Yokogawa Electric Corporation

Microsoft Technology Licensing, LLC

Nara Institute of Science and Technology

National University Corporation Nara Institute of Science and Technology

Hiroaki Kanokogi

Keiji Sato

Yota Furukawa

Go Takami

Hirotsugu Gotou

Keiichiro Kobuchi

Benjamin M Westbrook

Yutaka Suzue

Kevin Blaine Gjerstad

Yutaka Nakajima

Dong-Hui Zhang

Ryouhei Furihata

Kazutoshi Kodama

Junji Yamamoto

Yosuke Ishii

Hiromi Okamoto

Yoshio Uomori

Morihiro Fujisaki

Yoshiyuki Jinguu

Tomohiro Kuroda

Eiji Taya

Takamitsu Matsubara

Hiroto Abe

Mizuo Kawahara

Rei Karasawa

Shugo Sakatani

Liu Zhuo

Tomotaka Maki

Fumihiro Saito

Masayasu Sano

Takahisa Fukui

Lingwei Zhu

Yunduan Cui

Provided is a data recording apparatus including a key exchange unit for exchanging a first encryption key with a system in response to authentication by the system, a data collection unit for collecting measurement data obtained by measuring a physical quantity associated with a measurement target, a data recording unit for recording the measurement data, and a data transmission unit for transmitting the measurement data encrypted using the first encryption key to the system. In addition, provided is a system including a key management unit for exchanging a first encryption key with a data recording apparatus in response to authentication of the data recording apparatus, a data obtaining unit for obtaining measurement data obtained by measuring a physical quantity associated with the measurement target encrypted by the data recording apparatus using the first encryption key, and a data management unit for managing the measurement data using a distributed ledger technology.

Data recording apparatus, data recording method, recording medium having recorded thereon data recording program, system, method, and recording medium having recorded thereon program

There is provided a learning processing apparatus comprising: a learning processing unit configured to generate a control model that outputs a manipulated variable corresponding to an indicated variable and a process variable of a predetermined system by means of machine learning; a generation unit configured to generate controlling data that indicates a correspondence relation of a combination of the indicated variable and the process variable to the manipulated variable corresponding to the combination by using the control model; and a supply unit configured to supply the controlling data to a predetermined control apparatus.

Learning processing apparatus, control apparatus, learning processing method, control method, non-transitory computer-readable medium having learning program recorded thereon, and non-transitory computer-readable medium having control program recorded thereon

Provided is a control apparatus, including a control unit, configured to control a control target by a machine learned control model to output an operation amount of the control target according to a state of equipment having the control target provided therein; a prediction unit, configured to predict a future state of the equipment; an adjusting unit, configured to adjust the operation amount based on a predicted result; and an output unit, configured to output an adjusted operation amount to the control target.

Control apparatus, control method, and recording medium having control program recorded thereon

Provided is a control apparatus comprising a control unit configured to control a control target by a control model machine-learned so as to output an operation amount of the control target according to a state of equipment provided with the control target; a simulation unit configured to simulate, by using a simulation model, the state of the equipment in a case where the operation amount, which is output by the control model, is given to the control target; and a stop unit configured to stop control of the control target by the control model, based on a simulation result.

Control apparatus, control method and recording medium having recorded thereon control program

An apparatus is provided, which includes a setting unit for setting an operation content for a manufacturing system configured to manufacture an object to be manufactured, a first acquisition unit for acquiring a posterior state parameter set indicating a state of at least one of the manufacturing system or the object to be manufactured after the operation content is set, and a learning processing unit for executing, by using learning data including the operation content and the posterior state parameter set, a learning process of a control model of the manufacturing system configured to output the operation content that increases a reward value determined by a preset reward function in response to input of a state parameter set indicating a state of at least one of the manufacturing system or the object to be manufactured.

Apparatus, method and storage medium

A plant control supporting apparatus includes a segment selector configured to select, from among a plurality of segments defined in a plant, a segment for which learning for acquiring an optimal value of at least one parameter representing an operation state is executed, a reward function definer configured to define a reward function used for the learning, a parameter extractor configured to extract at least one parameter that is a target for the learning in the selected segment on the basis of input and output information of a device used in the plant and segment information representing a configuration of a device included in the selected segment, and a learner configured to perform the learning for acquiring the optimal value for each segment on the basis of the reward function and the at least one parameter.

Plant control supporting apparatus, plant control supporting method, and recording medium

Provided is an apparatus including a plurality of agents that each set some devices among a plurality of devices provided in a facility to be target devices, wherein each of the plurality of agents includes a state acquiring section that acquires state data indicating a state of the facility; a control condition acquiring section that acquires control condition data indicating a control condition of each target device; and a learning processing section that uses learning data including the state data and the control condition data to perform learning processing of a model that outputs recommended control condition data indicating a control condition recommended for each target device in response to input of the state data.

Apparatus, method, program, and recording medium

A battery management device according to one aspect of the present invention for managing a plurality of field devices of a battery-driven type, the plurality of field devices being associated with a facility disposed in a plant and being defined as belonging to a same group includes a battery manager that, in a case receiving battery life information representing approach to a battery life of an installed battery from a first field device that is one field device currently operating among the plurality of field devices, switches the operating field device to a second field device that is another field device belonging to the same group, an operation of the second field device being stopped.

Battery management device, battery management system, and battery management method

A plant control device of the present invention includes a register configured to register a simulated dangerous condition which is a simulated representation of an operation condition under which a plant is dangerous, a first acquirer configured to acquire an operation condition of the plant, a learner configured to learn the operation condition acquired and the simulated dangerous condition registered and produce an operation model of the plant, a determiner configured to determine an operation parameter of the plant on the basis of the operation condition acquired and the operation model produced, and an instructor configured to instruct an operation of the plant on the basis of the operation parameter determined.

Plant control device, plant control method, and recording medium

An information processing system includes a state data acquisition device configured to acquire state data indicating an operation state of a plant, a first classification device configured to generate a determination line used to classify the state data, a mirror image data generation device configured to generate mirror image data obtained by mirroring the acquired state data using the generated determination line, and a second classification device configured to generate a determination model on the basis of the state data and the generated mirror image data.

Information processing system, information processing method, and recording medium

Provided is a data management system including a plurality of nodes to be connected to and disconnected from a network. At least one of the plurality of nodes includes: a communicator that performs a communication via the network by using data having a data structure including a key; a database that accumulates the data; and a data analyzer that, when the node is newly connected to the network, provides another node already connected to the network with node information, the node information being used for enabling the node to serve as node for accumulating the data.

Data management system and data management method

A device setting apparatus according to one aspect of the present invention includes a data transmission processor configured to automatically and collectively acquire information used in at least one another device setting apparatus as other-device information from an external storage and an other-device information storage storing the other-device information. The external storage is communicatively connectable to the device setting apparatus via a network.

Device setting apparatus, storage storing device setting program, and method for sharing information among a plurality of device setting apparatuses

A field device management apparatus may include a plurality of COM in-process servers, each of which acquires and manages device data related to a corresponding one of field devices, and a launch-program COM in-process server that stores a launch-program, the launch-program activating an instance in each of the plurality of COM in-process servers, the launch-program preventing four different functions from being executed directly by an OS in the plurality of COM in-process servers. The plurality of COM in-process servers may be initialized on the Microsoft Windows operating system to generate COM objects in different memory spaces.

Field device management apparatus

There is provided a field device management apparatus for acquiring and managing device information about a field device. The apparatus includes: a device information description unit having: an activation processing algorithm that activates a device information processing algorithm for acquiring the device information from the field device; and a description information that describes the device information; and a device information acquisition control unit that activates the device information processing algorithm using the activation processing algorithm so as to acquire the device information through the device information description unit.

Field device management apparatus and field device management system

The sharing of language models is disclosed. In one embodiment, a language model service is provided that is shareable among handlers for input devices. The service includes a pre-processing mode of operation, and a correction mode of operation. In the former mode, the language model service is designed to receive a range within a document from a handler for an input device, and in response provide advice regarding text under consideration by the handler to insert within the document at the range, based on the context of the document within the range. In the latter mode, the language model service is designed to supervise correction over a range of text within a document, in which a number of different handlers for a number of different input devices were initially responsible for insertion of the text, such that the service solicits suggestions from the handlers, and based thereon determines text corrections. The corrections can then be made by the handlers, or by the service.

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Tokyo, Japan

Hiroaki Kanokogi