Abstract: First and second signals respectively associated with first and second motors are obtained. First and second motor wear metric that respectively represent an amount of wear associated with the first and second motors are determined based at least in part on the first and second signals, respectively. It is determined whether at least one of the first or second motor wear metrics exceeds a failure threshold. The VTOL vehicle is automatically prevented from performing a vertical takeoff attempt if least one of the first or second motor wear metrics exceeds the failure threshold. The first and second rotors are respectively positioned at first and second angles relative to a horizontal plane, at least during a hovering mode of the VTOL vehicle. The first and second angles are different angles. The first and second motors are respectively associated with the first and second rotors.

Abstract: An injection molding machine management system includes an injection molding machine, a take-out robot, an inspection device, a memory, and a processor. The processor is configured to receive physical information of the injection molding machine and a mold, and an inspection result of a molded product. The received physical information includes an identification information of the mold and the injection molding machine, a shot number of injection molding with respect to the mold, an injection filling time with respect to the mold, an injection pressure, a mold clamping force, and a set temperature of each part of the injection molding machine. The received physical information and the inspection result are displayed on a display. Necessity of maintenance is notified to an operator based on a predetermined maintenance period of time, the received physical information, and/or the inspection result.

Abstract: A computer-implemented method for determining automatically a machine safety and/or a product quality of a flexible cyber-physical production system with a configuration adaptable during a production process including production steps executed by machines forming equipment of a physical factory of the cyber-physical production system to produce a product according to a product recipe, wherein the machine safety and/or product quality are calculated during runtime of the flexible cyber-physical production system by processing a meta-model of the flexible cyber-physical production system stored in a computer readable storage medium, is provided.

Abstract: A sensor unit includes an orientation sensor, an electronic processor coupled to the orientation sensor, and memory coupled to the electronic processor and storing support structure configuration data and instructions. The instructions, when executed by the electronic processor, cause the sensor unit to monitor a position of a conductor support structure associated with the sensor unit based on data from the orientation sensor and generate an alert message responsive to determining that the position violates a position threshold. The position threshold is generated based on the support structure configuration data.

Abstract: A method for controlling an ESP-lifted well in an optimal fashion using the ESP speed and choke opening as actuators subject to operational constraints.

Abstract: Disclosed is a process stop loss reduction system, in which in case that pressure in a trapping apparatus and pressure in a process chamber are increased because of space clogging or the like caused by reaction by-products while the trapping apparatus for trapping of a reaction by-product contained in exhaust gas discharged from the process chamber operates over a long period of time during a semiconductor process, only the trapping apparatus, in which an exhaust gas supply flow path is blocked, may be quickly replaced while inert gas, instead of the exhaust gas, is received in an idle state and continuously supplied to the vacuum pump through a bypass pipe without stopping an operation of (shutting down) a semiconductor manufacturing process chamber facility, and then the trapping apparatus may be supplied with the exhaust gas again as the flow path is changed.

Abstract: Systems and methods for scheduling maintenance of equipment include collecting pre-emptive maintenance data associated with a pre-emptive maintenance task associated with a component of equipment, collecting preventive maintenance data associated with a scheduled preventive maintenance task associated with the component or another component, applying a model to predict a failure time value associated with a future failure of the component, analyzing the data and the time value to determine an optimal time to perform a maintenance event, and using that optimal time to schedule the next maintenance event. Determining the optimal time includes minimizing a total cost of the maintenance.

Abstract: A remote sensor including a first wireless interface for sending out data. The remote sensor has a second wireless interface arranged separate from the first wireless interface. The second wireless interface is configured for the wireless transmission of information between the remote sensor and an external device. The invention also relates to a method for communication between a remote sensor and an external device. The method involves creating a communication link between a wireless interface of the remote sensor and a wireless interface of the external device, as well as transmitting information between the remote sensor and the external device by the established communication link. This allows for simple configuration or maintenance of the remote sensor by the external device according to the exchanged information.

Abstract: An abnormality diagnosis device diagnoses an abnormality of a plurality of speed reducers included in a robot in accordance with disturbance torque regarding a state of the respective speed reducers acquired from a sensor installed in the robot, and outputs a result of the diagnosis to a display unit, the abnormality diagnosis device including a maintenance history DB configured to store maintenance data on maintenance made for the respective speed reducers, and a control unit configured to detect an abnormality in the respective speed reducers in accordance with the disturbance torque. The control unit, when detecting an abnormality in one speed reducer in accordance with the disturbance torque, predicts an abnormality in another speed reducer caused in association with the abnormality in the one speed reducer in accordance with the maintenance data, and outputs information on the predicted abnormality to the display unit.

Abstract: Provided is an automatic analyzer in which user work is in conjunction with apparatus driving and operation of a user even in complicated maintenance work is simplified. The automatic analyzer includes a measurement device 2 and a control device 3. The control device controls the measurement device. The control device includes an input unit 32 that receives a start instruction of maintenance work by a user, a control unit 31 that controls an apparatus to perform a predetermined first processing in accordance with input, a driving unit that performs driving in accordance with processing of the control unit, a display unit 33 that displays a second processing to be performed by the user in conjunction with the first processing after the first processing is terminated by the driving unit. The control device sequentially guides maintenance work of the user by performing the first processing or the second processing after the displayed second processing is executed by the user.

Abstract: A method for monitoring machine operation for various machine speed and loads includes measuring vibration information at a sensor associated with a machine and an associated machine speed. The machine is a rotating machine. The method includes performing an operational frequency analysis of the vibration information and comparing results from the operational frequency analysis with a vibration signature for the machine. The vibration signature is for a machine speed that matches the machine speed of the measured vibration information. The vibration signature is one of several vibration signatures for the machine where each is for a different machine speed. The method includes identifying a potential failure mode based on a frequency range where the frequency analysis of the measured vibration information exceeds, by a threshold amount, the vibration signature of the plurality of vibration signatures that matches the machine speed, and transmitting an alert comprising the identified potential failure mode.

Abstract: The present invention provides a method for integrated online monitoring and a system for integrated online monitoring from a remote location for a nuclear power plant. The method includes a first step of collecting machine monitoring data of a plurality of units in the nuclear power plant selectively from the local data acquisition device via the monitoring data relay device, and a second step of collecting machine diagnostic data of a plurality of units in the nuclear power plant selectively from the local data acquisition device via the diagnostic data relay device.

Abstract: A monitoring method for an electrical energy transfer device which has a first phase conductor and a second phase conductor, includes the following steps: a temperature of the first phase conductor is compared with the temperature of the second phase conductor and a signaling is performed if there is a deviation between the temperatures. The electrical energy transfer device is, for this purpose, equipped at the first phase conductor with a first temperature sensor and at the second phase conductor with a second temperature sensor.

Abstract: The embodiments of the present disclosure provide method and Internet of Things (IoT) systems for predicting maintenance materials of a smart gas pipeline network. The method may be implemented based on a smart gas safety management platform of an Internet of Things (IoT) system for predicting maintenance materials of a smart gas pipeline network. The method may comprise: obtaining a pipeline network feature of a gas pipeline network; predicting fault probabilities of one or more point positions of the gas pipeline network based on the pipeline network feature, the fault probabilities including probabilities of one or more preset fault types of faults occurring at the point positions; and determining demand for the maintenance materials based on the fault probabilities of the one or more point positions.

Abstract: Provided is a maintenance operation assistance system comprising: a failure knowledge database wherein failure knowledge data is recorded; a failure knowledge coupling unit for reconstructing partial failure knowledge data into failure knowledge data; and an inspection procedure generation unit for presenting an inspection procedure using the reconstructed failure knowledge data. The failure knowledge coupling unit evaluates and adjusts the relatedness of nodes among different instances of partial failure knowledge data, and connects the different instances of partial failure knowledge data. On the basis of the reconstructed failure knowledge data, the inspection procedure generation unit sets priorities for when presenting the inspection procedure, and presents the inspection procedure to a diagnostic interface unit in accordance with the priorities.

Abstract: An apparatus for assisting maintenance work includes circuitry configured to perform learning based on a data set in association with a replaced or repaired part, or a new part after replacement indicated by work content information, and the learning includes processing an input of the data set or a portion of the data set, in accordance with model parameters of a machine learning model; determining work content information applied to the input; and updating the model parameters of the machine learning model based on the determined work content information.

Abstract: A system for failure detection tools is disclosed. The system may include at least one user device, an application server, and a failure detection system, each of which may be in communication with one or more of the others via at least one network. The failure detection system may receive first data from a data source, process the first data to generate second data, apply a statistical modeling algorithm to make a prediction relating to the first data or the second data, and communicate data relating to the prediction and/or a trend related to the first data or the second data to the user device for displaying at least a portion of the data relating to the prediction and/or the trend on a display of the user device.

Abstract: A signal associated with a motor is obtained where the motor is included in a aircraft that has flight capabilities. A motor wear metric that represents an amount of wear experienced by the motor is determined based at least in part on the signal. It is determined, at a flight computer that is included in the aircraft, whether to restrict the flight capabilities of the aircraft based at least in part on the motor wear metric. The flight capabilities of the aircraft are restricted in the event it is so determined.

Abstract: An information processing system, an information processing apparatus, and a display method. The information processing system stores in one or more memories, error information acquired from the device and a solution method of an error input to the device or the information processing apparatus in association with time information and displays on a display, presence of the error information and presence of the solution method in association with time axis based on the time information.

Abstract: Described herein are methods and systems for generating and applying vehicle maintenance models to vehicle telematics data. A vehicle telematics analytics (VTA) computing device is configured to receive vehicle telematics data associated with operation of a subject vehicle, and apply the received vehicle telematics data to a vehicle maintenance model to determine whether the operation of the subject vehicle is better or worse than standard operation of like vehicles. The VTA computing device may adjust a maintenance cost and/or determine if a user of the vehicle is eligible for a reward based upon this determination. The VTA computing device is configured to transmit an itemized report to the user including the adjusted maintenance cost and/or the reward as well as one or more other vehicle costs.

Abstract: A system includes sensors for monitoring signals, and a processing system executes one or more methods for identification of system events, from the signals, corresponding to state changes and performance of the system and/or its subcomponents. Event identification is performed with classification and/or other machine learning algorithms, with generation of novel training data sets. The sensor(s) can also be used to determine power consumption information about the system and/or its subcomponents. The system processes event-associated outputs for execution of actions for improving system performance, along with other downstream applications.

Abstract: A cloud computing system receives data associated with a component of an industrial automation system, wherein the data identifies a supplier of the component, and a location of the component within the industrial automation system, updates a registry for the industrial automation system based on the received data, generates a mapping between the industrial automation system and the component of the industrial automation system, wherein the mapping is indicative of the supplier, the location, or both, models the component performing one or more operations in the industrial automation system based on the received data, the registry, and the mapping, determines a recommended action for the industrial automation system based on the model, the received data, the registry, and the mapping, and transmits the recommended action to a computing device.

Abstract: A method for determining a status of one of multiple machine components of a machine on the basis of a digital machine model, wherein the digital machine model describes the multiple machine components, includes the steps of: determining component manufacturer data of the multiple machine components; determining machine manufacturer data of the multiple machine components; determining machine operator data of the multiple machine components; and determining the status of the one of the multiple machine components by linking the determined component manufacturer data, the determined machine manufacturer data and the determined machine operator data.

Abstract: A computer system for automatically allocating periodic maintenance contributions to a maintenance savings account based upon vehicle telematics data includes a processor and a computer-readable storage medium having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations including: (i) receiving, from a vehicle, telematics data associated with a vehicle component; (ii) determining a replacement cycle associated with the vehicle component; (iii) determining a replacement cost of the vehicle component; (iv) calculating a plurality of periodic maintenance contributions to a maintenance savings account, the maintenance savings account associated with the vehicle owner and designated to receive the plurality of periodic maintenance contributions; and (v) automatically transferring the plurality of periodic maintenance contributions from a primary account associated with the user to the maintenance savings account.

Abstract: Provided is a method, device, and computer-readable medium for controlling a robot graphic user interface (“RGUI”) on a mobile device. The method can include determining a distance, a position, or both of the mobile device with respect to a first robot; and causing, by a processor, a first RGUI to be displayed on a display of the mobile device based on the determining.

Abstract: According to one embodiment, a device management apparatus includes processing circuitry. The processing circuitry acquires information indicating occurrence of a first failure prediction of a first device. The processing circuitry adjusts detection sensitivity of a second failure prediction of a second device relating to the information based on relevance between the first device and the second device. The second device is different from the first device.

Abstract: Sensor combinations that are effective for failure sign diagnosis are automatically generated in consideration of hidden relationships between sensor data. The present invention includes: a time shift data generation unit 106 that processes sensor data acquired from an instrument and generates the processed sensor data; and a sensor combinations/pre-processing condition generation unit 112 that generates sensor combinations on the basis of correlation coefficients between the sensor data and the processed sensor data, and generates, as a preprocessing condition, a processing condition that increases a correlation coefficient between sensors for each sensor combination, in which the failure sign diagnosis of the instrument is performed on the basis of a change in the relationship between the sensor data included in the sensor combination and the processed sensor data.

Abstract: A computer management apparatus including a plurality of nodes, each including a processor and a storage device, and stores a countermeasure result table including a plurality of combinations of an anomaly detection rule, a countermeasure rule which is a countermeasure against an anomaly, and an effect indicating effectiveness of these rules, and the management apparatus includes: an anomaly detection unit that detects an anomaly of the computer system based on information acquired from the computer system and the anomaly detection rule; an execution unit that decides a countermeasure, at which the anomaly has been detected by the anomaly detection unit, on the basis of the detected anomaly, the countermeasure rule, and the effect indicating the effectiveness, and executes the decided countermeasure; and a countermeasure result information setting unit that evaluates a result of the countermeasure and records the result in the effect indicating the effectiveness in the countermeasure result table.

Abstract: Systems, methods, and non-transitory computer-readable media can be configured to perform receiving a notification of a maintenance event associated with a resource. The method includes retrieving historic maintenance data in relation to the resource with which the fault is associated, the maintenance information originating from a time period preceding the time of the maintenance event. The method includes identifying at least a portion of the retrieved historic maintenance data as being indicative of the maintenance event. The method also includes causing the portion of the retrieved historic maintenance data identified as being indicative of the maintenance event to be stored as a precursor signal of the maintenance event. The method also includes causing future maintenance data received from a plurality of resources related to the resource with which the maintenance event is associated to be monitored to predict a future occurrence of the maintenance event in the plurality of resources.

Abstract: An automatic work order generation system for model predictive maintenance (MPM) of building equipment including an MPM system including an equipment controller to operate the building equipment to affect an environmental condition of a building. The MPM system can perform a predictive optimization to determine a service time at which to service the building equipment. The automatic work order generation system includes an equipment service scheduler that can determine whether any service providers are available to perform equipment service within a predetermined time range of the service time. In response to determining that service providers are available to perform the equipment service, the equipment service scheduler can select a service provider and an appointment time based on one or more service provider attributes. The equipment service scheduler can generate a service work order and transmit the service work order to the service provider to schedule a service appointment.

Abstract: Provided are a method, apparatus and system for storing fault data, an embodiment of the fault data storage method including: acquiring fault data of a target electrical device; sending a consensus request for the fault data, usable to request that consensus personnel who use the consensus client reach a consensus for the reason why the target electrical device is faulty, to at least one consensus client; respectively receiving a consensus result from each consensus client, the consensus result being formed by the consensus client according to the triggering of the consensus personnel; determining, according to each received consensus result, whether the reason for why the target electrical device is faulty is due to device quality; generating, upon the reason for why the target electrical device is faulty being due to device quality, a first data block which contains the fault data; and storing the first data block into a blockchain.

Abstract: This disclosure includes techniques for analyzing patient data. In one example, a method includes accessing, by a computer system, one or more databases comprising health information, with protected health information, for a plurality of patients, accessing, by the computer system, an analytical model, and receiving, by the computer system via a user interface, instructions to apply the analytical model to health information for each of the plurality of patients. The protected health information is isolated from the user interface to restrict access to the protected health information. The method further includes applying, by the computer system, the analytical model to health information for each of the plurality of patients, and storing a result of the analytical model to the one or more databases.

Abstract: Systems, methods, and other embodiments associated with long-term predictions for specific maintenance within a planned maintenance schedule. In one embodiment, a method includes updating a failure probability curve for a component part of a device based at least in part on data obtained from a sensor associated with the component part; determining based at least in part on the updated failure probability curve that a likelihood of failure for the component part following a first upcoming planned maintenance and before a second upcoming planned maintenance exceeds a threshold; and transmitting a work order for specific maintenance to reduce the likelihood of failure of the component part to be performed during the first upcoming planned maintenance.

Abstract: A device for a secure data connection of at least one manufacturing machine (104) has an information-processing system (114), which is subdivided into individual zones (108, 110, 112) interconnected by data diodes (120) such that data originating from the machine control (118) of the manufacturing machine (104) in a data flow can be transferred to other zones (108, 110, 112) without the possibility of a data return flow. The individual zones (110, 112) are ordered hierarchically. Each individual zone has a lower level of data security than the upstream individual zone (108, 110) in relation to the data flow. Every individual zone (108, 110, 112) is formed as an independent computer in the manner of an isolated application. In addition, a manufacturing machine and a production plant includes the device for secure data connection.

Abstract: A method for generating a report regarding prioritizations of industrial automation devices in an industrial system may include determining a first score for each of the industrial automation devices. The first score represents a relative importance of each of the industrial automation devices. The method may also include determining a second score for each of one or more parts of each of the industrial automation devices. The second score represents a relative importance of each of the parts with respect to each other. The method may also include generating the report comprising the parts, the industrial automation devices, the first score for each of the industrial automation devices, the second score for each of the parts, or any combination thereof, wherein the report is organized according to the first score, the second score, or based on a combination of the first score and the second score.

Abstract: An example method comprises receiving first historical data of a first time period and failure data, identifying at least some sensor data that was or potentially was generated during a first failure, removing the at least some sensor data to create filtered historical data, training a classification model using the filtered historical data, the classification model indicating at least one first classified state at a second period of time prior to the first failure indicated by the failure data, applying the classification model to second sensor data to identify a first potential failure state based on the at least one first classified state, the second sensor data being from a subsequent time period, generating an alert if the first potential failure state is identified based on at least a first subset of sensor signals generated during the subsequent time period, and providing the alert.

Abstract: An injection system, including an injector having a dispensing mechanism configured to dispense a medicament, and a ready-to-use indicator. The ready-to-use indicator includes a controller configured to interact with the ready-to-use indicator and an audio and/or visual indicator, a temperature sensor, and a temperature analog having similar thermodynamic properties of the medicament. The temperature sensor is configured to detect a temperature of the temperature analog which represents the dynamic temperature of medicament as the medicament is heated or cooled. The temperature sensor is configured to communicate the detected temperature to the controller and to alert the controller when a preset temperature is reached. The ready-to-use indicator is configured to alert a user when the preset temperature is reached, signifying the medicament is thermally ready to be delivered by the dispensing mechanism. The audio and/or visual indicator is configured to display indicate one or more notifications to the user.

Abstract: Methods and systems for data collection in an environment including pumps and fans are disclosed. A monitoring system may include a data collector communicatively coupled to a plurality of input channels, wherein the input channels are communicatively coupled to sensors measuring operational parameters of a pump or fan. A data storage may store one or more frequencies related to an operation of the pump or fan, and a data acquisition circuit may interpret a plurality of detection values from the collected data. A frequency evaluation circuit may detect a signal on one of the input channels at a frequency higher than the one or more frequencies at which the pump or fan operates.

Abstract: A facility readiness inspection system and method are disclosed. Embodiments comprise an asset database comprising inspection task definition for assets. An inspection coordination application program interface (API) can create at least one periodic inspection task list. Each periodic inspection task list can include a number of tasks and assets, chosen based on the total time allotted for completion of the periodic inspection task list and the complexity of the inspection task definitions of each physical asset. Mobile electronic device can be configured to present the periodic inspection task list as a series of discrete tasks and to receive task list response data in response to each discrete task. Response data can be compared to benchmarks and standards, and issues can be escalated to external systems. An analytics engine can automatically produce inspection compliance documentation for each of the physical assets related to the periodic inspection task list.

Abstract: An apparatus for detecting a fault state of an aircraft is provided. The apparatus accesses a training set of flight data for the aircraft. The training set includes observations of the flight data, each observation of the flight data includes measurements of properties selected and transformed into a set of features. The apparatus builds a generative adversarial network including a generative model and a discriminative model using the training set and the set of features, and builds an anomaly detection model to predict the fault state of the aircraft. The anomaly detection model is trained using the training set of flight data, simulated flight data generated by the generative model, and a subset of features from the set of features. The apparatus deploys the anomaly detection model to predict the fault state of the aircraft using additional observations of the flight data.

Abstract: A power device includes one or more electrical components, the electrical components including one or more physical attribute. The power device includes one or more sensors configured to monitor the attribute(s). The power device includes a non-transitory computer-readable storage medium including one or more alerting rule. The power device includes one or more processors configured for retrieving the one or more alerting rule from the storage medium. The processors are configured for monitoring one or more sensor value from the sensor(s), wherein the sensor values are associated with the attribute(s). The processors are configured for evaluating the at least one alerting rule during the monitoring, and when the one or more alerting rule results in a pending failure condition, sending a notification to a user.

Abstract: The present disclosure relates to diagnosing a fault in an electric drive of a process plant. The fault diagnosis method includes receiving fault data from an electric drive upon occurrence of the fault. The method further includes obtaining a fault code and a drive type associated with the electric drive from the fault data. In addition, the method comprises determining one or more drive parts to replace by comparing the fault code and the drive type with a mapped data for a plurality of drive types. The mapped data for each drive type includes a relation between a plurality of fault codes and a plurality of drive parts. The method further includes initiating a maintenance operation involving replacement of the one or more drive parts to address the fault.

Abstract: A sensor unit includes an orientation sensor, an electronic processor coupled to the orientation sensor, and memory coupled to the electronic processor and storing support structure configuration data and instructions. The instructions, when executed by the electronic processor, cause the sensor unit to monitor a position of a conductor support structure associated with the sensor unit based on data from the orientation sensor and generate an alert message responsive to determining that the position violates a position threshold. The position threshold is generated based on the support structure configuration data.

Abstract: Systems and methods are described herein for generating potential feature combinations for a new item. A neural network may be utilized to identify positive and/or negative sentiment phrases from textual data. Each sentiment phrase may correspond to particular features of existing items. A machine-learning model may utilize the sentiment phrases and their corresponding features to generate a set of potential feature combinations for a new item. The potential feature combinations may be scored, for example, based on an amount by which a potential feature combination differs from known feature combinations of existing items. One or more potential feature combinations may be provided in a feature recommendation. Feedback (e.g., human feedback, sales data, page views for similar items, and the like) may be obtained and utilized to retrain the machine-learning model to better identify subsequent feature combinations that may be desirable and/or practical to manufacture.

Abstract: An equipment inspection system receives data captured by a sensor of an autonomous vehicle (AV). The captured data describes a current state of equipment for servicing the AV. The equipment inspection system compares the captured data to a model describing an expected state of the equipment. The equipment inspection system determines, based on the comparison, that the equipment differs from the expected state. The equipment inspection system may transmit data describing the current state of the equipment to an equipment manager. The equipment manager may schedule maintenance for the equipment based on the current state of the equipment.

Abstract: Disclosed is a vacuum valve having a valve closure and having a drive unit which is coupled to the valve closure and which has at least one adjustment element. The vacuum valve furthermore has a position sensor, in particular a travel or distance sensor, such that a position of the valve closure and/or of the at least one adjustment element relative to a zero position, in particular an open position or closed position of the vacuum valve, can be measured.

Abstract: Provided is an abnormality diagnosis device including: a physical quantity measurement processor configured to acquire, as time-series data, a physical quantity of an electric motor or a load; a feature parameter calculation processor configured to calculate feature parameters; a correlation function creation processor configured to create a correlation function for two or more feature parameters, and calculate a correlation coefficient corresponding to a measurement result of the physical quantity that changes depending on an abnormality occurrence state; a database configured to store in advance reference data in which a remaining time until a failure is caused and the correlation coefficient are associated with each other; and a diagnosis processor configured to extract from the reference data the remaining time corresponding to the correlation coefficient, and identify the remaining time until the electric motor or the load causes a failure or a part that has caused a failure.

Abstract: An apparatus, method, and non-transitory machine-readable medium provide for 360° assistance for a QCS scanner with mixed reality (MR) and machine learning technology. The apparatus includes an optical sensor, a display, a Chatbot, cloud service, and a processor operably connected to the optical sensor and the display. The processor receives diagnostic information from a server related to a field device in an industrial process control and automation system; identifies an issue of the field device based on the diagnostic information; detects, using the optical sensor, the field device corresponding to the identified issue; guides, using the display, a user to a location and a scanner part of the field device that is related to the issue; provides, using the display, necessary steps or actions to resolve the issue; and connects, using a cloud server, a user to get modules of installation, commissioning, annual maintenance (AMC) and training for a quality control system (QCS) as per the selected persona.

Abstract: A method includes monitoring unstructured data related to a configuration item in a relevant source, analyzing the data using a natural language processing system, and determining that the configuration item has an event wherein the configuration item is to be maintained in response to the analysis of the data. The method also includes designating that the configuration item is in a maintenance mode and suppressing alerts related to the configuration item while the configuration item is in the maintenance mode.

Abstract: A system and method arranged to predict a match state event by a machine learning platform. The system and method including monitoring, by the machine learning platform, multimedia content on a live data feed, receiving, by the machine learning platform, current match state data corresponding to the multimedia content, and predicting, by the machine learning platform, an anomaly in the multimedia content based on an analysis of received multimedia content and current match state data. The system and method can include generating, by the machine learning platform, a confidence score regarding a likelihood of the anomaly in the multimedia content, and resolving, by the machine learning platform, the anomaly based on the confidence score. Resolving the anomaly includes extracting a portion of the multimedia content containing the anomaly, ignoring the anomaly, or correcting the anomaly.