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公开(公告)号：US11010222B2
公开(公告)日：2021-05-18
申请号：US16694673
申请日：2019-11-25
Applicant: SAP SE
Inventor： Rashmi B. Shetty
Abstract: Techniques for predicting failure mode specific reliability characteristics of tangible equipment using parametric probability models are disclosed. In some example embodiments, a computer system receives a model training configuration entered via a user interface, trains a failure curve model for a selected failure mode of a selected equipment model based on the model training configuration at a time indicated by training schedule data, generating, and generates analytical data for the selected failure mode of the selected equipment model using the trained failure curve model. The failure mode corresponds to a specific way in which the equipment model is capable of failing. In some example embodiments, the training of the failure curve model comprises determining a shape parameter and a scale parameter for the failure curve model based on a fitting of failure event data to a continuous probability distribution, and storing the parameters for use in generating the analytical data.
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公开(公告)号：US20210065086A1
公开(公告)日：2021-03-04
申请号：US16707539
申请日：2019-12-09
Applicant: SAP SE
Inventor： Simon Lee , Rashmi B. Shetty , Anubhav Bhatia , Patrick Brose , Martin Weiss , Lukas Carullo , Lauren McMullen , Karthik Mohan Mokashi
Abstract: Techniques for implementing and using failure curve analytics in an equipment maintenance system are disclosed. A method comprises: accessing a failure curve model for an equipment model, the failure curve model being configured to estimate lifetime failure data for the equipment model for different failure modes corresponding to different specific manners in which the equipment model is capable of failing, the lifetime failure data indicating a probability of the equipment model failing in the specific manner of the failure mode; generating first analytical data for a first failure mode of the plurality of failure modes using the failure curve model based on the first failure mode, the first analytical data indicating at least a portion of the lifetime failure data for the equipment model corresponding to the first failure mode; and causing a visualization of the first analytical data to be displayed on a computing device.
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公开(公告)号：US20210064456A1
公开(公告)日：2021-03-04
申请号：US16694673
申请日：2019-11-25
Applicant: SAP SE
Inventor： Rashmi B. Shetty
Abstract: Techniques for predicting failure mode specific reliability characteristics of tangible equipment using parametric probability models are disclosed. In some example embodiments, a computer system receives a model training configuration entered via a user interface, trains a failure curve model for a selected failure mode of a selected equipment model based on the model training configuration at a time indicated by training schedule data, generating, and generates analytical data for the selected failure mode of the selected equipment model using the trained failure curve model. The failure mode corresponds to a specific way in which the equipment model is capable of failing. In some example embodiments, the training of the failure curve model comprises determining a shape parameter and a scale parameter for the failure curve model based on a fitting of failure event data to a continuous probability distribution, and storing the parameters for use in generating the analytical data.
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公开(公告)号：US11573846B2
公开(公告)日：2023-02-07
申请号：US17844405
申请日：2022-06-20
Applicant: SAP SE
Inventor： Rashmi B. Shetty
Abstract: Techniques for predicting failure mode specific reliability characteristics of tangible equipment using parametric probability models are disclosed. In some example embodiments, a computer system receives a model training configuration entered via a user interface, trains a failure curve model for a selected failure mode of a selected equipment model based on the model training configuration at a time indicated by training schedule data, and generates analytical data for the selected failure mode of the selected equipment model using the trained failure curve model. The failure mode corresponds to a specific way in which the equipment model is capable of failing. In some example embodiments, the training of the failure curve model comprises determining a shape parameter and a scale parameter for the failure curve model based on a fitting of failure event data to a continuous probability distribution, and storing the parameters for use in generating the analytical data.
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Patent Agency Ranking
公开(公告)号：US11385950B2
公开(公告)日：2022-07-12
申请号：US17235686
申请日：2021-04-20
Applicant: SAP SE
Inventor： Rashmi B. Shetty
Abstract: Techniques for predicting failure mode specific reliability characteristics of tangible equipment using parametric probability models are disclosed. In some example embodiments, a computer system receives a model training configuration entered via a user interface, trains a failure curve model for a selected failure mode of a selected equipment model based on the model training configuration at a time indicated by training schedule data, generating, and generates analytical data for the selected failure mode of the selected equipment model using the trained failure curve model. The failure mode corresponds to a specific way in which the equipment model is capable of failing. In some example embodiments, the training of the failure curve model comprises determining a shape parameter and a scale parameter for the failure curve model based on a fitting of failure event data to a continuous probability distribution, and storing the parameters for use in generating the analytical data.
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公开(公告)号：US20220391276A1
公开(公告)日：2022-12-08
申请号：US17844405
申请日：2022-06-20
Applicant: SAP SE
Inventor： Rashmi B. Shetty
Abstract: Techniques for predicting failure mode specific reliability characteristics of tangible equipment using parametric probability models are disclosed. In some example embodiments, a computer system receives a model training configuration entered via a user interface, trains a failure curve model for a selected failure mode of a selected equipment model based on the model training configuration at a time indicated by training schedule data, generating, and generates analytical data for the selected failure mode of the selected equipment model using the trained failure curve model. The failure mode corresponds to a specific way in which the equipment model is capable of failing. In some example embodiments, the training of the failure curve model comprises determining a shape parameter and a scale parameter for the failure curve model based on a fitting of failure event data to a continuous probability distribution, and storing the parameters for use in generating the analytical data.
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公开(公告)号：US20210240559A1
公开(公告)日：2021-08-05
申请号：US17235686
申请日：2021-04-20
Applicant: SAP SE
Inventor： Rashmi B. Shetty
Abstract: Techniques for predicting failure mode specific reliability characteristics of tangible equipment using parametric probability models are disclosed. In some example embodiments, a computer system receives a model training configuration entered via a user interface, trains a failure curve model for a selected failure mode of a selected equipment model based on the model training configuration at a time indicated by training schedule data, generating, and generates analytical data for the selected failure mode of the selected equipment model using the trained failure curve model. The failure mode corresponds to a specific way in which the equipment model is capable of failing. In some example embodiments, the training of the failure curve model comprises determining a shape parameter and a scale parameter for the failure curve model based on a fitting of failure event data to a continuous probability distribution, and storing the parameters for use in generating the analytical data.
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公开(公告)号：US11922377B2
公开(公告)日：2024-03-05
申请号：US15927068
申请日：2018-03-20
Applicant: SAP SE
Inventor： Rashmi B. Shetty , Simon Lee
IPC: G06F40/30 , G05B19/418 , G06F18/214 , G06F18/24 , G06F40/20 , G06Q10/20 , G06V30/413
CPC classification number: G06Q10/20 , G05B19/4184 , G06F18/214 , G06F18/24 , G06F40/20 , G06V30/413
Abstract: Some embodiments provide a program that retrieves a set of notifications describing failures that occurred on a set of monitored devices. The program further determines a set of topics based on the set of notifications. The program also determines failure modes associated with the set of topic from a plurality of failure modes defined for the set of monitored devices. The program further determines failure modes associated with the set of notifications based on the set of topics and the failure modes associated with the set of topics. The program also receives a particular notification that includes a particular set of words describing a failure that occurred on a particular monitored device in the set of monitored devices. The program further determines a failure mode associated with the particular notification based on the particular set of words and the determined failure modes associated with the set of notifications.
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公开(公告)号：US20190317480A1
公开(公告)日：2019-10-17
申请号：US15927068
申请日：2018-03-20
Applicant: SAP SE
Inventor： Rashmi B. Shetty , Simon Lee
IPC: G05B19/418 , G06K9/62 , G06F17/27 , G06K9/00
Abstract: Some embodiments provide a program that retrieves a set of notifications describing failures that occurred on a set of monitored devices. The program further determines a set of topics based on the set of notifications. The program also determines failure modes associated with the set of topic from a plurality of failure modes defined for the set of monitored devices. The program further determines failure modes associated with the set of notifications based on the set of topics and the failure modes associated with the set of topics. The program also receives a particular notification that includes a particular set of words describing a failure that occurred on a particular monitored device in the set of monitored devices. The program further determines a failure mode associated with the particular notification based on the particular set of words and the determined failure modes associated with the set of notifications.
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