The present invention provides a rotating machinery diagnosis and monitoring device and method which have high reliability and enable the grasping of a symptom trend of vibrations and a determination of progress of the vibrations during increase and decrease in the rotation speed of a rotor. A rotating machinery diagnosis and monitoring device of the present invention, comprising: an input section that receives vibration values and rotation speeds as operation data of a rotating machine; a computing section that performs computations using the operation data received; and a calculator that includes an output section. The computing section is configured to identify peak values of the vibration values and evaluate each of magnitude of the peak values and the rotation speeds at the peak values. The output section is configured to display externally a result of evaluations performed by the computing section.

Various embodiments of the teachings herein include an apparatus for identifying a smoke event in an electron beam melting installation comprising: a current meter measuring a grounding current; and a processor programmed to identify a smoke event by evaluating the grounding current.

Provided is a life evaluating device that evaluates the life of a lubricant in a machine including a motor and a transmission mechanism that is lubricated by the lubricant and transmits power of the motor to a movable unit. The life evaluating device includes a motor-heat-value calculating unit that calculates a motor heat value on the basis of a current value of the motor, a frictional-heat-value calculating unit that calculates a frictional heat value in the transmission mechanism on the basis of rotating speed of the motor and a coefficient of friction of the transmission mechanism, a lubricant-temperature estimating unit that estimates temperature of the lubricant on the basis of the calculated frictional heat value and the calculated motor heat value, and a life estimating unit that estimates the life of the lubricant on the basis of the estimated temperature of the lubricant and information concerning impurities in the lubricant.

A monitoring device monitors a status of a process in a production line in separate unit tasks. The production line includes a plurality of processes. The unit tasks form the process. The monitoring device includes an operational condition acquisition section, a determination section, and an output section. The operational condition acquisition section acquires, on a per-unit task basis, operational conditions of a device being used in the tasks. The determination section determines whether or not the acquired operational conditions are appropriate based on preset reference values. The output section outputs, on a per-unit task basis, information as to whether or not the process is being appropriately performed, based on results of the determination.

A computer-implemented method for training a classifier, particularly a binary classifier, for classifying input signals to optimize performance according to a non-decomposable metric that measures an alignment between classifications corresponding to input signals of a set of training data and corresponding predicted classifications of the input signals obtained from the classifier. The method includes providing weighting factors that characterize how the non-decomposable metric depends on a plurality of terms from a confusion matrix of the classifications and the predicted classifications, and training the classifier depending on the provided weighting factors.

A monitoring system for an industrial operation having one or more machines, the monitoring system operates to obtain operational information comprising performance operating parameters and uses the operational information to create an operational baseline and reference thresholds and monitors real-time operational data to determine if an operating parameter exceeds a reference threshold.

A diagnostic apparatus includes a control unit configured to control a diagnostic operation for driving a belt, a first tension calculation unit configured to perform, based on data obtained from the diagnostic operation, a calculation to estimate a first belt tension value that is a tension value of the belt when the belt is not worn, a second tension calculation unit configured to calculate a second belt tension value in a case where a tension reduction factor of the belt and a wear factor of the belt are included, and a third tension calculation unit configured to calculate the degree of wear of the belt based on the first belt tension value and the second belt tension value. Accordingly, the diagnostic apparatus can support estimation of the degree of wear of a belt or abnormality diagnosis.

Device for detecting highly stressed positions in a machining tool with a spindle head and a spindle motor, the device comprising: a measuring unit adapted to acquire measurement values of the spindle head during operation of the spindle unit, the measurement values having a current position of the spindle head; a memory unit adapted to store the measurement values acquired; a stress determining unit adapted to determine an associated stress value for each of the detected positions taking into account the measurement values; and an output unit adapted to at least one of outputting the detected positions with the respective associated stress value, and determining from a total number of the determined stress values at least one high stress value which is greater than the other stress values of the total number, and then outputting the at least one determined high stress value with the position assigned to it.

Methods, systems, and devices for analyzing vibration data and for identifying and tracking vibration anomalies in industrial machines are described. In various embodiments, the system described herein collects, transforms, and analyzes sensor data from one or more machines, such as industrial machines. The system may identify one or more sensors that are experiencing vibrational anomalies. In various embodiments, the system: collects and analyzes vibration data for a set of one or more vibration-related sensors of one or more industrial machines; determines an occurrence of one or more anomalies based on the vibration data as compared to a threshold; tracks anomalies in collected vibration data for the one or more industrial machines of the facility; generates a report of vibration data for the one or more vibration-related sensors of the facility; and reports industrial machines in the facility that may deviate from a target performance.

A substrate processing method includes loading an operation list of substrate, the operation list including an operation site bar, an inspection site bar, and an operation flag record enabling bar, the operation site bar including a plurality of operation sites, and the inspection site bar including an inspection site; loading a substrate onto a production line; when the substrate flows to an operation site on the production line, inquiring the operation site at the operation site bar of the operation list, and judging whether the operation site is provided with an inspection site at the inspection site bar; if the operation site is provided with an inspection site at the inspection site bar, verifying whether a current operation flag of the substrate matches the inspection site; if the current operation flag of the substrate matches the inspection site, processing the substrate at the operation site.