Hitachi-high-technologies Corporation

Hitachi, Ltd.

Hitachi Cable, Inc.

Toshihiro Morisawa

Daisuke Shiraishi

Akira Kagoshima

Satomi Inoue

Shoji Ikuhara

Shigeru Nakamoto

Yasuharu Namba

Toshiyuki Ukai

Hisahiko Abe

Toshihiro Nakajima

Takehiko Tani

Takashi Furuya

Naohiro Suzuki

Hisataka Nagai

Kosaku Tachikawa

Various failure rates are supposed for each facility, and an optimal maintenance plan is made. A maintenance planning apparatus includes a failure rate model generation unit that generates a failure rate model on the basis of failure probability information which is set for an O&M asset by a user, a simulation execution unit that executes simulation regarding a failure which possibly occurs in the O&M asset in a plurality of different conditions on the basis of the generated failure rate model, a KPI computation unit that computes a KPI corresponding to each of the plurality of different conditions on the basis of results of the simulation, and an analysis unit that analyzes the plurality of different conditions and KPIs respectively corresponding to the plurality of different conditions, so as to determine an optimal condition corresponding to the best KPI.

Maintenance planning apparatus and maintenance planning method

A plasma processing apparatus including: a monitor device which monitors a process quantity generated at plasma processing; a monitor value estimation unit which has monitor quantity variation models for storing change of a monitor value of the process quantity in accordance with the number of processed specimens and which estimates a monitor value for a process of a next specimen by referring to the monitor quantity variation models; and a control quantity calculation unit which stores a relation between a control quantity for controlling the process quantity of the vacuum processing device and a monitor value and which calculates the control quantity based on a deviation of the estimated monitor value from a target value to thereby control the process quantity for the process of the next specimen. Thus, stable processed results can be obtained even when variation occurs in processes.

Plasma processing apparatus

Semiconductor manufacturing equipment includes: a controller controlling driving and processes of various parts of the semiconductor manufacturing equipment, and a sensor monitoring each physical amount in the semiconductor manufacturing equipment or a status of each chemical response amount; a database; and an arithmetic section executing: processing of reading out equipment data, calculating a correlation matrix between time points based on a plurality of pieces of signal data to be compared, calculating eigen values and eigen vectors from the correlation matrix, and calculating principal component scores by principal component analysis; processing of comparing magnitudes of the eigen values of the principal components, arranging the eigen values in descending order to display a list thereof; and processing of displaying a scatter diagram where the principal component scores of the respective signals are plotted in a feature space selecting the principal component corresponding to the eigen value having a contribution ratio.

Semiconductor manufacturing equipment

A plasma processing apparatus including: a monitor device which monitors a process quantity generated at plasma processing; a monitor value estimation unit which has monitor quantity variation models for storing change of a monitor value of the process quantity in accordance with the number of processed specimens and which estimates a monitor value for a process of a next specimen by referring to the monitor quantity variation models; and a control quantity calculation unit which stores a relation between a control quantity for controlling the process quantity of the vacuum processing device and a monitor value and which calculates the control quantity based on a deviation of the estimated monitor value from a target value to thereby control the process quantity for the process of the next specimen. Thus, a process model indicating variation of the state of a process processing apparatus can be added to a control loop in such run-to-run control that process conditions are changed according to each wafer process, so that stable processed results can be obtained even when variation occurs in processes.

Based on a model for determining optical emission intensity values Y at wavelengths from actuator values X of an etching apparatus, X is calculated from Y to achieve preferable Run-to-Run control over Y. A relation between X and Y is defined as a control model (matrix model C, ratio-constraint model C) based on an algebraical expression with &#x394;X as an input and &#x394;Y as an output. In etching process control, &#x394;X (manipulated volume) is calculated from &#x394;Y (controlled volume) using the control model, based on a non-control optical emission intensity value Y, to set X (S) for the etching process, during which Y is monitored. Based on an actual value for Y, a non-control optical emission intensity value Y to be used in the next wafer etching process is calculated.

Etching apparatus, control simulator, and semiconductor device manufacturing method

There is provided an etching apparatus in which, without setting the information of the substance and the chemical reaction, a small number of representative wavelengths can be selected from a waveform at a lot of wavelengths, and an analysis process of etching data which needs large man-hours can be eliminated to efficiently set the monitoring of the etching. The etching apparatus includes: a lot/wafer/step-depending OES-data searching/acquiring functionfor acquiring a plurality of optical emission intensity waveforms along an etching-treatment time axis; a waveform-change-existence judgment functionfor judging the existence of the change of the plurality of light emission intensity waveforms; a waveform-correlation-matrix calculating functionfor calculating a correlation matrix between the optical emission intensity waveforms; a waveform classifying functionfor classifying the optical emission intensity waveforms into groups; and a representative-waveform selecting functionfor selecting a representative optical emission intensity waveform from the group.

Etching apparatus, analysis apparatus, etching treatment method, and etching treatment program

In a manufacturing method of a semiconductor photonic device substrate, before multi-layer films different in material composition are successively and gradually crystal-grown in one chamber, an inter-layer growth rate model showing a relation in growth rate between each layer is defined, a growth rate of a film corresponding to at least one or more layers is obtained by actual crystal growth using an individual substrate, a growth rate of a film corresponding to other layers is estimated from the obtained growth rate by the inter-layer growth rate model, and a growth time is determined in accordance with a film thickness of each layer of the semiconductor photonic device substrate based on the actually obtained growth rate and the estimated growth rate. These steps are carried out by using a computer system connected to an MOCVD equipment, and then, a crystal growth of the semiconductor photonic device substrate is performed.

Manufacturing method of semiconductor photonic device substrate

An etching process state judgment method comprising: a spectral data obtaining step, in which an optical emission spectrum distribution is obtained by monitoring optical emission during an etching process of a plurality of wafers; a peak detection step, in which peaks are detected from the optical emission spectrum distribution at a specific time point during the etching process, to obtain peak characteristics; a common peak identifying step, in which peaks common to the wafers are identified among the peaks detected in the peak detection step; and a state detection step, in which the characteristics are compared regarding the common peaks, to detect a state of each wafer in the etching process. A state (anomaly or normalcy) of an etching process is detected from optical emission spectrum distribution at the time of etching process, by a simple method without assuming substances.

Etching process state judgment method and system therefor

In a wafer polishing method, a within-wafer distribution model of a removal rate and a within-wafer distribution model of a polishing process are selected, and a within-wafer distribution of a removal rate is obtained by determining parameters of a within-wafer distribution model of a removal rate based on the within-wafer distribution of the film thickness before/after CMP, polishing condition data, and the selected within-wafer distribution model of the polishing process of the polished wafer. Then, a film thickness in the polishing process is estimated from passage of time based on the obtained within-wafer distribution of the removal rate, the selected within-wafer distribution model of the polishing process, and the film thickness before CMP of the wafer to be processed, thereby determining the polishing conditions with a restriction that the film thickness at each position in the within-wafer distribution of the film thickness after CMP satisfies the control limit.

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Yokohama, Japan

Toshihiro Morisawa