A nesting and shear cutting preprocessing method for a defective plate, comprising the following steps: acquiring plate information of a plate, wherein the plate information includes defect information and plate dimension information; making an electronic defect map according to the defect information and the plate dimension information, and partitioning out a region available for nesting and shear cutting; and partitioning the plate to obtain small plates according to the region available for nesting and shear cutting. A nesting and shear cutting layout method for a defective plate, a nesting and shear cutting production optimization method for a defective plate, and a system, a computing device, a storage medium therefor. The preprocessing method and the system can reduce the scrap rate of plate processing.

Provided is a collaborative-robot risk assessment guidance device (1) including: an input device (2) that receives inputs from a user; a storage device (3) that stores information; a display device (4) that displays the information; and at least one processing device (5), wherein the processing device (5) prompts the user to input, by means of the input device (2), basic information including conditions for collaborating with people, prompts the user to select, by means of the input device (2), at least one candidate information item for hazard sources stored in the storage device (3) in association with the input basic information, performs a risk assessment on a basis of risk specifics information stored in the storage device (3) in association with the selected candidate information item for the hazard sources, determines whether a result of the risk assessment is at or below an acceptable risk, and displays, on the display device (4), countermeasure proposals for separating people and a collaborative robot without partitioning a space therebetween in a case in which the result of the risk assessment is not at or below the acceptable risk.

Control of a facility is performed in accordance with a common action plan. Further, a plurality of controllers provided in the facility are caused to control the facility in coordination. A control coordination apparatus includes a control information generation unit and a control information transmission unit. The control information generation unit generates control data which include information for specifying a control content of the facility to be controlled by the plurality of controllers and are received by each of the controllers, from an action plan file which includes an action plan made by an action plan generation apparatus and is generated by the action plan generation apparatus. The control information transmission unit transmits the control data to each of the controllers on the basis of facility design information including information on connection with the facility.

A method for optimizing production of sheet-metal parts, the production comprising cutting out and singularizing the sheet-metal parts and bending the sheet-metal parts, wherein the method includes: (A) training a neural network, which is executed on a Monte Carlo tree search framework, by means of supervised learning and self-play with reinforcement learning; (B) recording constraints for the sheet-metal parts, the constraints comprising geometric data of the sheet-metal parts; (C) creating an optimized production schedule by way of the neural network; and (D) outputting the production schedule.

A method for optimizing production of sheet-metal parts, the production comprising cutting out and singularizing the sheet-metal parts and bending the sheet-metal parts, wherein the method includes: (A) training a neural network, which is executed on a Monte Carlo tree search framework, by means of supervised learning and self-play with reinforcement learning; (B) recording constraints for the sheet-metal parts, the constraints comprising geometric data of the sheet-metal parts; (C) creating an optimized production schedule by way of the neural network; and (D) outputting the production schedule.

A system for assisting the design of manufactured components requiring post-processing and comprising an input module receiving original design data relative to engineering requirements of a component and manufacturing and post-processing data relative to the component. The system also comprising a compensation determination module receiving the original design data and the manufacturing and post-processing data from the input module, predicting the geometrical deviations created by the at least one post-processing procedure and generating dimension compensation data defining compensations for each one of the features of the component using at least one machine learning model generated by a machine learning algorithm trained using a training dataset. The system further comprises a compensated model generation module configured to receive the compensation data and to generate a compensated Computer Assisted Design (CAD) model therefrom. A computer implemented method for assisting the design of manufactured components requiring post-processing is also provided.

A method for generating a material for a partial replacement includes receiving an image of a sample of an original material needing to be replaced, generating a representative data set for the original material based on the image received, accessing a reference database comprised of a plurality of different materials and including reference texture data or reference characteristic data for each of the plurality of different materials, comparing the representative data set to the reference data in the reference database, identifying at least one of the plurality of different materials correlated to the representative data set, determining the identified correlated material is not available, sending a request to generate a replacement material, and generating the replacement material.

A method for generating a material for a partial replacement includes receiving an image of a sample of an original material needing to be replaced, generating a representative data set for the original material based on the image received, accessing a reference database comprised of a plurality of different materials and including reference texture data or reference characteristic data for each of the plurality of different materials, comparing the representative data set to the reference data in the reference database, identifying at least one of the plurality of different materials correlated to the representative data set, determining the identified correlated material is not available, sending a request to generate a replacement material, and generating the replacement material.

The confidentiality of data is maintained in a case where analysis of an operation state of a facility is entrusted to the outside. An embodiment of the present invention is configured to chronologically store log data in a first storage medium, and store attribute information indicating a relevance between a type of a failure expected to occur in a facility and each of a plurality of data users; The embodiment is further configured to select, at the occurrence of a failure in the facility, a data user who has a relevance to a type of the failure from among the plurality of data users based on the attribute information, selectively read log data relating to an operation state of the facility in which the failure has occurred, and transmits the read log data to the selected data user.

The confidentiality of data is maintained in a case where analysis of an operation state of a facility is entrusted to the outside. An embodiment of the present invention is configured to chronologically store log data in a first storage medium, and store attribute information indicating a relevance between a type of a failure expected to occur in a facility and each of a plurality of data users; The embodiment is further configured to select, at the occurrence of a failure in the facility, a data user who has a relevance to a type of the failure from among the plurality of data users based on the attribute information, selectively read log data relating to an operation state of the facility in which the failure has occurred, and transmits the read log data to the selected data user.