Abstract: The present disclosure provides an industrial IoT for correction and regulation of a defective product, a control method, and a storage medium. The industrial IoT includes a user platform, a service platform, a management platform, and a sensing network platform that interact in sequence. The service platform, the management platform, and the sensing network platform are all arranged in a front-sub-platform layout. The control method is applied in the industrial IoT. The industrial IoT may calculate whether a defective product is correctable according to a correction cost of the defective product, and may reduce the correction cost and a time consumption of a corresponding correction device, thereby reducing correction cost of the defective product and a loss in a manufacturing process, further ensuring a normal product manufacturing efficiency of the correction device, and thus reducing a correction loss of a waste product and the defective product.

Abstract: A method for performing bearing defect auto-detection provides an algorithm for processing condition monitoring data including vibration harmonics of at least one bearing coupled to a rotatable shaft, the bearing having an inner and an outer ring. The algorithm is used to confirm with high degree of confidence that a bearing defect is present or not.

Abstract: In an embodiment of the present invention, a memory stores case performances on anomaly handling of a plurality of apparatuses. A hardware processor performs: identification processing of identifying an anomaly cause of an abnormal apparatus in the plurality of apparatuses; selection processing of selecting an estimation model for estimating a handling method suitable for the anomaly cause from a plurality of estimation models based on the case performance of the abnormal apparatus; estimation processing of estimating a handling method suitable for the anomaly cause among a plurality of handling methods based on the selected estimation model; and output processing of outputting information indicating the estimated handling method.

Abstract: According to one embodiment, a monitoring apparatus includes a processing circuit. The processing circuit is configured to generate second data including a prediction value of a second sensor correlated with a first sensor from first data including a measurement value of the first sensor of which a measurement value changes suddenly in a case where the control signal changes, detect an anomaly of the system or an anomaly of at least one sensor, and make it difficult to detect the anomaly in a case where the determination signal indicates that there is a change in the control signal.

Abstract: Methods and systems are provided for monitoring a refrigerated cargo container in real time including receiving sensor signals from a plurality of sensors that include one or more of a temperature sensor, a humidity sensor, and a pressure sensor; and processing the sensor signals to identify one or more signal characteristics that correspond to predefined patterns, wherein the predefined patterns are correlated to one or more container conditions including at least one of an open door, a container load level, and a cargo type.

Abstract: An image forming system includes a plurality of image forming apparatuses and a server. The server is connected to the image forming apparatuses in a communicable manner. The server receives data indicating a numerical value of a common item from each of the image forming apparatuses, calculates a median of the data, and specifies an abnormal image forming apparatus from among the image forming apparatuses that has sent a numeric value of the common item that deviates the most from the median.

Abstract: Provided in the present invention is a bearing maintenance timing acquisition method: first, acquiring vibration signals of a bearing under different loads; then, respectively acquiring dimensionless parameters according to the vibration signal of each load; thus, acquiring predicted damage condition distribution data of the bearing under different loads according to the dimensionless parameters; and finally, obtaining accurate maintenance timing based on the predicted damage condition distribution data under different loads, so as to prolong the service life of the bearing while reducing maintenance costs.

Abstract: A vibration analysis apparatus includes: a storage unit storing a regression equation indicating correspondence between rotation speed change of a rotation mechanism and a peak occurrence frequency of acceleration of vibration, for each acceleration peak; an analysis unit extracting a peak occurrence frequency of acceleration of vibration for each acceleration peak, based on vibration data of the rotation mechanism and calculating, for each acceleration peak, a waveform area of the acceleration peak by integrating the acceleration peak over a specific frequency section; and an anomaly determination unit determining whether operational anomaly occurs in the rotation mechanism for each acceleration peak.

Abstract: A control apparatus includes a controller. The controller is configured to obtain a measurement value of a state of mechanical equipment corresponding to a period in which the mechanical equipment reaches a second state from a first state, extract at least one predetermined feature value by using the measurement value, and extract data for machine learning from data of the at least one predetermined feature value on a basis of a separation degree for distinguishing the first state and the second state from each other.

Abstract: Systems and methods are disclosed for voltage-less electrical signature analysis for fault protection. The systems and methods described herein may involve determining voltage values for a motor (which may then be used to estimate a speed of the motor) when complete voltage measurements may not be available, or may only be temporarily available. More specifically, the systems and methods described herein may address three scenarios, which may include at least: (1) when only a single phase voltage input is available for a three-phase motor, (2) when no voltage input is available, or (3) when a voltage input is only available for a limited period of time (for example, during a learning phase of the motor).

Abstract: The disclosure provides an approach for detecting and preventing attacks in a network. Embodiments include determining a plurality of network behaviors of a process by monitoring the process. Embodiments include generating a plurality of intended states for the process based on subsets of the plurality of network behaviors. Embodiments include determining a plurality of intended state clusters by applying a clustering technique to the plurality of intended states. Embodiments include determining a state of the process. Embodiments include identifying a given cluster of the plurality of intended state clusters that corresponds to the state of the process. Embodiments include selecting a novelty detection technique based on a size of the given cluster. Embodiments include using the novelty detection technique to determine, based on the given cluster and the state of the process, whether to generate a security alert for the process.

Abstract: Systems and methods are disclosed for predicting a remaining useful life of a component. One method comprises receiving, by a component prediction system, one or more component data sets associated with one or more components of a moving object. Based on the received one or more component data sets, environmental and operational conditions experienced over a lifetime of each failed component may be identified and summarized. Then, the effects of the environmental and operational conditions on a lifetime of a component of interest may be determined by training an accelerated failure time model using the summarized environmental and operational conditions. Using the trained accelerated failure time model, a remaining useful life of the component of interest may be determined.

Abstract: A method of detecting anomalies of a fan within an appliance includes receiving, at a service computer and/or remote server, data indicative of usage of the fan, analyzing the data indicative of usage of the fan with a machine learning model on the service computer and/or remote server, and flagging the fan for replacement when the machine learning model detects an anomaly in the data indicative of usage of the fan.

Abstract: Apparatus for binning an input value into an array of bins, each bin representing a range of input values and the bins collectively representing a histogram of input values, the apparatus comprising: an input for receiving the input value; a memory for storing the array; and a binning controller configured to: derive a plurality of bin values from the input value according to a binning distribution located about the input value, the binning distribution spanning a range of input values and each bin value having a respective input value dependent on the position of the bin value in the binning distribution; and allocate the plurality of bin values to a plurality of bins in the array, each bin value being allocated to a bin selected according to the respective input value of the bin value.

Abstract: A vehicle-mounted device for detecting battery state comprises a controller, a load unit, and a switch unit. The load unit is coupled to the battery, the switch unit is coupled between the battery and the load unit. The controller can control the switch unit to disconnect or connect the battery and the load unit at a predefined frequency. The controller can switch the load unit to generate ripple voltage on the battery, and measure the ripple voltage of each battery cell, an abnormal state of a battery can be determined according to the ripple voltage of each battery cell.

Abstract: A computer implemented method processes time waveform machine vibration data that are indicative of operational characteristics of a machine. The data, which were measured on the machine over a period of time having a begin time and an end time, are accessed from a memory or storage device. An integer number M of waveform samples are determined from the data to be averaged, and an asymptotically decaying DC bias component in the data is derived using a moving average of the M number of waveform samples. The DC bias component is extrapolated from the begin time of the waveform back to an earlier time and from the end time of the waveform forward to a later time. The DC bias component is then subtracted from the time waveform data, and a Fast Fourier Transform is performed on the data to generate a spectrum.

Abstract: This disclosure relates generally to a system and method to estimate an operational risk associated with one or more failures in at least one unit of a process plant. There is a continuous stream of operational data of several variables such as temperature, pressure, etc. Detections are defined in terms of acceptable/unacceptable ranges of parameters over a finite period and operating load of the unit. Often, these predefined parameters must be within a specified range based on operating condition of the process plant and when the measured parameters go beyond, a failure is detected. A risk priority number is estimated from number of occurrences of failure mode, average percentage change from dynamic limits with severity and degree of correlation with detectability from operational data and dynamic limits. Herein, operational risk associated with failure modes can be calculated and updated from time to time automatically from the stream of operational data.

Abstract: Embodiments are directed to a method and system of forecasting a disk drive survival period in a data storage network, by obtaining operating system data and manufacturer data for the disk drive to create a dataset, screening the dataset to identify a number of features to be selected for model creation, wherein the data set includes censored data and non-censored data, and performing, in an analytics engine, semi-parametric survival analysis on the data set using transfer learning on the model to provide a time-based failure prediction of the disk drive. A graphical user interface provides to a user the failure prediction in one of text form or graphical form.

Abstract: A diagnosis device for diagnosing a plant based on an operating state of the plant includes a monitoring data acquisition unit configured to acquire a plurality of monitoring data which are measurement values of a parameter related to the operating state of the plant measured at different times, a diagnosis target pattern generation unit configured to generate a diagnosis target pattern that is a plot pattern where each of the plurality of monitoring data is plotted against plant output data of the plant, and a pattern diagnosis unit configured to diagnose the plant based on the plot pattern of the diagnosis target pattern.

Abstract: A sensor includes a working electrode in contact with an analyte solution; an amplifier including: a source terminal; a drain terminal; a back gate terminal; and nanowires, each nanowire electrically connecting the source terminal to the drain terminal; and an insulator having a first side and a second side. The working electrode is positioned to the first side of the insulator. The source terminal, the drain terminal, and the nanowires are positioned to the second side of the insulator. The insulator prevents direct electrical contact between the working electrode, the analyte solution and either the source terminal, the drain terminal, or the nanowires. The working electrode is configured such that, when a chemical species is present in the analyte solution, a variation in an electrical field at a location of the nanowires is induced, inducing a corresponding variation in an electrical current between the source terminal and the drain terminal.

Abstract: An artificial intelligence (AI) device includes a sensing unit configured to collect operation log including information on an external environment factor and an operation state of an AI device, a memory configured to store data corresponding to the operation log, and a processor configured to provide the data corresponding to the operation log to an AI model, to acquire information about whether the AI device corresponds to a normal range or a malfunction symptom range, and to perform control based on the acquired information.

Abstract: A circuit debug apparatus for debugging an integrated circuit that causes a functional fault may include a processor configured to extract a scan pattern of a scan chain of the integrated circuit while the integrated circuit is in a scan mode. The scan pattern includes a plurality of logic states for a corresponding plurality of logic circuits of the integrated circuit. The processor may also be configured to apply a modified scan pattern to the integrated circuit while the integrated circuit is in the scan mode, where the modified scan pattern includes a test pattern configured to eliminate the functional fault. The processor may be further configured to determine whether the integrated circuit with the modified scan pattern produces the functional fault while the integrated circuit is in a functional mode.

Abstract: Systems and methods are disclosed that determine a duration and resources for testing software. In some implementations, the system performs operations including determining functions performed by applications of the software product, and determining categories based on the functions, the categories including a lowest-criticality category and a highest-criticality category. The operations also include determining degrees of change to the applications and test scripts corresponding to the degrees of change. The operations also include generating a data structure based on the categories and the degrees of change, the data structure including columns identifying the categories in an order from lowest to highest criticality. The operations also include determining weights corresponding to distances of the categories from the highest-criticality category.

Abstract: The present disclosure may provide a method. The method may include processing an image of a subject using a detection model to generate one or more detection results corresponding to one or more objects in the image; and generating an image metric of the image based on the one or more detection results corresponding to the one or more objects.

Abstract: Provided is a computer-implemented method, the method including storing a meta-model in a computer-readable storage medium, wherein the meta-model includes at least one risk element, at least one test element and at least one objective element, and associations between the elements, wherein each risk element is associated with one or more objective elements, and/or each risk element is associated with one or more test elements, wherein at least one element of the elements and/or at least one association has at least one associated risk-related parameter. A corresponding computer program product and system is also provided.

Abstract: A blood pressure measuring apparatus according to an aspect of the present invention includes: a touch sensor; a pulse wave measurer configured to measure pulse waves from a user; a contact force measurer including at least three force sensors and configured to measure a contact force between the touch sensor and the user by using the at least three force sensors; a contact area measurer configured to measure a contact area between the user and the touch sensor; and a processor configured to determine a vertical direction error, which indicates a degree of deviation of a direction of force, applied by the user to press the touch sensor, from a vertical direction to a surface of the touch sensor based on sensor values sensed by the at least three force sensors, and estimate blood pressure according to a determination result of the vertical direction error based on the pulse waves, the contact force, and the contact area.

Abstract: An apparatus as an aspect of the present invention is a factor analysis apparatus that analyzes a relationship between a target event that is a target of factor analysis and an assumed factor of the target event, and includes a similarity calculator, a first influence calculator, and a second influence calculator. The similarity calculator calculates a degree of similarity between a data item included in provided time-series data and the assumed factor. The first influence calculator calculates a first degree of influence indicating a degree of influence of the data item on the target event on the basis of time-series data of the data item and time-series data of the target event. The second influence calculator calculates a second degree of influence indicating a degree of influence of the assumed factor on the target event on the basis of the degree of similarity and the first degree of influence.

Abstract: A method for the self-check of at least one driving function of an autonomous or semi-autonomous vehicle in vehicle operation, after an error message about the at least one driving function, in which in one step, at least one vehicle electronic system and/or at least one sensor is/are restarted, a check is made for a further appearance of the error message after each restart, and in the event an error message is not repeated after the restart, the driving function in question is checked during operation of the autonomous or semi-autonomous vehicle.

Abstract: The application discloses an automatic screen state detection robot, comprising a memory having an automatic screen state detection program stored thereon and a processor, and the automatic screen state detection program being executed by the processor to implement the operations of: controlling the robot to move into a preset area of each of service devices in a self-service branch respectively; detecting whether a service device has a circuit fault or not if the robot moves into the preset area of the service device; and controlling the service device to display an image according to preset display parameters if the display screen has no circuit fault, and analyzing the image displayed on the display screen to find whether the display screen of the service device has an abnormality of a preset type. The application also provides an automatic screen state detection method and a computer-readable storage medium.

Abstract: Methods and systems are provided for operating a climate control system. In one example, a method for operating a vehicle climate control system includes modeling a pressure in a heat pump downstream of an exterior heat exchanger an upstream of an expansion valve. The method also includes operating the expansion valve to cool a vehicle cabin using the modeled pressure in conjunction with a temperature from a sensor positioned upstream of the expansion valve and downstream of the exterior heat exchanger.

Abstract: A computer-implemented method for providing explainable diagnostics for an electromechanical device. The method can include receiving data from an electromechanical device regarding a potential issue in the electromechanical device; curating the data with a machine learning model; receiving ground truth data associated with the curated data from a user of the electromechanical device; comparing the curated data with the ground truth data; and optimizing the machine learning model based on the comparing.

Abstract: A computer implemented method and apparatus for a marine vessel data system, the method comprising: receiving data from at least one sensor configured to measure vibration and operationally arranged to the marine vessel to provide time-domain reference sensor data; maintaining the time-domain reference sensor data within a data storage system; generating a Fast Fourier Transform (FFT) on the time-domain reference sensor data to provide a plurality of reference spectra files in frequency-domain, wherein each reference spectra file comprises spectra data defined by amplitude information and frequency information, and each spectra file is associated with condition information determined based on collection of the time-domain reference sensor data; normalizing each reference spectra file by converting the frequency information to order information using the condition information to provide normalized reference spectra files; and training a convolutional autoencoder type of neural network using the normalized refe

Abstract: A system and method are provided for operating and maintaining a wind turbine. Accordingly, a plurality of data inputs are received. The plurality of data inputs represent a plurality of monitored attributes of a component of the wind turbine. A consolidated risk index for the component is determined using the plurality of monitored attributes, and a range of potential risk indices is forecasted. A remaining-useful-life distribution is determined based on the damage potential and an end-of-life damage threshold. The wind turbine is shut down or idled if the remaining-useful-life distribution is below a shutdown threshold.

Abstract: A historical task database relating vehicle rollout decisions, vehicle maintenance states and subsequent deteriorations is created. A pattern analyzer may use an item-set mining algorithm on the task database to recommend whether a vehicle with its current maintenance state should be deployed. A supervisor uses this recommendation to make a rollout decision. These decisions are added to the database. Heuristic rules are defined to determine if the rollout decision was correct. The system to learns when a supervisor continues to make costly rollout errors. The system also discovers combinations of defects that lead to a rapid deterioration and makes recommendations that the vehicle be sent for maintenance rather than being rolled out.

Abstract: A gas turbine engine for an aircraft comprises an engine core comprising a turbine, a compressor, and a core shaft connecting the turbine to the compressor, wherein a compressor exit temperature is defined as an average temperature of airflow at the exit from the compressor; and a fan located upstream of the engine core, the fan comprising a plurality of fan blades extending from a hub, each fan blade having a leading edge and a trailing edge, wherein a fan rotor entry temperature is defined as an average temperature of airflow across the leading edge of each fan blade at cruise conditions and a fan tip rotor exit temperature is defined as an average temperature of airflow across a radially outer portion of each fan blade at the trailing edge at cruise conditions. A core to fan tip temperature rise ratio is in the range from 2.845 to 3.8.

Abstract: Embodiments provide techniques for estimating seasonal indices for multiple periods. Some embodiments can receive a signal comprising a plurality of measures sampled over a span of time from an environment in which one or more processes are being executed. Some embodiments may then extract a seasonal effector and a de-seasonalized component from the signal. Next, some embodiments can apply one or more spline functions to the seasonal effector to generate a first model. Some embodiments may then apply a linear regression technique to the de-seasonalized component to generate a second model. Some embodiments may then initiate actions associated with the code. Some embodiments may then generate a forecast of the signal based on the first model and the second model. Next, some embodiments may initiate, based at least in part on the forecast, one or more actions associated with the environment.

Abstract: Using an analytical model, a problem related to a product is identified from a collection of report data, the product being a three dimensional (3D) solid having a shape and produced from a manufacturing process. The problem is correlated with a set of factors. The set of factors describes a circumstance in which a user performs an operation of the product. According to a weight assigned to the problem, the problem is selected for prototyping. Using a processor and a memory, the set of factors and the operation are simulated by using a modified design of the product. In response to the modified design solving the problem, a specification of the modified design is provided for 3D printing to the user.

Abstract: Methods, systems, and devices for data attribution using frequent pattern analysis are described. In some cases, data stored at a multi-tenant database server may be analyzed to understand various interactions and patterns between data attributes associated with multiple users. The multi-tenant database server may effectively cluster and/or perform calculations on attributes of the data to understand user patterns. In some examples, the multi-tenant database server may determine a change (e.g., a probability change) in the user patterns by removing one or more attributes from the data set and re-performing the analysis. By re-performing the analysis, the multi-tenant database server may attribute a value to individual pieces and combinations of the data in order to indicate the effect that each piece of data has on the analysis.

Abstract: A heat exchanger, in particular a chiller, includes a heat exchanger block with a first fluid duct for a refrigerant and a second fluid duct for a coolant, an inlet and an outlet for the refrigerant, which are formed at a connecting flange and which are fluidically connected to the first fluid duct, a sensor for detecting a measured variable of the refrigerant, and an electronic expansion valve arranged in the inlet including an integrated regulating unit, wherein the expansion valve regulates a flow rate of the refrigerant in the inlet as a function of the detected measured variable. The sensor and the regulating unit are connected via a cable to transfer data. A port is formed at the expansion valve. The cable is further secured releasably or non-releasably in the respective port at the expansion valve. In addition, a method for controlling or regulating the heat exchanger is provided.

Abstract: A computer-implemented method, system and computer program product for identifying anomalies in data during a data outage. An anomaly detection model is built using data received from a sensor at a characterized granularity. Once a period of service occurs following a data outage, a quantum of missing data during the data outage is identified using predictive modeling if the data during the data outage is not available at the granularity in which the anomaly detection model is built. The identified quantum of missing data is retrofitted into a predicted pattern during the data outage and the analytics are then re-run on the retrofitted quantum of missing data in the predicted pattern to identify anomalies during the data outage. In this manner, anomalies in data, such as data from sensor readings, can be identified during the data outage thereby enabling the model to provide more accurate predictions of anomalies occurring during the data outage.

Abstract: Provided is a computer-implemented method, the method including storing a meta-model in a computer-readable storage medium, wherein the meta-model includes at least one risk element, at least one test element and at least one objective element, and associations between the elements, wherein each risk element is associated with one or more objective elements, and/or each risk element is associated with one or more test elements, wherein at least one element of the elements and/or at least one association has at least one associated risk-related parameter. Also provided is a corresponding computer program product and system.

Abstract: Embodiments are disclosed for determining whether a computing node is in a normal or an abnormal condition based on its characteristics relative to those of other computing nodes. In embodiments, characteristics about computing nodes (e.g., CPU resources used) are used to cluster those computing nodes, and those computing nodes that lie outside of a cluster are identified as abnormal.

Abstract: A sales data processing apparatus includes a display, a product scanner to obtain a commodity code from a product being registered in a sales transaction, a storage unit to store journal data including product information for registered. A controller is configured to record product information for products registered in the sales transaction and output a notification of an error in the sales transaction when detected. The notification is output to the display screen and includes information regarding resolution of the error. The controller executes a first countermeasure for resolving the error, then stops the sales transaction if the error is not resolved. The controller then executes a second countermeasure after the sales transaction has been stopped and starts a new transaction if the error is resolved by the second countermeasure.

Abstract: Methods and systems for detection in an industrial internet of things data collection environment with intelligent data collection and equipment package adjustment for a production line are disclosed. An example system includes a data collector communicatively coupled to a plurality of input channels connected to data collection points operatively coupled to at least one piece of equipment of an equipment package of the production environment and a data acquisition circuit structured to interpret a plurality of detection values from the plurality of input channels. A data analysis circuit utilizes an expert system diagnostic tool to identify an off-nominal process state in response to the plurality of detection values and a response circuit adjusts an equipment package parameter in response to the off-nominal process state.

Abstract: In the disclosure, a failure of a device performing work while moving is more reliably detected while the data amount of failure diagnosis data is reduced. The disclosure includes a frequency analyzing part which performs a frequency analysis on acquired data from an acceleration sensor; a maximum frequency detecting part which detects a maximum frequency from a result of the frequency analysis; and a failure diagnosis data generating part which sets a frequency twice or more of the maximum frequency as a sampling frequency, samples the acquired data from the acceleration sensor, and generates the failure diagnosis data.

Abstract: A system includes a reception interface that receives sensor data of an artificial lift system disposed at least in part in a well; an analysis engine that, based at least in part on a portion of the sensor data, outputs values of state variables of the artificial lift system; and a transmitter interface that transmits information, based at least in part on a portion of the values of state variables, to a surface controller operatively coupled to the artificial lift system.

Abstract: A communication adapter of a gas turbine engine of an aircraft includes a communication interface configured to wirelessly communicate with an offboard system and to communicate with an engine control of the gas turbine engine. The communication adapter also includes a memory system and processing circuitry configured to check for a change of an identifier associated with the engine control, check for a loss of a plurality of remote dynamic data recording parameters from the engine control, and pass a request to update the remote dynamic data recording parameters from the offboard system through the communication adapter to the engine control based on detecting the change of the identifier. The processing circuitry is further configured to reload an existing configuration of the remote dynamic data recording parameters at the engine control based on determining that the loss of the remote dynamic data recording parameters has occurred.

Abstract: A damage probability calculation device which calculates a damage probability in an evaluation target region of a gas turbine computes strength distributions including a mean, a standard deviation and a certainty factor of the strength of a material used for the evaluation target region with respect to stresses on the basis of strength test data of the material. In addition, the damage probability calculation device computes stress distributions including the mean, the standard deviation and the certainty factor of stresses input to the evaluation target region on the basis of operation data of the gas turbine acquired through a sensor. Further, the damage probability calculation device computes damage probability distributions indicating distributions of damage probabilities of the evaluation target region on the basis of the strength distributions and the stress distributions.

Abstract: 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.

Abstract: The system generally includes a crosspoint switch in the local data collection system having multiple inputs and multiple outputs including a first input connected to the first sensor and a second input connected to the second sensor. The multiple outputs include a first output and a second output configured to be switchable between a condition in which the first output is configured to switch between delivery of the first sensor signal and the second sensor signal and a condition in which there is simultaneous delivery of the first sensor signal from the first output and the second sensor signal from the second output. Each of multiple inputs is configured to be individually assigned to any of the multiple outputs. Unassigned outputs are configured to be switched off producing a high-impedance state. The local data collection system includes multiple multiplexing units and multiple data acquisition units receiving multiple data streams from multiple machines in the industrial environment.