Hitachi, Ltd.

Hitachi-high-technologies Corporation

Yoshiyuki Tajima

Takashi Noguchi

Koji Kamoshida

Tohru Watanabe

Takaharu Ishida

Shigeru Yano

Susumu Serita

Yuichi Igarashi

Tomoaki Akitomi

Naomi Ishii

Kazuya Monden

Fumiya Kudo

Takahiro Ohira

Koichiro Iijima

Tomoyuki Yamagata

Yoshinori Mochizuki

There are provided a device that collects operation data from equipment, and an information processing apparatus that detects an anomaly or an omen of an anomaly of the equipment on the basis of anomaly detection models constructed from the operation data, the information processing apparatus including means for collecting the operation data, means for learning anomaly detection models from the operation data, and means for calculating an anomaly score of respective operation data from the operation data and the anomaly detection models, the means for learning an anomaly detection model in which a dispersion of elements is small among the anomaly detection models. Thus, in an anomaly detection system, when the operation state of equipment is monitored, even if data for performing division of operation states cannot be obtained or even if division cannot be performed correctly, misdetection of an anomaly such as a malfunction or a failure or an omen of an anomaly can be decreased and the state of the system can be evaluated correctly.

Anomaly detection system

Provided is a technique for extracting a factor (event pattern) that has an influence on an objective index (objective variable). A data analysis device according to the present disclosure performs: a process of generating, with respect to explanatory variable data included in data to be analyzed, a time-series pattern in a predetermined range; a process of calculating a correlation value between the time-series pattern and at least one item of objective variable data included in the data to be analyzed; and a process of outputting, together with the correlation value, the time-series pattern corresponding to the correlation value as an analysis result.

Analysis server device, data analysis system, and data analysis method

An on-site system includes a disclosure-condition-table storage unit and a disclosure-condition-table creation unit. The disclosure-condition-table storage unit stores a disclosure condition table for management of a relationship between a purpose of a service and a data characteristic of on-site data, as a disclosure condition for disclosing the on-site data to a service device that provides the service. The disclosure-condition-table creation unit creates the disclosure condition table in which a purpose of a service included in descriptive information of the service is associated with a data characteristic included in descriptive information of the on-site data, and stores the disclosure condition table in the disclosure-condition-table storage unit.

On-site system

A calculation device is provided that executes calculations within real-time restrictions. The calculation device implements a step of predicting a processing time of a calculation related to the amount and property of input data based on a prediction model; a step of adjusting the processing time by decreasing the amount of data used for the calculation or decreasing the number of iterative calculations when the processing time exceeds a time slice allocated to the calculation; a step of executes the calculation using the adjusted processing time; a step of updating, as required, the prediction model used for predicting the processing time according to the result of the calculation which is executed in a period where the calculation is not performed while implementing a change of the amount of data or the number of iterative calculations or change to an approximation.

Predictive sequential calculation device

Precise prediction of the state of congestion in an automatic analysis system and adjustment of timings and the order of take-in and take-out of specimens in each of devices prevent increase in TATs of urgent specimens. A device management server for instructing each device to take in or take out specimens in each device determines the current position of each specimen, estimates the staying time of each specimen in one of regions by simulating the operation of each device assuming an initial state in which each specimen is at the current position, causes the simulation unit to perform a simulation, and corrects the timings or order of take-in and take-out of one or more other specimens so that each of the staying times in one of the regions do not exceed a corresponding allowable staying time in the region.

Automatic analysis system and device management server

There is provided a sample test system which can execute a prior process for a specific sample in consideration of priorities and process progresses of a plurality of samples processed in the sample test system. The sample test system includes a sample-test-device management server, when a specific-sample prior process request containing a specific sample ID and a prior-process-request level identification code is accepted from a sample access system, which selects a specific-sample prior-process-policy determination table based on the prior-process-request level identification code attached to the specific-sample prior process request, which determines a specific-sample prior process policy based on the specific-sample prior-process-policy determination table and a process state of the sample, which specifies a sample ID regarding the specific sample ID, and which transmits the specific-sample prior process policy to a sample-test-device group

Sample-test-device management server, sample test device, sample test system, and sample test method

Growing community of inventors

Tokyo, Japan

Yoshiyuki Tajima