Provided are a diagnosing device, a diagnosing method, and a program with which it is possible to detect abnormalities accurately even if there is a small amount of data or the number of data points varies. This diagnosing device is provided with a Mahalanobis distance calculating unit which calculates the Mahalanobis distance (referred to as ‘MD value’ hereinbelow) of a detected value, and an abnormality determining unit which determines the presence or absence of an abnormality on the basis of the MD value, wherein the abnormality determining unit determines the presence or absence of an abnormality by arranging that a determination that there is no abnormality is more likely to occur if the number of samples per unit space is small than if the number of samples per unit space is large.

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.

A substrate processing system includes: an acquiring unit configured to acquire process data of each step when each step included in a predetermined process is executed under different control conditions; an extracting unit configured to divide each step into a first section in which the process data fluctuates and a second section in which the process data is converged, and extract first data belonging to the first section and second data belonging to the second section from the process data; and a monitoring unit configured to monitor the process data by comparing one or both of an evaluation value that evaluates the first data and an evaluation value that evaluates the second data with corresponding upper and lower limit values.

A diagnostic method includes: acquiring first measurement data based on a physical quantity generated by an object repeating a predetermined operation pattern in a first period; a reference data generation step of generating reference data based on the first measurement data; acquiring second measurement data based on a physical quantity generated by the object repeating the predetermined operation pattern in a second period; and a diagnosis step of diagnosing a state of the object based on the reference data and the second measurement data, in which the reference data generation step includes extracting, from the first measurement data, a plurality of pieces of first period unit data corresponding to at least a part of the predetermined operation pattern, and generating the reference data by calculating a representative value of the plurality of pieces of first period unit data subjected to synchronization processing.

A diagnostic system diagnoses an abnormality of a diagnostic object by using a plurality of diagnostic logics. The diagnostic system includes an acquisition unit, a determination unit, a generation unit, and an output unit. The acquisition unit acquires diagnostic object information relating to the diagnostic object. The determination unit determines whether each of the diagnostic logics is executable or not based on the diagnostic object information. The generation unit generates a diagnostic result including information relating to whether the diagnostic logics determined by the determination unit are executable or not. The output unit outputs the diagnostic result.

The metal tank portion of an electric water heater is protected against corrosion utilizing a corrosion protection system that detects a voltage potential between the sheath portion of a tank water-immersed electric heating element and the tank. In one embodiment of the corrosion protection system the sensed sheath/tank potential is utilized to enable a user of the water heater to accurately gauge the necessity of replacing a sacrificial anode extending into the tank. In another corrosion protection system, the sensed sheath/tank potential is utilized to provide impressed current cathodic protection of the tank and also to prevent dry firing of the electric water heater.

A system for improving drill bit performance, having processors and memory storing instructions to obtain a wear report for a drill bit, wherein the wear report includes wear characteristics of the drill bit and drill operating parameters under which the drill bit was used; compare the wear characteristics of the drill bit to a threshold for acceptable drill bit wear; and adjust drill operating parameters based on the wear characteristics of the drill bit. The instructions to obtain the wear report for the drill bit include instructions to analyze images of the drill bit to identify wear characteristics; identify wear patterns based on the wear characteristics of the drill bit; identify probable drilling conditions based on the wear patterns; and generate the wear report for the drill bit based on the images of the drill bit, the wear characteristics of the drill bit, and the probable drilling conditions.

An abnormality analysis device including: an overall information obtainer that obtains overall information indicating an overall feature amount of a manufacturing system; an overall abnormal degree calculator that calculates an overall abnormal degree that is an abnormal degree of a whole of the manufacturing system by statistically processing the overall information; an individual information obtainer that obtains individual information indicating a feature amount of each of the plurality of constituent elements; an individual abnormal degree calculator that calculates an individual abnormal degree that is an abnormal degree of each of the plurality of constituent elements by statistically processing the individual information; and a determiner that determines whether or not the overall abnormal degree exceeds a threshold value, wherein the individual abnormal degree calculator calculates the individual abnormal degree when the determiner determines that the overall abnormal degree exceeds the threshold value.

An abnormality diagnostic device includes a diagnoser configured to diagnose a type of abnormality that occurs in an abnormality diagnostic target on the basis of differences between abnormality simulation results for each type of abnormalities obtained by simulating a plurality of types of abnormalities in the abnormality diagnostic target and a plurality of time-series observation results obtained by observing the abnormality diagnostic target in time series using a plurality of detectors.

Predictive maintenance methods and systems, including a method of applying transfer entropy techniques to find a causal link between parameters; a method of applying quality weighting to context data based on a priori knowledge of the accuracy of the context data; a method of detecting a maintenance action from parameter data by detecting a step and a process capability improvement; a method of managing unattended alerts by considering cost/benefit of attending to one or more alerts over time and assigning alert expiry time and/or ranking the alerts accordingly; a method of displaying components of a complex system in a functional way enabling improvements in system diagnostics; a method of determining the time of an event indicator in time series parameter data; a method of classifying an event associated with a fault condition occurring within a system; and a method of determining whether an event recorded in parameter data is attributable to an external factor.