A data management method, device and system based on blockchain. The data management method based on a blockchain is applied to a verification node. The method includes: acquiring transaction data including N pieces of digest data that are respectively generated on the basis of N pieces of data associated with the transaction data, and N is an integer greater than 1; selecting, from the N pieces of digest data, M pieces of digest data to be used for verification, M is an integer less than or equal to N and greater than or equal to 1; acquiring M pieces of storage data respectively corresponding to the M pieces of digest data; calculating respective digests of the M pieces of storage data, and when the M pieces of digest data are identical to the respective digests of the M pieces of storage data, respectively, writing the transaction data into a blockchain.

A data management method, device and system based on blockchain. The data management method based on a blockchain is applied to a verification node. The method includes: acquiring transaction data including N pieces of digest data that are respectively generated on the basis of N pieces of data associated with the transaction data, and N is an integer greater than 1; selecting, from the N pieces of digest data, M pieces of digest data to be used for verification, M is an integer less than or equal to N and greater than or equal to 1; acquiring M pieces of storage data respectively corresponding to the M pieces of digest data; calculating respective digests of the M pieces of storage data, and when the M pieces of digest data are identical to the respective digests of the M pieces of storage data, respectively, writing the transaction data into a blockchain.

A program for causing a processor of a computer to execute: a step of receiving an input of first information indicating a name of a component of a finished product to be manufactured at a manufacturing site; a step of receiving an input of second information indicating a name of a manufacturing process for the component; a step of receiving an input of image information captured by photographing or filming a state of the manufacturing process; a step of associating the image information with the first information and the second information; and a step of presenting the image information together with the first information and the second information to a user.

A server including a storage and a controller is communicably connected with a communication terminal. The storage is configured to store a processing data and an analysis data for each of a plurality of analysis targets. The processing data relates to a processing condition for forming a concavo-convex structure on a detection substrate to be used in performing a spectroscopic analysis. The analysis data is used to analyze the analysis target from a spectroscopic spectrum of the analysis target obtained by the spectroscopy analysis. Upon receiving a signal requesting the processing data, the controller is configured to select the processing data corresponding to the analysis target and transmit the selected processing data to the communication terminal. Upon receiving a spectroscopic spectrum, the controller is configured to use the analysis data to analyze the spectroscopic spectrum.

An image processing apparatus includes an image obtainer that obtains a moving image including an operation area captured with an image sensor, an image generator that generates an image of a face region of a worker performing an operation in the operation area based on the moving image, a statistical information generator that generates statistical information for the operation performed by the worker based on the moving image, a data generator that generates data including the generated image of the face of the worker linked to the generated statistical information for the operation performed by the worker, and an output unit that outputs the generated data.

A numerical control device comprises: a tool shape information storage/generation unit that generates and stores, as tool shape information, geometrical information relating to the shape of a multi-edge tool for turning; a machining shape information generation unit that generates machining shape information from relative movement direction information pertaining to the workpiece and the multi-edge tool and from positional relation information pertaining to the workpiece and the multi-edge tool; an edge direction determination unit that determines, from the generated tool shape information and the generated machining shape information, the edge direction of the multi-edge tool for each machining shape change point at which the machining shape changes; and a machining control unit that, on the basis of the edge direction of the multi-edge tool for each machining shape change point, controls the turning while changing the edge direction of the multi-edge tool between machining shape change points.

The present invention relates to an equipment diagnosis method using equipment diagnosis system comprising: an imaging module (110) for collecting image data by photographing the equipment having an equipment controller, in which a PLC is loaded, embedded therein; a diagnostic module (120) including hardware having software for diagnosing whether the equipment is normal or abnormal; and a plurality of IoT sensor units (130) for monitoring an object to be monitored, and thus a user can quickly diagnose, identify, and cope with a specific cause of an equipment failure on the basis of objective data provided from a PLC memory area, and image file, and an IOT sensor unit at the occurrence of various types of events generated by a diagnostic module for each condition designated by the user according to the state of equipment.

This disclosure relates to a system and method for custom made medical devices life cycle management, the life cycle management of the medical devices include tracking of material and procedure to be used in additive manufacturing of the medical device and analyzing design risk as per the raw material and the design specification. Further, it includes to identify potential hazards based upon the materials, their interactions and effect on process to be followed. An artificial intelligence (AI) enabled model is trained with one or more sample datasets pertaining to a plurality of materials to be used in the additive manufacturing to audit design, to determine materials to be used, and to generate a unique code to be used to label the manufactured medical device. A smart contract of blockchain is configured to record received input and update with new points for regulatory compliance.

This disclosure relates to a system and method for custom made medical devices life cycle management, the life cycle management of the medical devices include tracking of material and procedure to be used in additive manufacturing of the medical device and analyzing design risk as per the raw material and the design specification. Further, it includes to identify potential hazards based upon the materials, their interactions and effect on process to be followed. An artificial intelligence (AI) enabled model is trained with one or more sample datasets pertaining to a plurality of materials to be used in the additive manufacturing to audit design, to determine materials to be used, and to generate a unique code to be used to label the manufactured medical device. A smart contract of blockchain is configured to record received input and update with new points for regulatory compliance.

The disclosure provides an industrial Internet of Things for identifying and processing manufacturing problems, a control method, and a storage medium. The method includes an industrial Internet of Things for identifying and processing manufacturing problems. The industrial Internet of Things includes an acquisition module, a problem type determination module and a problem solving module, the acquisition module is configured to obtain equipment information and data of product manufacturing problems; the problem type determination module is configured to determine a problem type at least based on the data of the product manufacturing problems; and the problem solving module is configured to determine problem processing data based on the problem type, and solve the problem based on the problem processing data.