To provide a data management apparatus, a data management method, and a data management program capable of restricting the output of machine information to an external location according to the level of confidentiality of each piece of machine information. An edge server that provides machine information in a factory to an external location includes an execution unit configured to execute an application referring to a database storing the machine information, a setting unit configured to acquire lists of transmission destinations and transmission items defined for each application and set, as transmission conditions, a transmission destination and a transmission item permitted by a user from the lists, a data processing unit configured to sort out transmitted data output from the application according to the transmission conditions, and a transmission and reception unit configured to transmit the transmitted data processed to the external location.

The purpose of the present invention is to provide a method for constructing a digital twin, enabling real-time monitoring, operation improvement, and coping with the occurrence of an accident in an industrial site by combining reduced order models of a multiphysical system, measurement data and artificial intelligence techniques, and the method for constructing a digital twin, according to the present invention, comprises: a network-defining step of defining a multiphysical engineering system as a network constituted by a combination of element facilities; an element model establishing step of establishing a relation-based 0-dimensional (0-D) model for each of the element facilities; a system model establishing step of closing all relations for a system by reflecting an additional relation by machine learning from a 3-dimensional computer aided engineering reduced order model (3-D CAE ROM) or data for key element facilities in the 0-D models established in the element model establishing step; a system ROM constructing step of constructing a system ROM for the system model established in the system model establishing step from calculation results for conditions sampled in an operating variable parameter space; a system ROM correcting step of minimizing an error between a model predicted value and measured data for the element facility and the system; and a real-time algorithm constructing step of constructing an algorithm for identifying an expected system state or an optimal operating condition in a virtual operating condition based on the real-time monitoring result.

A production control apparatus includes a workpiece position detection unit, an ID generation unit, an ID notification unit, a data receiving unit, and a storage unit. The data receiving unit receives the unique IDs generated by the ID generation unit and the traceability data (actual production information) when the workpieces for which the unique IDs have been generated are processed, from the manufacturing machines to which the unique IDs have been notified by the ID notification unit. The storage unit records the unique IDs and the traceability data received by the data receiving unit in association with each other.

A method of evaluating factory production machinery up time and down time performance provides a collection of sensors in individual communication with factory production machinery, with each sensor collecting high frequency vector data as respecting a physical parameter associated with the machinery, extracts the data from the sensors to produce a sensor data set, transforms the data set into the frequency domain, extracts statistical and mathematical information from the data set, transfers the data set, to an associated edge cloud, and within the associated edge cloud processes the data set to provide a repair, maintenance and operation board for the machinery to evaluate up time and down time performance for the factory production machinery.

A brake system control module for use in a brake system is provided. The brake system control module includes a reservoir tank having a brake fluid level sensor. The brake system control module automatically determines if the brake fluid level sensor detects a low fluid level in the reservoir tank and monitors a value of sensors to determine if the value of the sensors is less than or greater than evac and fill start and stop thresholds. The brake system control module further manages an evacuation and a filling of the brake system based on the value of the sensors.

Provided is a plant data display processing device including: a data classification unit that classifies operation data into categories according to similarity; an evaluation index calculation unit that calculates an evaluation index of a category from a value of the operation data; and a classification result display processing unit that calculates a representative value of the operation data for each of the categories from the operation data contained in each of the categories, maps identification information of each of the categories to two-dimensional space in accordance with similarity of a representative value of the operation data, and generates three-dimensional image data in which the identification information of each of the categories is shown on a plane formed of a first axis and a second axis, and the evaluation index of the category is shown on a third axis.

System and methods are disclosed for improving manufacturing processes, improving manufactured products, and improving deployed devices. The devices can be reconfigurable holographic antennas (antennas). Manufacturing test results for a plurality of antennas is collected. Field performance data and antenna management information is collected for a plurality of deployed antennas. Query selection criteria, machine learning correlation criteria and a minimum correlation threshold are passed to a server to query for matching records from a data store and to perform machine learning on the query results to generate improvements to processes, manufactured antenna performance and deployed antenna performance.

The present invention provides a modular system and method for real-time evaluation and monitoring of a machining production line overall performances, calculated from each given metal workpiece, consumable tool and machine. The present invention is configured for an iterative and incremental calculation and evaluation of the machining production-line overall performances, by incrementally evaluating individual workpiece's performances, consumable tools'performances and machine's performances, extracted from the data of a plurality of workpieces and machines. The present invention is further configured for comparing the workpiece's performances to a similar workpiece's best performance, extracted from the evaluation of a plurality of the data similar workpieces. The present invention is further configured for the identification of significant process faults and their cause. The present invention is further configured for the analysis of the applied engineering-plan effectiveness, using a defined engineering score.

An evaluation value prediction unit predicts an evaluation value at a time point after a given time passes from a predetermined evaluation time based on input data related to an operation of a factory at the evaluation time using a learned prediction model. The prediction model is a learned model that is learned so that the evaluation value related to the operation of the factory at a time point after the given time passes from one time point is output by inputting a plurality of kinds of data related to the operation of the factory at one time point. An evaluation value output unit outputs information related to the evaluation value.

A metal fabrication resource performance monitoring method includes collecting data representative of a parameter sampled during one or more metal fabrication operations of one or more metal fabrication resources, the one or more resources being selectable by a user from a listing of individual and groups of resources, receiving event data comprising a time that an event occurred, via at least one computer processor, determining a first analyzed system parameter from the collected data, via the at least one computer processor, populating a dashboard page with graphical indicia representative of the first analyzed system parameter before and after the event, and transmitting the dashboard page to a user-viewable display.