| Sonstiges: |
- Nachgewiesen in: USPTO Patent Applications
- Sprachen: English
- Document Number: 20240185257
- Publication Date: June 6, 2024
- Appl. No: 17/971342
- Application Filed: October 21, 2022
- Claim: 1. A method for generating a reliability model for building devices or building device components, the method comprising: receiving, by a processing circuit, warranty claim data associated with the building devices or the building device components; processing, by the processing circuit, the warranty claim data using natural language processing to generate a training data set comprising one or more causes and solutions associated with failure of the one or more building devices or the building device components; and training, by the processing circuit, a component reliability model using the training data set to produce a trained model.
- Claim: 2. The method of claim 1, wherein the warranty claim data includes a warranty claim comment, wherein the processing the warranty claim data comprises at least one of identifying key words in the warranty claim comment, removing a stop word in the warranty claim comment, lemmatizing words in the warranty claim comment, and removing unnecessary words from the warranty claim comment.
- Claim: 3. The method of claim 1, wherein evaluating the processed warranty claim data using natural language processing comprises: identifying, by the processing circuit, a plurality of words which occur in the warranty claim data over a predetermined amount of time; determining, by the processing circuit, that the plurality of words are independent from each other; creating, by the processing circuit, a plurality of word clusters associated with each of the plurality of words that are independent from each other; and generating, by the processing circuit, a plurality of n-grams for the plurality of word clusters to determine the one or more causes and solutions associated with the failure of the one or more building devices or the building device components.
- Claim: 4. The method of claim 3, wherein generating the training data set based on the one or more causes and solutions further comprises combining, by the processing circuit, the plurality of n-grams to form the training data set which describes a predetermined number of building component failure causes and solutions.
- Claim: 5. The method of claim 1, further comprising: generating, by the processing circuit, a reliability metric describing a predicted failure time associated with the one or more building devices or the building device components based on the trained model; and updating, by the processing circuit, the building device components based on the reliability metric.
- Claim: 6. The method of claim 5, wherein updating the building device components comprises automatically updating software for the building device components.
- Claim: 7. The method of claim 1, wherein training the component reliability model to produce the trained model includes determining a shape parameter and a scale parameter of a Weibull model.
- Claim: 8. The method of claim 1, wherein processing the warranty claim data includes filtering out unnecessary information and identifying key words.
- Claim: 9. One or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to: receive warranty claim data associated with one or more building devices or building device components; process the warranty claim data using natural language processing to generate a training data set comprising one or more causes and solutions associated with failure of the one or more building devices or the building device components; and train a component reliability model using the training data set to produce a trained model.
- Claim: 10. The one or more non-transitory computer-readable storage media of claim 9, wherein the warranty claim data includes a warranty claim comment.
- Claim: 11. The one or more non-transitory computer-readable storage media of claim 10, wherein the processing the warranty claim data comprises at least one of identifying key words in the warranty claim comment, removing a stop word in the warranty claim comment, lemmatizing words in the warranty claim comment, and removing unnecessary words from the warranty claim comment.
- Claim: 12. The one or more non-transitory computer-readable storage media of claim 9, wherein evaluating the processed warranty claim data using the natural language processing comprises: identifying a plurality of words which occur in the warranty claim data over a predetermined amount of time; determining that the plurality of words are independent from each other; creating a plurality of word clusters associated with each of the plurality of words that are independent from each other; and generating a plurality of n-grams for the plurality of word clusters to determine the one or more causes and solutions associated with the failure of the one or more building devices or the building device components.
- Claim: 13. The one or more non-transitory computer-readable storage media of claim 12, wherein generating the training data set based on the one or more causes and solutions further comprises combining the plurality of n-grams to form the training data set which describes a predetermined number of building component failure causes and solutions.
- Claim: 14. The one or more non-transitory computer-readable storage media of claim 9, wherein the instructions further cause the one or more processors to: generate a reliability metric describing a predicted failure time associated with the one or more building devices or the building device components based on the trained model; and update the building device components based on the reliability metric.
- Claim: 15. The one or more non-transitory computer-readable storage media of claim 14, wherein updating the building device components comprises automatically updating a software for the building device components.
- Claim: 16. The one or more non-transitory computer-readable storage media of claim 14, wherein training the component reliability model to produce the trained model includes determining a shape parameter and a scale parameter of a Weibull model.
- Claim: 17. A predictive maintenance system, comprising: a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the processor to: receive warranty claim data associated with one or more building devices or building device components; process the warranty claim data using natural language processing to generate a training data set comprising one or more causes and solutions associated with failure of the one or more building devices or the building device components; and train a component reliability model using the training data set to produce a trained model.
- Claim: 18. The predictive maintenance system of claim 17, wherein the warranty claim data includes a warranty claim comment.
- Claim: 19. The predictive maintenance system of claim 18, wherein the processing the warranty claim data comprises at least one of identifying key words in the warranty claim comment, removing a stop word in the warranty claim comment, lemmatizing words in the warranty claim comment, and removing unnecessary words from the warranty claim comment.
- Claim: 20. The predictive maintenance system of claim 17, wherein the instructions further cause the processor to: generate a reliability metric describing a predicted failure time associated with the one or more building devices or the building device components based on the trained model; and update the building device components based on the reliability metric.
- Current International Class: 06; 06
|
