Kabushiki Kaisha Toshiba

Shuichi Samata

Takashi Nakao

Yukihiro Ushiku

Yoshiaki Matsushita

Yuuichi Mikata

Ken Ishii

Masanori Numano

Atsuko Kubota

Norihiko Tsuchiya

Takeo Furuhata

Yoshihiro Ueno

Akihito Yamamoto

Tsunetoshi Arikado

Toshiro Usami

Moriya Miyashita

Masakatu Kojima

Yoko Inoue

Shizuo Sawada

Hiroshi Akahori

Satoshi Maeda

Masanobu Ogino

Susumu Yoshikawa

Mokuji Kageyama

Tadahide Hoshi

Hiroyuki Fukui

Akiko Sekihara

Toshinori Shinki

Tsutomu Amai

Hachiro Hiratsuka

Toshikatsu Masuda

Keiko Akita

A system for designing a utility facility includes a state analyzer analyzing operational states of tools included in a production line, an extraction module extracting an operational period and a standby period of each of the tools, a calculator calculating changes in a quantity of utilities consumed by the tools in operation and in standby, based on the operational periods and the standby periods, and a facility design module designing at least any of a utility facility for supplying utilities to the tools and a utility facility for disposing of utilities discharged from the tools.

System, method and program for designing a utility facility and method for manufacturing a product by the utility facility

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.

Manufacturing apparatus and method for predicting life of a manufacturing apparatus which uses a rotary machine

An apparatus for predicting life expectancy of a rotary machine includes: a load recipe input module acquiring loading conditions of a rotary machine; a characterizing feature input module obtaining characterizing feature data of a rotary machine; and a life expectancy prediction module calculating life expectancy of the rotary machine in conformity with the loading conditions and the characterizing feature data.

Apparatus for predicting life of rotary machine and equipment using the same

A method for avoiding irregular shutoff of production equipment, includes: measuring regularly time-series data of characteristics of a rotary machine used in the production equipment running for the production; obtaining first failure diagnosis data subjecting the time-series data to a first real-time analysis; obtaining second failure diagnosis data subjecting the first failure diagnosis data to a second real-time analysis; predicting a status of the production equipment several minutes later using the second failure diagnosis data; and shutting off during a production process if the result of the prediction determines that the production equipment will shut off irregularly, and switching to a purge sequence for conducting a gas purge of the production equipment.

Method for avoiding irregular shutoff of production equipment and system for avoiding irregular shutoff

A method for diagnosing failure of a manufacturing apparatus, includes: measuring time series data of characteristics of a reference apparatus which conducts same processes as the manufacturing apparatus, and recording the time series data of the characteristics in a system information storage unit as a system information database; reading out a recipe listed in a process control information database recorded in a process control information storage unit; driving and controlling the manufacturing apparatus, measuring time series data of the characteristics as test data, and outputting the test data in real time, in accordance with the recipe; performing calculations on the test data, and creating failure diagnosis data; and diagnosing the failure of the manufacturing apparatus using the failure diagnosis data and the system information database.

Method for diagnosing failure of a manufacturing apparatus and a failure diagnosis system

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.

System for predicting life of a rotary machine, method for predicting life of a manufacturing apparatus which uses a rotary machine and a manufacturing apparatus

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.

Method for predicting life span of rotary machine used in manufacturing apparatus and life predicting system

An apparatus for predicting life expectancy of a rotary machine includes: a load recipe input module acquiring loading conditions of a rotary machine; a characterizing feature input module obtaining characterizing feature data of a rotary machine; and a life expectancy prediction module calculating life expectancy of the rotary machine in conformity with the loading conditions and the characterizing feature datap.

Method for predicting life of rotary machine and determining repair timing of rotary machine

A method for diagnosing life of manufacturing equipment having a rotary machine, includes: measuring reference time series data for characteristics before deterioration of the manufacturing equipment occurs; finding a reference auto covariance function based on the reference time series data; extracting a reference variation caused by variations of the process condition and power supply from the reference auto covariance function, and calculating a cycle of the reference variation; measuring diagnostic time series data for the characteristics in a sequence to be measured of the manufacturing equipment; finding a diagnostic auto covariance function based on the diagnostic time series data; and determining the life of the manufacturing equipment from the diagnostic auto covariance function using a component with a cycle shorter than a cycle of the reference variation.

Method for diagnosing life of manufacturing equipment using rotary machine

A semiconductor substrate has a support substrate formed of monocrystal silicon, an oxide film formed on the support substrate and a thin film of monocrystal silicon formed on the oxide film. The support substrate is a high-concentration P-type substrate to which boron is so doped that a resistivity of the support base is 0.1 .OMEGA..cm or less. In manufacturing: boron is into the support base so that a resistivity of the support base is 0.1 .OMEGA..cm or less; a silicon substrate on which the thin film of monocrystal silicon is formed is heated at 1100.degree. C. or higher for 30 min or longer within a reducing atmosphere; the heat treated silicon substrate is attached to the high-concentration P-type support substrate via the oxide film formed on a surface of any one of the support substrate and the P-type silicon substrate and the attached substrates are heated at 950.degree. C. or higher for 10 min or longer to bond the attached substrates together; and the bonded silicon substrate is thinned.

Semiconductor substrate and method of manufacturing same

A manufacturing method for manufacturing a semiconductor substrate has first annealing step for annealing silicon single crystal to permit oxygen embryos or oxygen precipitations grown from the oxygen embryos precipitating in a predetermined region and a second annealing step for permitting said oxygen embryos or said oxygen precipitations to contract using a second temperature range higher than the first temperature range, said second temperature range being high enough to contract said oxygen embryos and low enough to prevent redistribution of boron from affecting to device characteristics, to form a denuded zone in said predetermined region at the principal surface. An inspection method for inspecting a semiconductor substrate further has measuring step, subsequent to said first and second annealing steps for measuring the density of oxygen embryos grown into oxygen precipitations among those precipitated in said silicon single crystal.

Manufacturing method of semiconductor substrate and inspection method

Provided is a process for producing a semiconductor silicon wafer by which an intrinsic gettering effect can be improved and at the same time the top side can be made free from faults. A silicon ingot is produced and sliced to obtain silicon wafers. Then, a polycrystal silicon depositing film is formed on one side of a silicon wafer, which is subjected to a heat treatment in an inert gas, a reducing gas or a mixture thereof to discharge oxygen from the vicinity of the other side. Alternatively, after discharging oxygen from the silicon wafer by a heat treatment, a polycrystal silicon depositing film may be formed on one side of the silicon wafer.

Semiconductor silicon wafer and process for producing it

A method for manufacturing a semiconductor device can reduce a micro-roughness and does not change a construction and electric characteristics of elements formed in the semiconductor device. In the method for manufacturing the semiconductor device including a pre-oxidation process in which an oxide layer is first formed on a silicon wafer, and the oxide layer is secondly eliminated to eliminate impurities on a surface of the silicon wafer, a formation of the oxide layer in the pre-oxidation process is performed in an oxidization atmosphere including H.sub.2 O and gas including germanium hydride (german --GeH.sub.4 --). Since german (GeH.sub.4) is included in the oxidization atmosphere, it is possible to reduce a softening temperature of the silicon dioxide formed in pre-oxidation, thereby decreasing the micro-roughness on the surface of the silicon wafer. Furthermore, since it is possible to perform the pre-oxidation process in a low temperature and in a short time, there is no change of a construction and electric characteristics of elements formed in the semiconductor device.

Method for manufacturing a semiconductor device including pre-oxidation

Process for producing Semiconductor silicon wafer

There are provided a method of inspecting and evaluating semiconductor substrates, good quality semiconductor substrates, a method of manufacturing good quality semiconductor substrates, and a method of manufacturing semiconductor devices using good quality semiconductor substrates. A semiconductor substrate is processed with aqueous basic solution. In this process, the substrate is dipped in the aqueous solution or exposed to a vapor of the aqueous solution. With this process, the surface of the substrate is selectively etched. The substrate surface after the etching process is radiated with a laser beam to measure a light scattered point density. The quality of the substrate can be judged in accordance with the measured density. A thermal treatment may be carried out before or after processing the substrate with the aqueous basic solution. The thermal treatment considerably changes the fine defect density on the surface of the substrate. In accordance with such a change, the quality of the substrate may be judged. If a substrate judged as having a good quality is used, a semiconductor device having a good quality substrate can be obtained.

Growing community of inventors

Yokohama, Japan

Shuichi Samata