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A diagnostic system for dry pumps is proposed. It predicts future pump motor current from time-series in-situ measurements. The prediction system has been constructed using a data acquisition system with an online system identification software algorithm. A field test on a low pressure chemical vapour deposition (LPCVD) system for the silicon nitride process predicted large values of motor current, some of which correlated well with actual motor currents as the pump became clogged. The combined use of the predicted motor current and the stability criteria shows promise in predicting the actual service life of a dry pump.
Inspec keywords: control engineering computing; electronic engineering computing; time series; maintenance engineering; recursive estimation; life testing; autoregressive moving average processes; identification; stability criteria; vacuum pumps; chemical vapour deposition; data acquisition; integrated circuit manufacture; automatic test software
Other keywords:
Subjects: Vacuum physics; Testing; Pressure and vacuum control; Other final control equipment; Control applications in the electronics industry; Computerised instrumentation; Plant engineering, maintenance and safety; Surface treatment and coating techniques; Semiconductor industry; Control applications to materials processing; Electronic engineering computing; Production facilities and engineering; Chemical vapour deposition; Control gear and apparatus; Electronics industry; Data acquisition systems for control; Control technology and theory (production); Production engineering computing; Control engineering computing; Industrial applications of IT; Semiconductor technology; Computerised instrumentation; Instrumentation; Data acquisition systems; Maintenance and reliability