Failure mode analytics

US11567460B2 · kind B2 · utility

Assignee

• SAP SE · DE

Inventors

• Lukas Carullo · Walldorf, DE
• Patrick Brose · San Francisco, US
• Kun Bao · Sunnyvale, US
• Anubhav Bhatia · Sunnyvale, US
• Rashmi Shetty B · San Ramon, US
• Leonard Brzezinski · San Jose, US
• Lauren McMullen · Park Village, US
• Harpreet Singh · Coventry, GB
• Karthik Mohan Mokashi · San Ramon, US
• Simon Lee · San Ramon, US

Key dates

• Filing date: Feb 25, 2019
• Grant date: Jan 31, 2023
• Expiry date: Dec 3, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N20/20
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Provided is a system and method for training and validating models in a machine learning pipeline for failure mode analytics. The machine learning pipeline may include an unsupervised training phase, a validation phase and a supervised training and scoring phase. In one example, the method may include receiving a request to create a machine learning model for failure mode detection associated with an asset, retrieving historical notification data of the asset, generating an unsupervised machine learning model via unsupervised learning on the historical notification data, wherein the unsupervised learning comprises identifying failure topics from text included in the historical notification data and mapping the identified failure topics to a plurality of predefined failure modes for the asset, and storing the generated unsupervised machine learning model via a storage device.