A device for estimating a cause of a mounting error includes a first determination section configured to perform a process of determining whether the error occurrence status is biased under a condition that an individual as the first factor is specified according to a difference in the second factor, on each of multiple individuals as the first factor, a second determination section configured to perform a process of determining whether the error occurrence status is biased under a condition that an individual as the second factor is specified according to a difference in the first factor, on each of multiple individuals as the second factor, and a cause estimation section configured to estimate a causative individual causing the mounting error based on determination results in the first determination section and the second determination section.

According to one embodiment, an estimation device acquires a data set from history data. The history data includes a plurality of data IDs, path information, first and second qualitative variables. The data IDs respectively indicate a plurality of data flowing through a plurality of nodes. The path information indicates a path of the nodes for each of the data. The first and second qualitative variables are mutually-independent and indicate classifications of each of the data IDs. The data set includes a part of the data IDs having a first variable value assigned as the first qualitative variable. The estimation device estimates an overall relevance indicating a relevancy to the data set for each of the nodes. The estimation device generates a plurality of partial data sets. The estimation device estimates a partial relevance indicating a relevancy to each of the partial data sets for each of the nodes.

Power systems are disclosed. The power system may include at least one computing device in communication with a control circuit including a plurality of electrical loops. The computing device(s) may be configured to test each of the plurality of electrical loops of the control circuit by performing processes including configuring a first electrical loop in a first electrical setting by adjusting an operational characteristic of one or more electrical switch(s) of the first electrical loop. The processes may also include determining an actual electrical status of the first electrical loop in the first electrical setting based on whether a relay of a return line in the first electrical loop detects a supplied voltage. Additionally, the computing device(s) may detect a fault in the first electrical loop in response to the determined actual electrical status of the first electrical loop differing from an expected electrical status of the first electrical loop.

An operation monitoring device includes an analytical data obtaining unit for obtaining analytical data that contain history information of a machine; a non-operation reason analysis unit for analyzing the state of the machine by classifying the state of the machine for every predetermined time as either of an operating state and a plurality of kinds of non-operating states, based on the analytical data, the operating state being a state in which the machine is operating, and the non-operating states being classified based on a reason for non-operation; a storage unit for storing an analysis result storage database that stores the result of analysis; a display unit for presenting to a user the result of the analysis; and a correction unit for correcting the result of the analysis according to an instruction from the user.

The disclosure provides an industrial Internet of Things for identifying and processing manufacturing problems, a control method, and a storage medium. The method includes an industrial Internet of Things for identifying and processing manufacturing problems. The industrial Internet of Things includes an acquisition module, a problem type determination module and a problem solving module, the acquisition module is configured to obtain equipment information and data of product manufacturing problems; the problem type determination module is configured to determine a problem type at least based on the data of the product manufacturing problems; and the problem solving module is configured to determine problem processing data based on the problem type, and solve the problem based on the problem processing data.

Computer-implemented methods for fault diagnosis in an industrial environment generally includes processing the plurality of sensor data values to determine a recognized pattern therefrom; retrieving at least one industrial-environment digital twin corresponding to the industrial environment, the at least one industrial-environment digital twin comprising a plurality of component digital twins, with each of the plurality of component digital twins corresponding to one of the plurality of components in the industrial environment, and wherein the at least one industrial-environment digital twin and the plurality of component digital twins are visual digital twins that are configured to be rendered in a visual manner; and rendering the at least one industrial-environment digital twin and the at least one respective component digital twin corresponding to the particular component in the client application in response to the received request and based on the operational condition of the particular component.

According to the embodiments of the present disclosure, there is provided a method and device of detecting fault in production, and a computer readable storage medium. The method includes: determining whether a plurality of production paths in a production line are faultless in one or more production batches, based on production record data; and determining at least one of the plurality of production paths to be faulty, at least partially based on whether the plurality of production paths are faultless in the one or more production batches.

Computer-implemented methods for fault diagnosis in an industrial environment generally includes processing the plurality of sensor data values to determine a recognized pattern therefrom; retrieving at least one industrial-environment digital twin corresponding to the industrial environment, the at least one industrial-environment digital twin comprising a plurality of component digital twins, with each of the plurality of component digital twins corresponding to one of the plurality of components in the industrial environment, and wherein the at least one industrial-environment digital twin and the plurality of component digital twins are visual digital twins that are configured to be rendered in a visual manner; and rendering the at least one industrial-environment digital twin and the at least one respective component digital twin corresponding to the particular component in the client application in response to the received request and based on the operational condition of the particular component.

A monitoring apparatus for the identification of anomalies and degradation paths in a machine tool is disclosed. The monitoring apparatus includes a control system interfaceable with a machine tool and configured for making the machine tool execute a predetermined cycle of operations; a recording system interfaceable with a plurality of sensors in the machine tool, wherein the recording system is configured for collecting operation data of machine tool during the predetermined cycle of operations; and an analysis system configured for receiving the operation data and for executing a statistical and data mining analysis on the operation data, comparing a pattern of the operation data with a predetermined pattern, for identifying any anomalies and degradation paths.

The present invention concerns a method and a system for detecting malfunctions in an apparatus and/or defects in a workpiece processed by said apparatus. The method provides for acquiring a sound signal emitted by an apparatus during an operation cycle of the same, then comparing the sound signal with a plurality of audio tracks stored in a memory area for determining a malfunction of the apparatus and/or a defectiveness of the workpiece processed by the apparatus based on the result of said comparison. The operation cycle is subdivided into a plurality of work phases and during the acquisition of the sound signal a work phase of said plurality of work phases is identified. Each audio track of the plurality of stored audio tracks comprises an audio component relating to acquired sound signals, and additional information data comprising at least one identifier of the work phase executed by the apparatus during the acquisition of the sound signals of the audio component. The plurality of audio tracks used for the comparison with the sound signal is a group of audio tracks of the plurality of audio tracks whose identifier of the work phase of the apparatus corresponds to the identified work phase. The identification data of the audio tracks additionally comprise at least one identifier of a plurality of components activated during the phase to which the audio component refers, and it is further provided for a) identifying a plurality of components activated during the identified work phase, b) on the basis of the plurality of activated components, identifying a set of comparison phases among the plurality of phases of the operation cycle, and c) identifying as defective at least one component between the plurality of components activated during the work phase and/or the workpiece, on the basis of the audio tracks relating to the set of comparison phases identified and/or on the basis of sound signals acquired during the identified comparison phases.