An abnormality determination apparatus of the present invention acquires state data from work equipment provided with an attaching part to which a plural kinds of work parts are attached in a replaceable manner, identifies the kind of a work part attached to the attaching part, sets, corresponding to the identified kind of the work part, abnormality determination data for determining an abnormality of the work equipment, acquires, from among state data acquired from the work equipment, state data of a time when the identified kind of the work part was being attached, and compares the acquired state data with the set abnormality determination data to determine an abnormality of the work equipment.

Provided are a failure classifying device, a failure classifying method, and a failure classifying program capable of specifying the causes of failures even when a controller does not generate an alarm. A failure classifying device includes: a failure unit acquiring unit that acquires a data set in which a failure unit of a machine is correlated with one or a plurality of constituent parts; a failure history acquiring unit that acquires a failure history including events of failures that occurred in the past and countermeasure parts; and a correlating unit that stores information on one or a plurality of events in correlation with the failure unit by matching the constituent part to the countermeasure part.

An abnormality determination apparatus of the present invention acquires state data from work equipment provided with an attaching part to which a plural kinds of work parts are attached in a replaceable manner, identifies the kind of a work part attached to the attaching part, sets, corresponding to the identified kind of the work part, abnormality determination data for determining an abnormality of the work equipment, acquires, from among state data acquired from the work equipment, state data of a time when the identified kind of the work part was being attached, and compares the acquired state data with the set abnormality determination data to determine an abnormality of the work equipment.

Provided are a failure classifying device, a failure classifying method, and a failure classifying program capable of specifying the causes of failures even when a controller does not generate an alarm. A failure classifying device includes: a failure unit acquiring unit that acquires a data set in which a failure unit of a machine is correlated with one or a plurality of constituent parts; a failure history acquiring unit that acquires a failure history including events of failures that occurred in the past and countermeasure parts; and a correlating unit that stores information on one or a plurality of events in correlation with the failure unit by matching the constituent part to the countermeasure part.

A system and method monitor and/or diagnose the operation of a production line of an industrial plant which is controlled by an automation system. The system includes a remote data processing server, which is installed outside of the industrial plant. The remote data processing server is configured to receive a digital input signal reflecting at least one control input signal and a digital output signal reflecting a second operational state, to determine at least first and second modeled states corresponding to the at least first and second operational states, respectively, by inputting the digital input and the digital output signals to a digital observer model of the production line and the automation system and by processing the digital observer model, and to forward the first and second modeled states to an output interface from where they can be accessed by modeling and/or diagnosing modules.