公开(公告)号：US11651627B2

公开(公告)日：2023-05-16

申请号：US16699023

申请日：2019-11-28

Applicant: Oracle International Corporation

Inventor： Amit Vaid ,  Neha Tomar ,  Utkarsh Milind Desai ,  Vijayalakshmi Krishnamurthy ,  Goldee Udani

IPC: G07C5/00 ,  G05B23/02 ,  G06Q10/0635 ,  G06Q10/20 ,  G07C5/08

CPC classification number: G07C5/006 ,  G05B23/024 ,  G05B23/0283 ,  G06Q10/0635 ,  G06Q10/20 ,  G07C5/0808

Abstract: Embodiments determine an optimized maintenance schedule for a maintenance program that includes multiple levels, each level including at least one asset (i.e., asset type) and at least one of the levels including a plurality of assets. Embodiments receive historical failure data for each of the assets, the historical failure data generated at least in part by a sensor network. For each asset, embodiments generate a probability density function (“PDF”) using kernel density estimation (“KDE”). For each asset, based on a reliability rate threshold, embodiments determine a cumulative density function (“CDF”) using the PDF. For each asset, embodiments determine an optimized time to failure (“TTF”) using the CDF. Embodiments then create the schedule for each level that includes a minimum TTF for the assets at each level.

公开(公告)号：US20240378489A1

公开(公告)日：2024-11-14

申请号：US18314880

申请日：2023-05-10

Applicant: Oracle International Corporation

Inventor： Suresh Kumar Golconda ,  Niclolas Kavantzas ,  Neha Tomar ,  Lubomir Nerad ,  Abhinav Kumar

IPC: G06N20/00

Abstract: The present disclosure relates to systems and methods for enhancing computer services with parallel models. A training dataset can be generated. Computer models can be trained using the training dataset. Second data can be partitioned into a set of data subsets. Each data subset can be allocated to a different computer model. Projections of data points can be generated by executing each computer model using a corresponding data subset. Relative differences between the projections can be determined. An output of the computer models can be provided by aggregating the projections of data points.