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Paul Michael Rahilly

from San Diego, CA
Age ~57
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Also known as:
Paul M Rahilly
Phone and address:
3200 6Th St, San Diego, CA 92103
Related to:
Mary Marda Hankinson, 88John MartiniskoMariasol Ortiz
Connected to:
Kevin A Rahilly, 54Thomas J Rahilly, 54Aamir R Rahim, 63Ahmed A Rahim, 63Ali Rahim, 61Amina RahimAndre A Rahim, 48Aziz A Rahim, 87Azrudeen R Rahim, 35Chowdhury F Rahim, 76

Paul Rahilly Phones & Addresses

  • 3200 6Th St, San Diego, CA 92103
  • 3940 7Th St, San Diego, CA 92103
  • New York, NY
  • Las Vegas, NV
  • Brooklyn, NY

Resumes

Resumes

Paul Rahilly Photo 1

Senior Director, Apm Technology Office

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Location:
San Diego, CA
Industry:
Computer Software
Work:
Aspen Technology
Senior Director, Apm Technology Office
Aspen Technology
Senior Director of Product Management
Mtell Aug 1997 - Oct 2016
Chief Executive Officer
Education:
University College Dublin 1985 - 1989
Bachelor of Engineering, Bachelors, Engineering, Mechanical Engineering St. Mary's College C.s.sp 1974 - 1985
Skills:
Automation
Integration
Project Management
Management
Process Automation
Software Development
Product Management
Scada
Software Project Management
Business Intelligence
Energy
Enterprise Software
Analytics
Cloud Computing
Business Strategy
Mobile Devices
Plc
Agile Methodologies
Microsoft Sql Server
Paul Rahilly Photo 2

Paul Rahilly

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Location:
Greater San Diego Area
Industry:
Oil & Energy

Business Records

Name / Title
Company / Classification
Phones & Addresses
Paul M. Rahilly
President
Mtelligence Corporation
Asset Management Services & Development of Intelligence Software
1550 Hotel Cir N, San Diego, CA 92108
9040 Friars Rd, San Diego, CA 92108
(619) 295-0022
Paul Rahilly
Principal
Interactive Facilities Corp
Computer Software · Nonclassifiable Establishments
3940 7 Ave UNIT 209, San Diego, CA 92103
Paul F. Rahilly
Pastor
Diocese of Rockville Center
Religious Organization · Catholic Elementary School
614 Central Ave, Cedarhurst, NY 11516
620 Central Ave, Cedarhurst, NY 11516
(516) 569-1845, (516) 569-2290
Paul Rahilly
Principal
Ifc Pacifica, LLC
Nonclassifiable Establishments · Real Estate Investment
110 W C St, San Diego, CA 92101

Publications

Us Patents

System And Methods For The Universal Integration Of Plant Floor Assets And A Computerized Management System

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US Patent:
20080271057, Oct 30, 2008
Filed:
Apr 26, 2007
Appl. No.:
11/740404
Inventors:
Alex BATES - San Diego CA, US
Paul RAHILLY - San Diego CA, US
Scott MACNAB - Wilsonville OR, US
Gordon BROOKS - San Diego CA, US
Assignee:
MTELLIGENCE CORPORATION - San Diego CA
International Classification:
G06F 3/00
US Classification:
719328
Abstract:
A server platform and a method to integrate a plurality of diverse plant floor equipment with at least one computerized management system in a manufacturing operational or maintenance system. The server platform includes a plurality of plant floor drivers adapted to communicatively interface with a plurality of diverse plant floor data sources. The server platform further includes at least one computerized management system driver adapted to communicatively interface with the at least one computerized management system. The server platform also includes a message translator adapted to broker communication between the plant floor data sources and the at least one computerized management system using an open standard. The server platform, using the open standard, enables a universal enterprise type taxonomy across the plant floor data sources and the at least one computerized management system.

Population-Based Learning With Deep Belief Networks

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US Patent:
20180082217, Mar 22, 2018
Filed:
Sep 29, 2017
Appl. No.:
15/721040
Inventors:
- San Diego CA, US
Caroline Kim - San Francisco CA, US
Paul Rahilly - San Diego CA, US
International Classification:
G06N 99/00
G05B 23/02
G05B 19/418
Abstract:
A plant asset failure prediction system and associated method. The method includes receiving user input identifying a first target set of equipment including a first plurality of units of equipment. A set of time series waveforms from sensors associated with the first plurality of units of equipment are received, the time series waveforms including sensor data values. A processor is configured to process the time series waveforms to generate a plurality of derived inputs wherein the derived inputs and the sensor data values collectively comprise sensor data. The method further includes determining whether a first machine learning agent may be configured to discriminate between first normal baseline data for the first target set of equipment and first failure signature information for the first target set of equipment. The first normal baseline data of the first target set of equipment may be derived from a first portion of the sensor data associated with operation of the first plurality of units of equipment in a first normal mode and the first failure signature information may be derived from a second portion of the sensor data associated with operation of the first plurality of units of equipment in a first failure mode. Monitored sensor signals produced by the one or more monitoring sensors are received. The first machine learning agent is then and activated, based upon the determining, to monitor data included within the monitored sensor signals.

System And Methods For Automated Plant Asset Failure Detection

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US Patent:
20170083830, Mar 23, 2017
Filed:
Nov 30, 2016
Appl. No.:
15/365607
Inventors:
- San Diego CA, US
Paul Rahilly - San Diego CA, US
Scott Macnab - San Diego CA, US
International Classification:
G06N 99/00
Abstract:
A system for performing failure signature recognition training for at least one unit of equipment. The system includes a memory and a processor coupled to the memory. The processor is configured by computer code to receive sensor data relating to the unit of equipment and to receive failure information relating to equipment failures. The processor is further configured to analyze the sensor data in view of the failure information in order to develop at least one learning agent for performing failure signature recognition with respect to the at least one unit of equipment.

System And Methods For The Universal Integration Of Plant Floor Assets And A Computerized Management System

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US Patent:
20160187872, Jun 30, 2016
Filed:
Sep 4, 2015
Appl. No.:
14/846553
Inventors:
- San Diego CA, US
Paul RAHILLY - San Diego CA, US
Scott MACNAB - Wilsonville OR, US
Gordon BROOKS - San Diego CA, US
International Classification:
G05B 19/418
H04L 12/24
Abstract:
A server platform and a method to integrate a plurality of diverse plant floor equipment with at least one computerized management system in a manufacturing operational or maintenance system. The server platform includes a plurality of plant floor drivers adapted to communicatively interface with a plurality of diverse plant floor data sources. The server platform further includes at least one computerized management system driver adapted to communicatively interface with the at least one computerized management system. The server platform also includes a message translator adapted to broker communication between the plant floor data sources and the at least one computerized management system using an open standard. The server platform, using the open standard, enables a universal enterprise type taxonomy across the plant floor data sources and the at least one computerized management system.

Population-Based Learning With Deep Belief Networks

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US Patent:
20160116378, Apr 28, 2016
Filed:
Aug 26, 2015
Appl. No.:
14/836848
Inventors:
- San Diego CA, US
Caroline Kim - San Diego CA, US
Paul Rahilly - San Diego CA, US
International Classification:
G01M 99/00
Abstract:
A plant asset failure prediction system and associated method. The method includes receiving user input identifying a first target set of equipment including a first plurality of units of equipment. A set of time series waveforms from sensors associated with the first plurality of units of equipment are received, the time series waveforms including sensor data values. A processor is configured to process the time series waveforms to generate a plurality of derived inputs wherein the derived inputs and the sensor data values collectively comprise sensor data. The method further includes determining whether a first machine learning agent may be configured to discriminate between first normal baseline data for the first target set of equipment and first failure signature information for the first target set of equipment. The first normal baseline data of the first target set of equipment may be derived from a first portion of the sensor data associated with operation of the first plurality of units of equipment in a first normal mode and the first failure signature information may be derived from a second portion of the sensor data associated with operation of the first plurality of units of equipment in a first failure mode. Monitored sensor signals produced by the one or more monitoring sensors are received. The first machine learning agent is then and activated, based upon the determining, to monitor data included within the monitored sensor signals.

System And Methods For Automated Plant Asset Failure Detection

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US Patent:
20140351642, Nov 27, 2014
Filed:
Mar 17, 2014
Appl. No.:
14/217265
Inventors:
Alexander B. BATES - San Diego CA, US
Paul RAHILLY - San Diego CA, US
Scott MACNAB - San Diego CA, US
Assignee:
MTELLIGENCE CORPORATION - San Diego CA
International Classification:
G06F 11/22
G06F 11/07
US Classification:
714 26
Abstract:
A system for performing failure signature recognition training for at least one unit of equipment. The system includes a memory and a processor coupled to the memory. The processor is configured by computer code to receive sensor data relating to the unit of equipment and to receive failure information relating to equipment failures. The processor is further configured to analyze the sensor data in view of the failure information in order to develop at least one learning agent for performing failure signature recognition with respect to the at least one unit of equipment.
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Paul Michael Rahilly from San Diego, CA, age ~57 Get Report