Abstract: Various embodiments described herein relate to an anomaly detection framework adaptable to different asset types. In this regard, a data stream associated with a first asset is received. The data stream is then processed to generate output data by encoding the data stream based on historical data associated with the first asset, the historical data comprising clustered data representative of fault states and one or more non-fault states. Furthermore, in accordance with a determination that the generated output data is indicative of a potential fault of the first asset, fault data indicative of the potential fault is generated and caused to be transmitted to an administrative device for display.

Abstract: Methods, apparatuses, and systems for predicting radio altimeter failures are provided. An example method may include determining a first plurality of altitude values associated with a first radio altimeter, determining a second plurality of altitude values associated with a second radio altimeter, calculating a first level feature based at least in part on the first plurality of altitude values and the second plurality of altitude values, and determining a radio altimeter failure indicator based at least in part on the first level feature.

Abstract: Systems and methods of providing usage-based maintenance services for a plurality of vehicles arranged in a fleet includes receiving usage data. A usage parameter distribution is generated, and a fleet usage model is generated according to the distribution. The fleet usage model expresses a score as a function of the usage parameter. Also, a score distribution is generated, and a reward model is generated according to the score distribution. The reward model expresses a maintenance reward as a function of the score. Additionally, the score for one of the vehicles is determined using the fleet usage model, and the maintenance reward is determined for the vehicle using the reward model.

Abstract: Methods, apparatuses, and systems for predicting radio altimeter failures are provided. An example method may include determining a first plurality of altitude values associated with a first radio altimeter, determining a second plurality of altitude values associated with a second radio altimeter, calculating a first level feature based at least in part on the first plurality of altitude values and the second plurality of altitude values, and determining a radio altimeter failure indicator based at least in part on the first level feature.

Abstract: Methods, apparatuses, and systems for predicting radio altimeter failures are provided. An example method may include determining a first plurality of altitude values associated with a first radio altimeter, determining a second plurality of altitude values associated with a second radio altimeter, calculating a first level feature based at least in part on the first plurality of altitude values and the second plurality of altitude values, and determining a radio altimeter failure indicator based at least in part on the first level feature.

Abstract: Various embodiments described herein relate to an anomaly detection framework adaptable to different asset types. In this regard, a data stream associated with a first asset is received. The data stream is then processed to generate output data by encoding the data stream based on historical data associated with the first asset, the historical data comprising clustered data representative of fault states and one or more non-fault states. Furthermore, in accordance with a determination that the generated output data is indicative of a potential fault of the first asset, fault data indicative of the potential fault is generated and caused to be transmitted to an administrative device for display.

Abstract: Various embodiments described herein relate to providing optimization related to enterprise performance management. In this regard, a request to obtain one or more insights with respect to a formatted version of disparate data associated with one or more data sources is received. The request includes an insight descriptor that describes a goal for the one or more insights. In response to the request, aspects of the formatted version of the disparate data is associated to provide the one or more insights. The associated aspects are determined by the goal and relationships between the aspects of the formatted version of the disparate data. Furthermore, one or more actions are performed based on the one or more insights.

Abstract: Systems and methods of providing usage-based maintenance services for a plurality of vehicles arranged in a fleet includes receiving usage data. A usage parameter distribution is generated, and a fleet usage model is generated according to the distribution. The fleet usage model expresses a score as a function of the usage parameter. Also, a score distribution is generated, and a reward model is generated according to the score distribution. The reward model expresses a maintenance reward as a function of the score. Additionally, the score for one of the vehicles is determined using the fleet usage model, and the maintenance reward is determined for the vehicle using the reward model.

Abstract: Systems and methods of providing usage-based maintenance services for a plurality of vehicles arranged in a fleet includes receiving usage data. A usage parameter distribution is generated, and a fleet usage model is generated according to the distribution. The fleet usage model expresses a score as a function of the usage parameter. Also, a score distribution is generated, and a reward model is generated according to the score distribution. The reward model expresses a maintenance reward as a function of the score. Additionally, the score for one of the vehicles is determined using the fleet usage model, and the maintenance reward is determined for the vehicle using the reward model.

Abstract: Methods, apparatuses, and systems for predicting radio altimeter failures are provided. An example method may include determining a first plurality of altitude values associated with a first radio altimeter, determining a second plurality of altitude values associated with a second radio altimeter, calculating a first level feature based at least in part on the first plurality of altitude values and the second plurality of altitude values, and determining a radio altimeter failure indicator based at least in part on the first level feature.

Abstract: Systems and methods of providing usage-based maintenance services for a plurality of vehicles arranged in a fleet includes receiving usage data. A usage parameter distribution is generated, and a fleet usage model is generated according to the distribution. The fleet usage model expresses a score as a function of the usage parameter. Also, a score distribution is generated, and a reward model is generated according to the score distribution. The reward model expresses a maintenance reward as a function of the score. Additionally, the score for one of the vehicles is determined using the fleet usage model, and the maintenance reward is determined for the vehicle using the reward model.

Abstract: A method includes identifying costs associated with different outcomes of a failure prediction algorithm. The algorithm is configured to predict one or more faults with at least one piece of industrial equipment. The different outcomes include both successful and unsuccessful predictions by the algorithm. The method also includes identifying a threshold value for the algorithm using the costs, where the threshold value is used by the failure prediction algorithm to identify whether maintenance of the at least one piece of industrial equipment is needed. The method further includes providing the threshold value to the algorithm. The threshold value is selected such that a net positive economic benefit is obtained from use of the threshold value with the failure prediction algorithm. In addition, the method can include generating a signal indicating whether maintenance is needed based on a comparison of an indicator value calculated using the algorithm and the threshold value.

Abstract: A method includes identifying costs associated with different outcomes of a failure prediction algorithm. The algorithm is configured to predict one or more faults with at least one piece of industrial equipment. The different outcomes include both successful and unsuccessful predictions by the algorithm. The method also includes identifying a threshold value for the algorithm using the costs, where the threshold value is used by the failure prediction algorithm to identify whether maintenance of the at least one piece of industrial equipment is needed. The method further includes providing the threshold value to the algorithm. The threshold value is selected such that a net positive economic benefit is obtained from use of the threshold value with the failure prediction algorithm. In addition, the method can include generating a signal indicating whether maintenance is needed based on a comparison of an indicator value calculated using the algorithm and the threshold value.