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.

System and method that includes mapping temperature values from a two dimensional (2D) thermal image of a component to a three dimensional (3D) drawing model of the component to generate a 3D thermal model of the component; mapping temperature values from the 3D thermal model to a 2D virtual thermal image corresponding to a virtual thermal camera perspective; and predicting an attribute for the component by applying a prediction function to the 2D virtual thermal image.

The present disclosure relates to diagnosing a fault in an electric drive of a process plant. The fault diagnosis method includes receiving fault data from an electric drive upon occurrence of the fault. The method further includes obtaining a fault code and a drive type associated with the electric drive from the fault data. In addition, the method comprises determining one or more drive parts to replace by comparing the fault code and the drive type with a mapped data for a plurality of drive types. The mapped data for each drive type includes a relation between a plurality of fault codes and a plurality of drive parts. The method further includes initiating a maintenance operation involving replacement of the one or more drive parts to address the fault.

Techniques monitor machinery for the production or treatment of synthetic fibers. Such techniques involve constant generation and recording of system messages of machine components and control components. Such techniques further involve continuous storage of the system messages as log data in a log memory. Such techniques further involve readout, preprocessing and analysis of the log data with the aid of algorithms based on statistical procedures and machine learning methods in order to identify frequent sequences of system messages and/or an anomaly.

A method for correlating data from different sensors for product lifecycle management includes receiving sensor information from an additional sensor of a plurality of sensors of an industrial operation. The additional sensor is different from component sensors used for functionality of a component of the industrial operation. Sensor information from the additional sensor monitors conditions of a portion of the industrial operation different from sensor information of the component sensors used for the functionality of the component. The method includes deriving, using the sensor information, a correlation between an operational parameter of the component and sensor information of the additional sensor. The operational parameter is related to a predicted operational lifetime of the component. The method includes identifying an abnormal operating condition of the component based on a comparison between additional sensor information from the additional sensor and the operational parameter, and sending an alert with the abnormal operating condition.

There is provided a configuration at least including a screen control part configured to display on a display part a maintenance component management screen displaying a component, a mechanism, or both, as a maintenance component, a collection part configured to collect component data related to the maintenance component, a determination part configured to compare a cumulative value of the component data with a predetermined threshold value to determine the cumulative value exceeding the threshold value, a calculation part configured to calculate a replacement time, and an operation part configured to calculate replacement times based on an average value of the component data and a cumulative value of the component data for each predetermined cycle, display the maintenance component sequentially from the maintenance component reaching the earliest replacement time, and display the maintenance component on the display part in a state where the component data is updated for the predetermined cycle.

One illustrative method comprises retrieving a set of drive information associated with an operation of an electric drive in a time period from a drive control unit and one or more sensor units. The method further includes obtaining reliability information associated with the electric drive from a server. The reliability information is computed in the server, with the set of drive information and a model corresponding to a drive type of the electric drive. The reliability information includes a probability of occurrence of the abnormal condition in a specified future time period. The method further includes, providing at least one condition indication regarding the abnormal condition to one of a human machine interface and a drive controller based on the probability of occurrence of the abnormal condition.

Provided is a load data analysis method for analyzing, based on a rainflow method, load data indicative of a load irregularly and repeatedly applied to an object. The load data analysis method comprises: a first step of acquiring a given amount of load data, and calculating a frequency/frequencies regarding a load amplitude of a load applied to the object and/or a load average, based on the rainflow method, by using load data satisfying a given condition among the given amount of load data; a second step of storing load data failing to satisfy the given condition among the given amount of load data; and a third step of combining the load data stored in the second step with newly-acquired load data to generate the given amount of load data for executing the first step, wherein the first to third steps are repeatedly executed.

A method is provided for assessing health of a mechanical system. The method includes receiving discontinuous system data that is obtained intermittently and is associated with health of the system and generating a discontinuous health index that is based on the discontinuous system data and receiving continuous system data that is obtained continuously and is associated with the health of the system and generating a continuous health index that is based on the continuous system data, wherein the discontinuous health index and the continuous health index are configured to be combinable. The method further includes combining the discontinuous health index and the continuous health index, generating an overall health index based on the combination of the discontinuous health index and the continuous health index, and automatically taking one or more actions to maintain or improve health of the mechanical system and/or avoid risk based on the overall health index.

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.