公开(公告)号：US20240210935A1

公开(公告)日：2024-06-27

申请号：US18087633

申请日：2022-12-22

Applicant: Delaware Capital Formation, Inc.

Inventor： Bodhayan Dev ,  Prem Swaroop ,  Richard Buteau ,  Girish Juneja ,  Sreedhar Patnala

IPC: G05B23/02

CPC classification number: G05B23/0283 ,  G05B23/0216 ,  G05B23/024

Abstract: Among other things, systems and techniques are described for a predictive model for determining overall equipment effectiveness (OEE) in industrial equipment. Data including spectral features is obtained. A probability of survival is determined by fitting at least one degradation function to degradation data associated with the industrial equipment. An overall equipment effectiveness metric is predicted as a product of predicted planned production time, predicted performance, and predicted quality output by trained machine learning models.

公开(公告)号：US20240319686A1

公开(公告)日：2024-09-26

申请号：US18609902

申请日：2024-03-19

Applicant: Delaware Capital Formation, Inc.

Inventor： Bodhayan Dev ,  Prem Swaroop

IPC: G05B13/04

CPC classification number: G05B13/041

Abstract: A process includes obtaining a target thermal load profile and a target location; determining weather conditions associated with the target location; simulating regulation of the target thermal load profile by different temperature regulation systems having different corresponding sets of components, subject to the weather conditions, to obtain energy consumption data for each of the different temperature regulation systems; and providing at least one of the different temperature regulation systems based on the energy consumption data, to cause use of the at least one of the different temperature regulation systems having the corresponding set of components.

公开(公告)号：US20230297058A1

公开(公告)日：2023-09-21

申请号：US18186903

申请日：2023-03-20

Applicant: Delaware Capital Formation, Inc.

Inventor： Bodhayan Dev ,  Atish P. Kamble ,  Prem Swaroop ,  Vijay Karthick Baskar ,  Richard Buteau ,  Sreedhar Patnala

IPC: G05B19/048 ,  H04W4/38

CPC classification number: G05B19/048 ,  H04W4/38 ,  G05B2219/24075

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for an end-to-end wireless sensor hub include: configuring a sensor hubs in an order using a sequence established by 5 a time of addition to a network. The sensor hubs is grouped into one or more groups. Sensor data captured by the one or more groups is obtained according to a current group number, wherein the sensor data is obtained from each group of the one or more groups according to a predetermined schedule.

公开(公告)号：US20240184282A1

公开(公告)日：2024-06-06

申请号：US18285449

申请日：2022-03-31

Applicant: Delaware Capital Formation, Inc.

Inventor： Bodhayan Dev ,  Atish P. Kamble ,  Prem Swaroop ,  Vijay Karthick Baskar ,  Richard Buteau ,  Sreedhar Patnala

IPC: G05B23/02 ,  F04C14/28

CPC classification number: G05B23/0283 ,  F04C14/28 ,  F04C2270/12 ,  F04C2270/80

Abstract: Among other things, systems and techniques are described for predictive maintenance of industrial equipment. Sensor data is obtained, e.g., using sensor hubs that are configured to capture sensor data associated with one or more operating conditions of the industrial equipment. The sensor data is input to a trained machine learning model. The trained machine learning model includes a physics based feature extraction model and a deep learning based automatic feature extraction model. Operating conditions associated with operation of the industrial equipment are predicted using the trained machine learning models.

公开(公告)号：US20240211798A1

公开(公告)日：2024-06-27

申请号：US18087630

申请日：2022-12-22

Applicant: Delaware Capital Formation, Inc.

Inventor： Prem Swaroop ,  Bodhayan Dev ,  Sreedhar Patnala ,  Girish Juneja

IPC: G06N20/00 ,  G06F11/34

CPC classification number: G06N20/00 ,  G06F11/3495

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer for an industrial machine-learning operation model monitoring system, that include the actions of receiving monitoring data for an industrial machine-learning operations model, determining, from the monitoring data, to retrain the industrial machine-learning operations model, where the determining includes computing drift parameters, each of the drift parameters being indicative of a type of observable drift of the industrial machine-learning operations model, where the drift parameters include (i) a usage drift, (ii) a performance drift, (iii) a data drift, and (iv) a prediction drift, and where each drift parameter includes a respective retraining criteria, and confirming, from the drift parameters, the respective retraining criteria is met by at least one of the drift parameters, and triggering, in response to the determining to retrain the industrial machine-learning operations model, an update of the industrial machine-learning operations model.

公开(公告)号：US20240193615A1

公开(公告)日：2024-06-13

申请号：US18287624

申请日：2022-04-20

Applicant: Delaware Capital Formation, Inc.

Inventor： Prem Swaroop ,  Bodhayan Dev ,  Atish P. Kamble ,  Girish Juneja ,  Jonah Somers

IPC: G06Q30/012

CPC classification number: G06Q30/012

Abstract: Among other things, techniques are described for an after-market service process digitization. Service data is obtained that is associated with at least one asset and comprises at least historical warranty data and current IoT data. Predictive analysis to generate an asset survival prediction is performed based on current data associated with a first asset and the service data. Troubleshooting data associated with the first asset from at least one knowledge data source is received. A warranty coverage metric is determined based on the asset survival prediction and the troubleshooting data, wherein the warranty coverage metric is calculated in real time according to the asset survival prediction and the troubleshooting data. The warranty coverage metric is transformed at a device into human-readable form.

公开(公告)号：US20220318616A1

公开(公告)日：2022-10-06

申请号：US17223525

申请日：2021-04-06

Applicant: Delaware Capital Formation, Inc.

Inventor： Atish P. Kamble ,  Prem Swaroop ,  Bodhayan Dev ,  Nicholas Möller

IPC: G06N3/08 ,  G06N3/04

Abstract: Among other things, techniques are described for predictive maintenance using vibration analysis of vane pumps. Sensor data is obtained and pre-processed the sensor data according to at least one feature extraction system. The features are extracted from the pre-processed sensor data and classified into at least one operating condition. A representation of the at least one operating condition is rendered at a device.