Disclosed embodiments provide techniques for automated replacement of components in a datacenter. A robot is instructed to follow a route to replace parts within a datacenter. Embodiments include predicting a failure rate for a plurality of computer components within a datacenter. A failure time is then predicted for the computer components based on the corresponding failure rate. A route is created that allows the robot to visit the one or more racks containing the computer components that need to be replaced. The robot then replaces the components that require replacing. In this way, datacenter efficiency is improved and operating costs are reduced.

Techniques to facilitate predictive maintenance for industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives a plurality of industrial automation process variables associated with at least one industrial asset employed in an industrial automation process. The industrial automation process variables are fed into a machine learning model associated with the at least one industrial asset to generate a future maintenance event prediction for the at least one industrial asset. The future maintenance event prediction for the at least one industrial asset is provided to an industrial controller that controls the at least one industrial asset.

An operating system for a container handling machine, including an operating device for the container handling machine having a screen and a data transmitter for transmitting information and at least one separate additional screen having a data receiver for receiving information, with the operating device designed for selecting the information and the additional screen designed for displaying the selected information.

An information processing device according to one aspect of the present invention includes a first acquirer configured to acquire measured data of a sensor, a second acquirer configured to acquire characteristic data of the sensor, the characteristic data having been acquired by maintaining the sensor, and a generator configured to generate teacher data in which the acquired characteristic data is associated as label information with the acquired measured data.

Disclosed embodiments provide techniques for automated replacement of components in a datacenter. A robot is instructed to follow a route to replace parts within a datacenter. Embodiments include predicting a failure rate for a plurality of computer components within a datacenter. A failure time is then predicted for the computer components based on the corresponding failure rate. A route is created that allows the robot to visit the one or more racks containing the computer components that need to be replaced. The robot then replaces the components that require replacing. In this way, datacenter efficiency is improved and operating costs are reduced.

An atomic power plant operation system for assisting the operation of an atomic power generation plant is provided with: an operation monitoring system which monitors and controls the operation of the atomic power generation plant; an abnormality indication monitoring system which, on the basis of an operation history of the atomic power generation plant, monitors an indication of abnormality in the atomic power generation plant; an abnormality diagnosis system which, on the basis of a result of abnormality indication that has been detected, makes an abnormality diagnosis for the atomic power generation plant; and a maintenance system for performing maintenance and management of the atomic power generation plant, wherein the systems are communicably connected, and the abnormality diagnosis system provides the maintenance system with the result of the abnormality diagnosis of the atomic power generation plant.

A device maintenance apparatus, includes: a communication control part configured to control a communication with a device; a device information acquisition part configured to acquire device information of the device via the communication; a storage configured to store maintenance process information, the maintenance process information including device specifying information for specifying a maintenance target device and process specifying information for specifying details of a maintenance process; and an information processing part configured to compare the acquired device information to the stored maintenance process information, and to execute a maintenance process on the device based on the result of the comparison.

A maintenance information management device includes an information registration unit configured to register vehicle identification information and maintenance information in a memory for each vehicle, an information update unit configured to update the maintenance information after the maintenance of the vehicle by adding maintenance contents to the maintenance information registered in the memory, and an information providing unit configured to provide the maintenance information when a provision request for the maintenance information is accepted.

An apparatus for assisting maintenance work includes circuitry configured to perform learning based on a data set in association with a replaced or repaired part, or a new part after replacement indicated by work content information, and the learning includes processing an input of the data set or a portion of the data set, in accordance with model parameters of a machine learning model; determining work content information applied to the input; and updating the model parameters of the machine learning model based on the determined work content information.

Control system and method for a technical plant, in particular a production or process plant, includes an operator station server and an operator station client connected to the operator station server, wherein the operator station client, at runtime of the plant, receive an instruction specified by the operator for an operator activity relating to the plant and a condition specified by the operator and which relates to an internal state of the plant for the instruction and transmit them to the operator station server, and the operator station server stores the instruction and condition received from the operator station client in memory and checks whether the condition is met, such that operators can adapt flexibly and efficiently to the operation and monitoring of the plant, particularly if it is formed in a modular manner for plant configurations that change during its life cycle.