A system for providing an inspection system including an autonomous unmanned aerial vehicle (UAV) having the image capture device coupled together for generating image data used in inspections, a blockchain-based data exchange storage and verification device for maintaining image data, identified parts data, parts acquisition data, parts report data, and repair reports and corresponding repair data, a parts identifier, a parts identifier for generating one or more potential part identifications from the image data generated by the UAV, a parts acquisition installer, a repair reports generator for generating one or more repair reports based upon data stored within the blockchain-based data exchange storage and verification device, and a digital twin parts predictive fatigue and lifecycle maintenance estimator, the digital twin parts predictive fatigue maintenance lifecycle estimator for generating fatigue-based part life cycles for the one or more potential part identifications from the parts identifier. The parts identifier is an application programming interface to a remote third-party image analysis and component identification system. The parts acquisition installer schedules installation of a replacement part selected from the one or more potential part identifications from the parts identifier. The repair reports generator generates one or more repair reports based upon data stored within the blockchain-based data exchange storage and verification device. The digital twin parts fatigue maintenance estimator is an application programming interface to a remote third-party digital twin modeling and simulation-based parts fatigue and maintenance estimator.

A system for providing an inspection system including an autonomous unmanned aerial vehicle (UAV) having the image capture device coupled together for generating image data used in inspections, a blockchain-based data exchange storage and verification device for maintaining image data, identified parts data, parts acquisition data, parts report data, and repair reports and corresponding repair data, a parts identifier, a parts identifier for generating one or more potential part identifications from the image data generated by the UAV, a parts acquisition installer, a repair reports generator for generating one or more repair reports based upon data stored within the blockchain-based data exchange storage and verification device, and a digital twin parts predictive fatigue and lifecycle maintenance estimator, the digital twin parts predictive fatigue maintenance lifecycle estimator for generating fatigue-based part life cycles for the one or more potential part identifications from the parts identifier. The parts identifier is an application programming interface to a remote third-party image analysis and component identification system. The parts acquisition installer schedules installation of a replacement part selected from the one or more potential part identifications from the parts identifier. The repair reports generator generates one or more repair reports based upon data stored within the blockchain-based data exchange storage and verification device. The digital twin parts fatigue maintenance estimator is an application programming interface to a remote third-party digital twin modeling and simulation-based parts fatigue and maintenance estimator.

A production planning system (6) for a raw materials industry plant (ANL), which determines the production planning data (Pi) thereof and specifies said data to the automation system (1) of the plant (ANL). A state monitoring system (7) determines previous and future anticipated states (Z1) of components of the plant (ANL). A quality determination system (8) determines states (Z2) of output products (Ai) produced and still to be produced by the plant (ANL) and/or past and future states (Z3) of the plant (ANL) as a whole. A maintenance planning system (9) and/or the production planning system (6) receive, from the state monitoring system (7), the states (Z1) of the components of the plant (ANL), determined by the state monitoring system (7) and, from the quality determination system (8), the states (Z2 and Z3) of the output products (Ai) and/or of the plant (ANL) as a whole, determined by the quality determination system (8). They consider the data received from the state monitoring system (7) and from the quality determination system (8) in the determination of maintenance planning data (W) and/or the production planning data (Pi).

An equipment inspection system capable of creating an inspection plan for inspecting a component part of an equipment at an appropriate timing is provided. An equipment inspection system includes an index acquisition unit, an importance level judgement unit, and an inspection time determination unit. The index acquisition unit acquires at least one influence index. The importance level judgement unit judges an importance level of an inspection on a component part based on the influence index. The inspection time determination unit determines the inspection time of the component part according to the importance level.

In an approach to tracking mass-produced items via a digital twin, one or more computer processors receive one or more images of a product. One or more computer processors retrieve a digital twin template corresponding to the product. One or more computer processors detect an imperfection in the one or more images of the product. One or more computer processors map data associated with the imperfection to the digital twin template. One or more computer processors map data associated with the imperfection to the digital twin template. One or more computer processors assign a unique identifier to the digital twin template that includes the data associated with the imperfection. One or more computer processors store the data associated with the imperfection in association with the unique identifier.

A computer-implemented method for training a neural network on a hardware accelerator of an edge device includes dividing a trained neural network into a domain independent portion and a domain dependent portion. The domain independent portion of the neural network is deployed onto a dedicated neural network processing unit of the hardware accelerator of the edge device, and the domain dependent portion of the neural network is deployed onto one or more additional processors of the hardware accelerator of the edge device. The domain dependent portion on the additional processors of the hardware accelerator is retrained using data collected at the edge device.

Multiple component mounters that configure multiple user-side component mounting lines and a support-side information server are connected so as to be able to communicate with each other via a network. The support-side information server includes an information registration section collecting and registering failure information generated in the multiple user-side production devices and updating and registering failure avoidance information as a failure avoidance method becomes apparent, and an information distribution section distributing the failure information and the failure avoidance information to the user-side production devices. Each user-side production device includes an information receiving section receiving the failure information and the failure avoidance information from the support-side information server, and an information transmitting section transmitting to a user-side production manager the failure information and the failure avoidance information related to a failure that may occur at a production device managed by the production manager.

Methods and systems include ways to implement change analysis of an automated production line including at least one robot. Monitoring a plurality of operating parameters associated with the automated production line including the at least one robot is followed by recording at least one change to the plurality of operating parameters. A notification is then provided identifying the at least one change to the plurality of operating parameters. The notification can include mapping the at least one change onto a graphical representation of the automated production line, thereby identifying a portion of the automated production line affected by the at least one change. As a result, at least one of the operating parameters can be adjusted in response to the notification. An action can also be performed in response to the notification. In this manner, the change analysis can optimize operation of the automated production line.

Methods and systems include ways to implement change analysis of an automated production line including at least one robot. Monitoring a plurality of operating parameters associated with the automated production line including the at least one robot is followed by recording at least one change to the plurality of operating parameters. A notification is then provided identifying the at least one change to the plurality of operating parameters. The notification can include mapping the at least one change onto a graphical representation of the automated production line, thereby identifying a portion of the automated production line affected by the at least one change. As a result, at least one of the operating parameters can be adjusted in response to the notification. An action can also be performed in response to the notification. In this manner, the change analysis can optimize operation of the automated production line.

An automated, computer-controlled, cooking system for use with user selectable ones of a plurality of different pre-sealed computerized cooking containers containing dry contents (PSCCCCDC) useful in preparing corresponding different food products, the system including a microwave radiation generator, a PSCCCCDC support for supporting a user-selected one of the plurality of different PSCCCCDCs during cooking, a computer-controlled liquid supply subsystem for supplying liquid to the selected PSCCCCDC, a computer-controlled stirrer subsystem for producing stirring of the dry contents of the PSCCCCDC together with the liquid, a cooking instructions input interface for receiving PSCCCCDC specific cooking instructions and a computer controller operative to control operation of at least the computer-controlled liquid supply subsystem, the computer-controlled stirrer subsystem and the microwave radiation generator in a predetermined sequence corresponding to and specifically adapted for cooking the contents of the selected PSCCC-CDC in accordance with the PSCCCCDC specific cooking instructions.