is shown with an example of the sidewall curl springback compensation in U-channel forming.

Control charts are generally used for process control, but the role of traditional control charts have been limited in case of a non-contaminated process. Traditional x-s control chart has not been activated well for such a problem because of trying to control processes as center line and control limits changed by the contaminated value. This paper suggests modified x-s control chart based on robust estimation. In this paper, we consider the trimmed mean of the sample means and the trimmed mean of the sample standard deviations. By comparing with ARL value, the responding results are decided. The comparison resultant results of traditional control chart and modified control chart are contrasted.

Control charts are generally used for process control, but the role of traditional control charts have been limited in case of a contaminated process. Traditional x control charts have not been activated well for such a problem because of trying to control processes as center line and control limits changed by the contaminated value. This paper is to propose robust x control charts which is considering a location parameter in order to respond to contaminated process. In this paper, we consider x, that is trimmed rate; typically ten percent rate is used. By comparing with p, ARL value, the responding results are decided. The comparison resultant results of proposed two control charts are shown and are well contrasted.

When it comes to designing a product or a process, the robust parameter design (RPD) methodology devised by Taguchi is recognized as a way to produce products or processes with less variability, while the specifications of products or processes are met, so that the ratio of nonconforming products can be as minimized as possible. Nevertheless, as a matter of fact, there have been many pros and cons concerning the RPD method, mainly because of the use of signal to noise ratio as the measure of quality characteristic. Meanwhile, the variability analysis method has been highly recommended as an alternative of the RPD in the literature. In this paper, it is demonstrated that RPD can also be implemented within the framework of the variability analysis, which is sounder in the statistical sense. In light of an example of RPD approach, the modeling and estimation procedure is discussed in some detail with a view to a comparison of the two methods.

This essay talks about research of robust design for quality improvement of production procedure of Wet Etchant. It suggested the optimum design method in consideration of specific capability value that is the way to maximize the quality of product in the production system by using Daguchi parameter design method while finding factors affecting product quality with analysis of production system of product A from producer D. Also, it set long term of 6months as noise factor and let it to be the robust design that can find the optimum condition of control factor that is dull to the changes of each month, that is the change in noise factor. The control factor which affects the product quality is decided as combination method, temperature of raw material, combination time and as there are too many possibilities for combination methods, we performed 4 methods first based on previous research data then derived three ways with product that passed SPEC and set as the factor. As a result of application of optimum production procedure suggested in this essay to the actual production process with its standardization, there was a effect of drop of more than 10particles in comparison to the particle number of previous product and also it brought the effect that resulted the stable number of particle of under 30 that is what the client company suggested.

Monitoring autocorrelated processes is prevalent in recent manufacturing environments. As a proactive control for manufacturing processes is emphasized especially in the semiconductor industry, it is natural to monitor real-time status of equipment throug

This study develops three new models that are practically applicable to three stages of Taguchi's robust design, which includes system design, parameter design and tolerance design. In system design, the Multiple Loss Function Analysis(MLFA) and Overall Loss Index(OLI) which reflect upon weight of characteristics and importance of specification are developed. Moreover parameter design presents Process Capability Index(PCI), CPUK and CPLK, in order to segregate Signal-To-Noise Ratio(SNR) into accuracy and precision for an evaluation of relative comparison. In addition, tolerance design presents the new model of allowance computation for assembled product which is primarily derived from safety margin(SM) considering functional limit and specification. The guideline of those three new models, which include systematic charts and applicable illustrations, offers convenience for practitioners in the field. Hence, the practical applications could be made with the steps of robust designs such as system design, parameter design and specification allowance design.

Quality design methodologies have received constituent attention from a number of researchers and practitioners for more than twenty years. Specially, the quality design for drug products must be carefully considered because of the hazards involved in the

  According to the automated manufacturing processes followed by the development of computer manufacturing technologies, products or quality characteristics produced on the processes have measured and recorded automatically. Much amount of data daily prod

As technique that can contribute in quality improvement in design process to overcome shortcoming of traditional quality control, call design or development department quality control activity that is achieved to reduce gun damage shuddering at circle minimizing change or side effect of product performance as off-line quality control. This paper discuss optimal process design of investment projects expansion and replacement investment on each line or individual in the production. Generally optimal plant design has add to a few method by Subsidiary means with use a especial method. And then in this paper, a Robust design is presented, which may be effective to the processes appraisal or improvement. We propose that should make a optimal plant design model for reducing field failure rate to assign by real data on different factors in plant system. Using this model, robust design of taguchi method used in this comprehensive method for reducing field failure rate in plant system.

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.