William R Winn

US Patent:

20210141785, May 13, 2021

Filed:

Nov 12, 2020

Appl. No.:

17/096354

Inventors:

- Lake Forest CA, US
Vinay T. Kamath - Rancho Santa Margarita CA, US
William Charles Winn Bielke - Lake Forest CA, US
Zhen Zhao - Sydney, AU

International Classification:

G06F 16/248
G06F 3/0481
G06F 16/17

Abstract:

Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework that automatically generates and dynamically updates an interactive user interface (UI) that comprises digital information related to multiple processes and operations. The UI provides uniform functionality across platforms, devices and/or services being utilized to view and/or interact with the UI and/or interface objects (e.g., tiles) included therein. The UI provides a dynamic mechanism for assets to be controlled, as well as mechanisms to compare the data of different assets by which certain assets can be subsequently manipulated. The UI enables the detection, and contextualized visualization of operational data for assets and/or locations in distributed supervisory control and data acquisition (SCADA) systems in Cloud connected environments.

US Patent:

20210080928, Mar 18, 2021

Filed:

Sep 15, 2020

Appl. No.:

17/021654

Inventors:

- Lake Forest CA, US
Prarthana Rohitkumar Shah - Lake Forest CA, US
Brian Kenneth Erickson - Lake Forest CA, US
William Charles Winn Bielke - Lake Forest CA, US

International Classification:

G05B 19/4063
G06N 3/08

Abstract:

A novel system includes an intelligent process anomaly detection and trend projection system which is configured to train artificial intelligence and machine learning systems for anomaly prediction in industrial systems according to some embodiments. In some embodiments, such intelligent process anomaly detection and trend projection system is configured to determine an estimated remaining useful life of an industrial asset. For example, in some embodiments, the system is configured to identify a degradation part of the signal and a normal part of the signal; separate the degradation part of the signal from the normal part of the signal; identify one or more patterns of a degradation part of the signal and the normal part of the signal; and determine an anomaly prediction based on the one or more patterns.