A collection device includes a state correlation information storage unit that stores state correlation information indicating correlative relationships between control information relating to control of an industrial machine and environment information relating to the environment of the industrial machine, a control information acquisition unit that acquires control information from the industrial machine, an environment information acquisition unit that acquires environment information relating to the environment of the industrial machine, a state inference unit that infers the current state of the industrial machine on the basis of the control information, the environment information, and the state correlation information, and a proxy response unit that responds to an inquiry from another device on behalf of the industrial machine on the basis of the inferred state of the industrial machine.

A diagnostic apparatus (10) diagnoses the existence of an abnormality in a tool for processing of a processing target by each of multiple working machines. The diagnostic apparatus (10) includes an acquirer (110) and a diagnoser (160). The acquirer (110) acquires program identification information identifying a program executed in each of the working machines, tool information indicating a type of the tool applied to processing, and transition information indicating transition of load in the working machine from the start to the end of the processing executed by execution of the program, at execution of the processing in the working machine. The diagnoser (160) diagnoses whether an index value of the load obtained from the transition information is out of a predetermined range corresponding to a combination of the program identification information, the tool information, and machine information identifying the working machine that transmits the transition information.

When a general-purpose operation part (22, 23) is hidden by a window part (24), it becomes hard for an operator to visually check an association state between a field device (10A, 10B) and a hardware switch (3). If such a display state has occurred, an HMI server (5) stops a health check signal which is being output to a PLC (6). The PLC (6) detects the stop of the health check signal and forcibly cancels the association state between the field device (10A, 10B) and the hardware switch (3). Thus, a human error can be prevented.

An analysis device includes: a first acquisition unit that acquires data indicating a first time zone in which each product stays in each of a plurality of processes; a second acquisition unit that acquires data indicating a second time zone in which a worker stays in each of the plurality of processes; an analyzer that analyzes a work situation for each product in each of the plurality of processes; and a providing unit that provides an analysis result. The analyzer determines, on the basis of a relationship between the first time zone and the second time zone in a period for analysis of a process for analysis, whether or not a factor that decreases work efficiency has occurred in the period for analysis of the process for analysis.

A control system for evaluating residual operating life of a machine component of a machine tool includes a sensor and a control system. The sensor is disposed on the machine tool and is configured to sense movement of the machine component. The control device is configured to calculate a length of time based on a sense signal received from the sensor and sampled at a time point right after the machine component is freshly oiled, and to enable output of an alarm when determining that the length of time thus calculated is smaller than a predetermined length.

An on-machine monitoring system for the failure state of the rotating tool and a detection method thereof are provided. The monitoring system includes a detector, a data processing controller, a tool data server, and a Hall current sensor. A tool diameter and a tool length are determined according to image sequences of a tool. A wear state and a breakage state of the tool are determined according to the tool diameter and the tool length. A spindle current signal is acquired by the Hall current sensor. And an edge chipping state and a breaking state of the tool are determined according to the spindle current signal.

Traditional infrastructure monitoring systems have the disadvantage that they either fail to consider dependency between metrices or consider the dependency only at an abstract level, which adversely affects efficiency with which a performance assessment of the infrastructure being monitored can be carried out. Another disadvantage of the existing systems is that manual intervention is required at different stages of the infrastructure monitoring. The disclosure herein generally relates to infrastructure monitoring, and, more particularly, to a method and system for identifying correlation between metrices in the infrastructure. The system uses a hybrid correlation approach which considers determining a dominant correlation from among a direct correlation and a chained correlation that may exist between each pair of metrices being considered at a time for determining the correlation.

Systems, methods, and control units for diagnosis and life prediction of one or more electro-mechanical system are provided. One method includes receiving sensor data from a plurality of sensors associated with operation of the electro-mechanical system. The method includes determining at least one system response associated with at least one failure mode of the electro-mechanical system from the sensor data, wherein the sensor data is indicative of the at least one failure mode of the electro-mechanical system. The method further includes receiving at least one simulated response associated with the at least one failure mode of the electro-mechanical system, wherein the at least one failure mode is simulated on a system model of the electro-mechanical system. The method includes generating a hybrid model of the electro-mechanical system in real-time based on the at least one system response and the at least one simulated response, wherein the hybrid model combines the at least one system response and the at least one simulated. The method also includes generating a diagnosis of the electro-mechanical system based on the hybrid model, wherein the diagnosis includes identification of one or more failures in the electro-mechanical system and wherein the one or more failures indicates initiation of degradation of the one or more electro-mechanical system. The method includes predicting a life trend of the electro-mechanical system based on the diagnosis.

A tool insert for a machine, in particular a cutting, punching and/or folding machine, is disclosed. The tool insert (24) has an identification element (38) comprising tool information about the type of the tool insert (24) and/or about the area of application of the tool insert (24). The identification element (38) is machine-readable such that the tool information is transmitted to the machine when the machine reads out the identification element. Further, a machine, a machine system and a method for operating a machine are disclosed.

An automatic inspection system includes a wireless slave device and a wireless master device. The wireless slave device includes a sound collection unit that collects sound generated from an inspection target object, an analysis unit that analyzes the collected sound to obtain a degree of difference between the collected sound and normal sound learned in advance and sound state information of the collected sound, as an analysis result, a wireless communication unit that wirelessly transmits data including the analysis results to a wireless master device, and a power supply unit that supplies power to the sound collection unit, the analysis unit, and the wireless communication unit. The wireless master device is configured to perform processing of receiving and managing the data from the wireless slave device, and transmitting the analysis result extracted from the data to a monitoring terminal that monitors a state of the inspection target object.