• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2444-2447
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• 2005

The purpose of this study was to analyze the gait motion of the aged with a lower limbs orthosis. The gait motion was analyzed with and without lower limbs orthosis using APAS 3D Motion Analysis System. The pattern of lower limbs motion was tracked based on four targets attached to the body of the subject. The targets were positioned at hip, knee, ankle, and foot. The parameters measured were the displacement, the velocity, and the acceleration of the four targets. The improvement in the measured values on the displacement and the velocity of the four targets were small with the orthosis due to inconvenience of wearing it, but the increase in the acceleration was large due to the elastic force of the rubber actuator. Especially, the increase of the acceleration of foot with lower limbs orthosis seems to help the gait motion of the elderly.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.945-949
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• 2004

These days there are so many scheduling systems or softwares. But only few scheduling systems have succeeded in the market. In spite of powerful engine and functions, those systems have difficulties to be applied in real processes. In real processes, there are various constraints caused by physical or systematical environments of plants. Those constraints are too many to be handled in the system. This problem makes it difficult for the system to represent the details of processes. In order to resolve this problem, we have developed a specialized scheduling system for a target process. The system could be developed by the experts for target process and researchers for scheduling. In this study, a scheduling system for PVC process has been developed as an MILP (Mixed integer linear programming) model and coded in $Fortran^{TM}$. The scheduling system has been applied to two processes, which have different characteristics. Simulation results indicate that the profit of the target process can be increased by about 5% by implementing the scheduling system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).