On-line learning delivery decision support system for highlyproduct mixed semiconductor foundry

A production learning system (PLS) based on the tool model was constructed as a decision support and real-time information update system to forecast the cycle time. A tool model includes a waiting model and a processing model. Each of the waiting and processing models uses a backpropagation neural network to establish the relationship between the input and output (time) of the model. Hence, cycle time estimation, tool group move and confirm line item performance (CLIP) value can be obtained based on the memory stored in the neural network. The result shows that the forecasting ability of the PLS has an error rate below 8% on average     

The effect of charge relaxation on the electromagnetic radiation of an oscillating charged viscous drop

A dispersion equation for the capillary oscillations of a charged drop of incompressible liquid possessing a finite electric conductivity is derived with an allowance for the energy lost as a result of the electromagnetic wave emission. The magnitude of the electromagnetic radiation losses of the oscillating drop linearly increases with the electric conductivity and the surface mobility of charge carriers.     

Thermal expansion of gray tin

Translated from Izmeritel'naya Tekhnika, No. 7, pp. 40–41, July, 1989.     

Tuning a three-loop steam temperature regulation system using the method of evolutionary simulation

We present the results from tuning a PI controller and two differentiators for a three-loop steam temperature regulation system with two leading speed signals. The calculation was carried out with a numerical method using a simulation model and with the application of the authors’ version of the evolutionary optimization algorithm.     

Analysis of the high-frequency spectrum of acoustic emission signals and its relationship to the wear resistance of filled polytetrafluoroethylene

We have performed tribotechnical tests of carbonaceous filled polytetrafluoroethylene in a wide range of loads with the recording of acoustic emission signals. Based on a spectral analysis of the sequence of rms deviations of acoustic emission signals using a discrete Fourier transform, we have constructed a normalized energy spectrum. We show that the mass wear of the material can be determined from the power of the high-frequency component of the spectrum obtained.