In this study, a winch and load motion control system design method is introduced. Especially, the winch and load (moving cart) are connected with long wire rope which is extended to few kilometers long. Therefore, the rope length changes such that many dynamic parameter values are changed as well by winding and releasing the rope from the winch system. In this paper, the authors designed the control system by considering the real time parameter variation to occupy and keep good control performance continuously. The effectiveness of introduced method was evaluated by simulation results.

In the manufacturing industry fields, thousands of quality characteristics are measured in a day because the systems of process have been automated through the development of computer and improvement of techniques. Also, the process has been monitored in database in real time. Particularly, the data in the design step of the process have contributed to the product that customers have required through getting useful information from the data and reflecting them to the design of product. In this study, first, characteristics and variables affecting to them in the data of the design step of the process were analyzed by decision tree to find out the relation between explanatory and target variables. Second, the tolerance of continuous variables influencing on the target variable primarily was shown by the application of algorithm of decision tree, C4.5. Finally, the target variable, loss, was calculated by a loss function of Taguchi and analyzed. In this paper, the general method that the value of continuous explanatory variables has been used intactly not to be transformed to the discrete value and new method that the value of continuous explanatory variables was divided into 3 categories were compared. As a result, first, the tolerance obtained from the new method was more effective in decreasing the target variable, loss, than general method. In addition, the tolerance levels for the continuous explanatory variables to be chosen of the major variables were calculated. In further research, a systematic method using decision tree of data mining needs to be developed in order to categorize continuous variables under various scenarios of loss function.

The object of this study is concerned about the optimal design of the supporting frame in a twist screen. Twist screen is widely used for grading and screening materials in the fields such as coal-selecting, mining-selecting, building materials, electrical power and chemical industry, etc. It is composed of base, supporting frame, vibrator, screen, spring, trough, clamp and etc. Especially, supporting frame in twist screen are stressed by high load, mostly it is shock-type loads. Nevertheless, design of base is dependent on experience, and it will cause reliability reduction and cost increase. The supporting plate is composed by the upper plate, the bracket and etc. This research purpose is to propose and verify a method to achieve higher product quality, lower costs, and far less physical testing. In this study, design parameters used for optimization are the upper plate thickness(8㎜, 10㎜, 12㎜) and the bracket thickness(8㎜, 10㎜, 12㎜) in the supporting frame. The result showed that base weight reduced to maximum 25.8% when compared with the current twist screen.

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.

An algorithm to determine the optimum nominal value of geometrical and material parameters in divice modelling is proposed. The algorithm uses the yield and variance prediction formula and Monte-Carlo analysis. The performance specification of the noise figure must also be satisfied. In this paper, the total number of considered devices is 1000, and each parameter of geometrical and material parameters is generated randomly within the limits of ±3% of nominal value, and the distribution of 1000 geometrical and material parameters is gaussing distribution.