A medium conveying apparatus includes a conveying unit including a conveyance roller to convey a medium and a processor. The processor detects a skew of a medium conveyed by the conveying unit, calculates an occurrence frequency of skew based on a detection result, and outputs a first notification related to maintenance of the conveyance roller or a second notification not related to the maintenance based on the occurrence frequency.

A monitoring system for an industrial operation having one or more machines, the monitoring system operates to obtain operational information comprising performance operating parameters and uses the operational information to create an operational baseline and reference thresholds and monitors real-time operational data to determine if an operating parameter exceeds a reference threshold.

A production planning system (6) for a raw materials industry plant (ANL), which determines the production planning data (Pi) thereof and specifies said data to the automation system (1) of the plant (ANL). A state monitoring system (7) determines previous and future anticipated states (Z1) of components of the plant (ANL). A quality determination system (8) determines states (Z2) of output products (Ai) produced and still to be produced by the plant (ANL) and/or past and future states (Z3) of the plant (ANL) as a whole. A maintenance planning system (9) and/or the production planning system (6) receive, from the state monitoring system (7), the states (Z1) of the components of the plant (ANL), determined by the state monitoring system (7) and, from the quality determination system (8), the states (Z2 and Z3) of the output products (Ai) and/or of the plant (ANL) as a whole, determined by the quality determination system (8). They consider the data received from the state monitoring system (7) and from the quality determination system (8) in the determination of maintenance planning data (W) and/or the production planning data (Pi).

A data processing method includes a sampling step of obtaining time series data based on a measurement result of a physical quantity in a substrate processing apparatus, an evaluation value calculation step of obtaining an evaluation value of the time series data by comparing the time series data with reference data, and a sampling period control step of controlling a sampling period used in the sampling step for each time series data. In the sampling period control step, all sampling periods are controlled to a normal period in an initial state, and when the evaluation value of the time series data is abnormal, the sampling period used when obtaining the time series data is controlled to an abnormal period shorter than the normal period.

Methods, systems, and devices for analyzing vibration data and for identifying and tracking vibration anomalies in industrial machines are described. In various embodiments, the system described herein collects, transforms, and analyzes sensor data from one or more machines, such as industrial machines. The system may identify one or more sensors that are experiencing vibrational anomalies. In various embodiments, the system: collects and analyzes vibration data for a set of one or more vibration-related sensors of one or more industrial machines; determines an occurrence of one or more anomalies based on the vibration data as compared to a threshold; tracks anomalies in collected vibration data for the one or more industrial machines of the facility; generates a report of vibration data for the one or more vibration-related sensors of the facility; and reports industrial machines in the facility that may deviate from a target performance.

Multiple component mounters that configure multiple user-side component mounting lines and a support-side information server are connected so as to be able to communicate with each other via a network. The support-side information server includes an information registration section collecting and registering failure information generated in the multiple user-side production devices and updating and registering failure avoidance information as a failure avoidance method becomes apparent, and an information distribution section distributing the failure information and the failure avoidance information to the user-side production devices. Each user-side production device includes an information receiving section receiving the failure information and the failure avoidance information from the support-side information server, and an information transmitting section transmitting to a user-side production manager the failure information and the failure avoidance information related to a failure that may occur at a production device managed by the production manager.

A diagnostic device (10) includes an acquirer (101) and a diagnoser (140). The acquirer (101) acquires a plurality of input signals including a target signal to be diagnosed for abnormality. The diagnoser (140) diagnoses, using a first index value relating to the target signal and a second index value relating to the plurality of input signals based on a correlation between the plurality of input signals, whether an abnormality occurs. The first index value indicates a degree of similarity of a waveform of the target signal to a predetermined reference waveform. The second index value is a value that is based on comparison between the target signal and a predetermined pattern and is calculated from values of the plurality of input signals.

A data processing method includes a period setting step of obtaining a rising period, a stable period, and a falling period with respect to time series data obtained in a substrate processing apparatus, an evaluation value calculation step of obtaining an evaluation value in the rising period, an evaluation value in the stable period, and an evaluation value in the falling period as an evaluation value of the time series data. In the period setting step, a period from when a control signal changes until the time series data falls within a first range including a target level is obtained as the rising period, a period from when the control signal changes until the time series data falls within a second range including an initial level is obtained as the falling period, and a period between the rising period and the falling period is obtained as the stable period.

Provided is an analyzing method using a platform for analyzing health of a heavy electric machine. The method includes inputting on-site diagnosis information in which pieces of data collected in a site are received in a state in which operation of the heavy electric machine stops, collecting pieces of online sensor data in which pieces of data of installed sensors are periodically/discontinuously collected through a sensor module and a data collection module, building a database using the data in the inputting of the on-site diagnosis information and the data in the collecting of the pieces of online sensor data, analyzing of the current standard health of the heavy electric machine, and automatically determining a diagnosis result.

2Systems and methods described herein use context-adaptive resolution to achieve lossless transfer of critical industrial control system data. Bandwidth and storage optimization is achieved for time-series data generated or collected by an industrial control system and transmitted through a network to a remote historian system. The control system may be implemented through one or more embedded historians and local historians. The control system continuously processes input data, computes output variables, and generates an event trigger when a set of variables meet pre-defined set of conditions. When there are no active event triggers, the control system publishes time-series data for a pre-defined set of variables at a lower resolution to conserve bandwidth and storage. When an event trigger is activated, the control system publishes recent and current time-series data for a subset of the variables to subscribers at a higher resolution.