Abstract: A system for predicting life of a rotary machine, includes a vibration gauge configured to measure time series data of a peak acceleration of the rotary machine; a band pass filter configured to filter an analog signal of the time series data of the peak acceleration measured by the vibration gauge in a frequency band including a first analysis frequency expressed as a product of an equation including a number of rotor blades of the rotary machine and a normal frequency unique to the rotary machine; and a data processing unit configured to predict a life span of the rotary machine by characteristics of the filtered analog data of the time series data of the peak acceleration with the first analysis frequency.

Abstract: A method for predicting life of a rotary machine used in a manufacturing apparatus, includes: determining a starting time of an abnormal condition just before a failure of a monitor rotary machine used in a monitor manufacturing process, from monitor time-series data for characteristics of the monitor rotary machine, statistically analyzing the monitor time-series data, and finding a value for the characteristics at the starting time of the abnormal condition as a threshold of the abnormal condition; measuring diagnosis time-series data for the characteristic of a motor current of a diagnosis rotary machine during a manufacturing process; preparing diagnosis data from the diagnosis time-series data; and determining a time for the diagnosis data exceeding the threshold as the life of the diagnosis rotary machine.

Abstract: A manufacturing apparatus which includes a rotary machine, includes: a plurality of accelerometers configured to measure diagnosis time series data attached to the rotary machine at locations where variations of the rotary machine are different; a frequency analysis device configured to perform a frequency analysis on the diagnosis time series data measured by the plurality of accelerometers; a time series data recording module configured to generate diagnosis data based on variations in characteristics of vibration corresponding to an analysis target frequency and to record the diagnosis data; and a life prediction unit configured to analyze the diagnosis data to determine a life span of the rotary machine.

Abstract: SiGe or SiC films are selectively grown on source/drain regions, followed by selectively growing silicon. A monocrystalline film having a high dislocation density or a polycrystalline film can be grown in growing the silicon film by making the C or Ge concentration higher than a predetermined level. The silicon layer on each of the source/drain regions is not monocrystalline or, even if monocrystalline, has a high density of dislocation. Therefore, the silicon film formed thereon is in the form of a monocrystalline silicon film having a high dislocation density or a polycrystalline silicon film. It is possible to suppress an impurity diffusion to reach a deep region caused by channeling of ions generated in the doping step by means of an ion implantation.

Abstract: SiGe or SiC films are selectively grown on source/drain regions, followed by selectively growing silicon. A monocrystalline film having a high dislocation density or a polycrystalline film can be grown in growing the silicon film by making the C or Ge concentration higher than a predetermined level. The silicon layer on each of the source/drain regions is not monocrystalline or, even if monocrystalline, has a high density of dislocation. Therefore, the silicon film formed thereon is in the form of a monocrystalline silicon film having a high dislocation density or a polycrystalline silicon film. It is possible to suppress an impurity diffusion to reach a deep region caused by channeling of ions generated in the doping step by means of an ion implantation.

Abstract: A method for predicting life span of a rotary machine used in a manufacturing apparatus, includes: measuring rotary machine acceleration evaluation time series data with a sampling interval being less than a half the cycle of an analysis target frequency, a number of samplings being at least four times the analysis target frequency; generating evaluation diagnosis data based on variations in characteristics corresponding to the analysis target frequency by subjecting the evaluation time series data to frequency analysis; and determining the life span of the rotary machine using the evaluation diagnosis data.