Submit Search
Upload
Cwin16 tls-faurecia predictive maintenance
•
0 likes
•
1,032 views
Capgemini
Follow
Predictive Maintenance or How Big Data is impacting on future factories?
Read less
Read more
Presentations & Public Speaking
Report
Share
Report
Share
1 of 21
Download now
Download to read offline
Recommended
Cwin16 tls cnes-realite_augmentee_eng_v1 2
Cwin16 tls cnes-realite_augmentee_eng_v1 2
Capgemini
Alan Southall, SVP of Engineering, Head of IoT Predictive Maintenance, SAP
Alan Southall, SVP of Engineering, Head of IoT Predictive Maintenance, SAP
MIT Enterprise Forum Cambridge
Logicalis IoT & Smart Cities (Use Case)
Logicalis IoT & Smart Cities (Use Case)
Cloudera, Inc.
Cwin16 tls-partner-mark logic-an innovation journey in manufacturing
Cwin16 tls-partner-mark logic-an innovation journey in manufacturing
Capgemini
ttec - ParStream
ttec - ParStream
Marco van der Hart
Michael Hummel - Stop Storing Data! - Parstream
Michael Hummel - Stop Storing Data! - Parstream
Business of Software Conference
AI in Software for Augmenting Intelligence Across the Enterprise
AI in Software for Augmenting Intelligence Across the Enterprise
The Hive
IoTMeetup
IoTMeetup
Shivanshu Upadhyay
Recommended
Cwin16 tls cnes-realite_augmentee_eng_v1 2
Cwin16 tls cnes-realite_augmentee_eng_v1 2
Capgemini
Alan Southall, SVP of Engineering, Head of IoT Predictive Maintenance, SAP
Alan Southall, SVP of Engineering, Head of IoT Predictive Maintenance, SAP
MIT Enterprise Forum Cambridge
Logicalis IoT & Smart Cities (Use Case)
Logicalis IoT & Smart Cities (Use Case)
Cloudera, Inc.
Cwin16 tls-partner-mark logic-an innovation journey in manufacturing
Cwin16 tls-partner-mark logic-an innovation journey in manufacturing
Capgemini
ttec - ParStream
ttec - ParStream
Marco van der Hart
Michael Hummel - Stop Storing Data! - Parstream
Michael Hummel - Stop Storing Data! - Parstream
Business of Software Conference
AI in Software for Augmenting Intelligence Across the Enterprise
AI in Software for Augmenting Intelligence Across the Enterprise
The Hive
IoTMeetup
IoTMeetup
Shivanshu Upadhyay
Data Science in the Enterprise
Data Science in the Enterprise
The Hive
Next-Gen ML/AI Platform
Next-Gen ML/AI Platform
Josh Yeh
Is it sensible to use Data Vault at all? Conclusions from a project.
Is it sensible to use Data Vault at all? Conclusions from a project.
Capgemini
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
The Hive
GITEX Big Data Conference 2014 – SAP Presentation
GITEX Big Data Conference 2014 – SAP Presentation
Pedro Pereira
Dell Digital Transformation Through AI and Data Analytics Webinar
Dell Digital Transformation Through AI and Data Analytics Webinar
Bill Wong
Innovation Without Compromise: The Challenges of Securing Big Data
Innovation Without Compromise: The Challenges of Securing Big Data
Cloudera, Inc.
Meet up roadmap cloudera 2020 - janeiro
Meet up roadmap cloudera 2020 - janeiro
Thiago Santiago
MT84 IoT and Smart Manufacturing Innovations
MT84 IoT and Smart Manufacturing Innovations
Dell EMC World
AWS O&G Day - Ambyint and AWS
AWS O&G Day - Ambyint and AWS
AWS Summits
BLD() Tech Conference — Data exploration with KSQL
BLD() Tech Conference — Data exploration with KSQL
Gillis J. de Nijs
Harel Kodesh, Vice President, Predix and CTO, GE Digital
Harel Kodesh, Vice President, Predix and CTO, GE Digital
MIT Enterprise Forum Cambridge
Digital Transformation; Digital Twins for Delivering Business Value in IIoT
Digital Transformation; Digital Twins for Delivering Business Value in IIoT
The Hive
Artificial Intelligence Application in Oil and Gas
Artificial Intelligence Application in Oil and Gas
SparkCognition
AIOps: Your DevOps Co-Pilot
AIOps: Your DevOps Co-Pilot
DevOps.com
Meetup 27/6/2018: AIOPS om de uitdagingen van een slimme stad te ondersteunen
Meetup 27/6/2018: AIOPS om de uitdagingen van een slimme stad te ondersteunen
Digipolis Antwerpen
Data as the New Oil: Producing Value in the Oil and Gas Industry
Data as the New Oil: Producing Value in the Oil and Gas Industry
VMware Tanzu
Hey IT, Meet OT with Hima Mukkamala
Hey IT, Meet OT with Hima Mukkamala
gogo6
Accelerating big data with ioMemory and Cisco UCS and NOSQL
Accelerating big data with ioMemory and Cisco UCS and NOSQL
Sumeet Bansal
Building the Next Generation IoT & Telematics Platform
Building the Next Generation IoT & Telematics Platform
Cloudera, Inc.
Predictive Maintenance by analysing acoustic data in an industrial environment
Predictive Maintenance by analysing acoustic data in an industrial environment
Capgemini
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
Daniel Westzaan
More Related Content
What's hot
Data Science in the Enterprise
Data Science in the Enterprise
The Hive
Next-Gen ML/AI Platform
Next-Gen ML/AI Platform
Josh Yeh
Is it sensible to use Data Vault at all? Conclusions from a project.
Is it sensible to use Data Vault at all? Conclusions from a project.
Capgemini
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
The Hive
GITEX Big Data Conference 2014 – SAP Presentation
GITEX Big Data Conference 2014 – SAP Presentation
Pedro Pereira
Dell Digital Transformation Through AI and Data Analytics Webinar
Dell Digital Transformation Through AI and Data Analytics Webinar
Bill Wong
Innovation Without Compromise: The Challenges of Securing Big Data
Innovation Without Compromise: The Challenges of Securing Big Data
Cloudera, Inc.
Meet up roadmap cloudera 2020 - janeiro
Meet up roadmap cloudera 2020 - janeiro
Thiago Santiago
MT84 IoT and Smart Manufacturing Innovations
MT84 IoT and Smart Manufacturing Innovations
Dell EMC World
AWS O&G Day - Ambyint and AWS
AWS O&G Day - Ambyint and AWS
AWS Summits
BLD() Tech Conference — Data exploration with KSQL
BLD() Tech Conference — Data exploration with KSQL
Gillis J. de Nijs
Harel Kodesh, Vice President, Predix and CTO, GE Digital
Harel Kodesh, Vice President, Predix and CTO, GE Digital
MIT Enterprise Forum Cambridge
Digital Transformation; Digital Twins for Delivering Business Value in IIoT
Digital Transformation; Digital Twins for Delivering Business Value in IIoT
The Hive
Artificial Intelligence Application in Oil and Gas
Artificial Intelligence Application in Oil and Gas
SparkCognition
AIOps: Your DevOps Co-Pilot
AIOps: Your DevOps Co-Pilot
DevOps.com
Meetup 27/6/2018: AIOPS om de uitdagingen van een slimme stad te ondersteunen
Meetup 27/6/2018: AIOPS om de uitdagingen van een slimme stad te ondersteunen
Digipolis Antwerpen
Data as the New Oil: Producing Value in the Oil and Gas Industry
Data as the New Oil: Producing Value in the Oil and Gas Industry
VMware Tanzu
Hey IT, Meet OT with Hima Mukkamala
Hey IT, Meet OT with Hima Mukkamala
gogo6
Accelerating big data with ioMemory and Cisco UCS and NOSQL
Accelerating big data with ioMemory and Cisco UCS and NOSQL
Sumeet Bansal
Building the Next Generation IoT & Telematics Platform
Building the Next Generation IoT & Telematics Platform
Cloudera, Inc.
What's hot
(20)
Data Science in the Enterprise
Data Science in the Enterprise
Next-Gen ML/AI Platform
Next-Gen ML/AI Platform
Is it sensible to use Data Vault at all? Conclusions from a project.
Is it sensible to use Data Vault at all? Conclusions from a project.
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
GITEX Big Data Conference 2014 – SAP Presentation
GITEX Big Data Conference 2014 – SAP Presentation
Dell Digital Transformation Through AI and Data Analytics Webinar
Dell Digital Transformation Through AI and Data Analytics Webinar
Innovation Without Compromise: The Challenges of Securing Big Data
Innovation Without Compromise: The Challenges of Securing Big Data
Meet up roadmap cloudera 2020 - janeiro
Meet up roadmap cloudera 2020 - janeiro
MT84 IoT and Smart Manufacturing Innovations
MT84 IoT and Smart Manufacturing Innovations
AWS O&G Day - Ambyint and AWS
AWS O&G Day - Ambyint and AWS
BLD() Tech Conference — Data exploration with KSQL
BLD() Tech Conference — Data exploration with KSQL
Harel Kodesh, Vice President, Predix and CTO, GE Digital
Harel Kodesh, Vice President, Predix and CTO, GE Digital
Digital Transformation; Digital Twins for Delivering Business Value in IIoT
Digital Transformation; Digital Twins for Delivering Business Value in IIoT
Artificial Intelligence Application in Oil and Gas
Artificial Intelligence Application in Oil and Gas
AIOps: Your DevOps Co-Pilot
AIOps: Your DevOps Co-Pilot
Meetup 27/6/2018: AIOPS om de uitdagingen van een slimme stad te ondersteunen
Meetup 27/6/2018: AIOPS om de uitdagingen van een slimme stad te ondersteunen
Data as the New Oil: Producing Value in the Oil and Gas Industry
Data as the New Oil: Producing Value in the Oil and Gas Industry
Hey IT, Meet OT with Hima Mukkamala
Hey IT, Meet OT with Hima Mukkamala
Accelerating big data with ioMemory and Cisco UCS and NOSQL
Accelerating big data with ioMemory and Cisco UCS and NOSQL
Building the Next Generation IoT & Telematics Platform
Building the Next Generation IoT & Telematics Platform
Viewers also liked
Predictive Maintenance by analysing acoustic data in an industrial environment
Predictive Maintenance by analysing acoustic data in an industrial environment
Capgemini
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
Daniel Westzaan
Predictive Maintenance
Predictive Maintenance
Saama
What is predictive maintenance?
What is predictive maintenance?
Danko Nikolic
The Science of Predictive Maintenance: IBM's Predictive Analytics Solution
The Science of Predictive Maintenance: IBM's Predictive Analytics Solution
Senturus
Predictive maintenance
Predictive maintenance
James Shearer
Business Insight and Predictive Analysis
Business Insight and Predictive Analysis
USAID CEED II Project Moldova
DATA FORUM MICROPOLE 2015 - Atelier Talend
DATA FORUM MICROPOLE 2015 - Atelier Talend
Micropole Group
Predictive maintenance
Predictive maintenance
Elena Maria Vaccher
Predictive Analysis
Predictive Analysis
Michael Bystry
Ibm ofa ottawa_analytics_in_gov _campbell_robertson
Ibm ofa ottawa_analytics_in_gov _campbell_robertson
dawnrk
Déjeuner Conférence - La maintenance à l'ère du prédictif
Déjeuner Conférence - La maintenance à l'ère du prédictif
agileDSS
Witekio introducing-predictive-maintenance
Witekio introducing-predictive-maintenance
Witekio
Predictive analysis and modelling
Predictive analysis and modelling
lalit Lalitm7225
Predictive analysis
Predictive analysis
Vedprakash Srivastava
Maintenance Big Data Multi-Cloud Infrastructure: Notes from the Fields by Dzm...
Maintenance Big Data Multi-Cloud Infrastructure: Notes from the Fields by Dzm...
Dzmitry Durasau
BigData in IoT #iotconfua
BigData in IoT #iotconfua
Andy Shutka
Using the Industrial Internet to Move From Planned Maintenance to Predictive ...
Using the Industrial Internet to Move From Planned Maintenance to Predictive ...
Sentient Science
Présentation simulation des flux
Présentation simulation des flux
Capgemini
The Data Science behind Predictive Maintenance for Connected Vehicles
The Data Science behind Predictive Maintenance for Connected Vehicles
Esther Vasiete
Viewers also liked
(20)
Predictive Maintenance by analysing acoustic data in an industrial environment
Predictive Maintenance by analysing acoustic data in an industrial environment
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
Predictive Maintenance
Predictive Maintenance
What is predictive maintenance?
What is predictive maintenance?
The Science of Predictive Maintenance: IBM's Predictive Analytics Solution
The Science of Predictive Maintenance: IBM's Predictive Analytics Solution
Predictive maintenance
Predictive maintenance
Business Insight and Predictive Analysis
Business Insight and Predictive Analysis
DATA FORUM MICROPOLE 2015 - Atelier Talend
DATA FORUM MICROPOLE 2015 - Atelier Talend
Predictive maintenance
Predictive maintenance
Predictive Analysis
Predictive Analysis
Ibm ofa ottawa_analytics_in_gov _campbell_robertson
Ibm ofa ottawa_analytics_in_gov _campbell_robertson
Déjeuner Conférence - La maintenance à l'ère du prédictif
Déjeuner Conférence - La maintenance à l'ère du prédictif
Witekio introducing-predictive-maintenance
Witekio introducing-predictive-maintenance
Predictive analysis and modelling
Predictive analysis and modelling
Predictive analysis
Predictive analysis
Maintenance Big Data Multi-Cloud Infrastructure: Notes from the Fields by Dzm...
Maintenance Big Data Multi-Cloud Infrastructure: Notes from the Fields by Dzm...
BigData in IoT #iotconfua
BigData in IoT #iotconfua
Using the Industrial Internet to Move From Planned Maintenance to Predictive ...
Using the Industrial Internet to Move From Planned Maintenance to Predictive ...
Présentation simulation des flux
Présentation simulation des flux
The Data Science behind Predictive Maintenance for Connected Vehicles
The Data Science behind Predictive Maintenance for Connected Vehicles
Similar to Cwin16 tls-faurecia predictive maintenance
Cwin16 tls-iot approach-applied_in_the_plm_domain
Cwin16 tls-iot approach-applied_in_the_plm_domain
Capgemini
Cwin16 - Paris- m rapid
Cwin16 - Paris- m rapid
Capgemini
Bitrock manufacturing
Bitrock manufacturing
cosma_r
2018 McRock Capital IIoT Symposium: Antonio Pietri, Aspentech
2018 McRock Capital IIoT Symposium: Antonio Pietri, Aspentech
MTechHub
CeBIT 2016 - The Data Centre in the age of Microservices
CeBIT 2016 - The Data Centre in the age of Microservices
Gunnar Menzel
Cwin16 tls-partner-sas new-open_analytics_platform
Cwin16 tls-partner-sas new-open_analytics_platform
Capgemini
CWIN17 Toulouse / Industrial big data and mes, the winning combination to imp...
CWIN17 Toulouse / Industrial big data and mes, the winning combination to imp...
Capgemini
The Future of Infrastructure: Key Trends to consider
The Future of Infrastructure: Key Trends to consider
Capgemini
Future-Proofing Asset Failures with Cognitive Predictive Maintenance
Future-Proofing Asset Failures with Cognitive Predictive Maintenance
Anita Raj
Big Data - A Real Life Revolution
Big Data - A Real Life Revolution
Capgemini
Meetup Spark UDF performance
Meetup Spark UDF performance
Guilherme Braccialli
Power ai nordics dcm
Power ai nordics dcm
IBM Sverige
Paris FOD Meetup #5 Cognizant Presentation
Paris FOD Meetup #5 Cognizant Presentation
Abdelkrim Hadjidj
Capgemini’s Data WARP: Accelerate your Journey to Insights
Capgemini’s Data WARP: Accelerate your Journey to Insights
Capgemini
CWIN17 Toulouse / Additive manufacturing and cognitive augmented design 3 ds-...
CWIN17 Toulouse / Additive manufacturing and cognitive augmented design 3 ds-...
Capgemini
Miguel Angel Perdiguero - Head of BIG data & analytics Atos Iberia - semanain...
Miguel Angel Perdiguero - Head of BIG data & analytics Atos Iberia - semanain...
COIICV
Data warehouse modernization programme by TOBY WOOLFE at Big Data Spain 2014
Data warehouse modernization programme by TOBY WOOLFE at Big Data Spain 2014
Big Data Spain
Cwin16 tls-datalab for scientists
Cwin16 tls-datalab for scientists
Capgemini
IBM Power Systems Update 1Q17
IBM Power Systems Update 1Q17
David Spurway
MongoDB World 2019: Data Digital Decoupling
MongoDB World 2019: Data Digital Decoupling
MongoDB
Similar to Cwin16 tls-faurecia predictive maintenance
(20)
Cwin16 tls-iot approach-applied_in_the_plm_domain
Cwin16 tls-iot approach-applied_in_the_plm_domain
Cwin16 - Paris- m rapid
Cwin16 - Paris- m rapid
Bitrock manufacturing
Bitrock manufacturing
2018 McRock Capital IIoT Symposium: Antonio Pietri, Aspentech
2018 McRock Capital IIoT Symposium: Antonio Pietri, Aspentech
CeBIT 2016 - The Data Centre in the age of Microservices
CeBIT 2016 - The Data Centre in the age of Microservices
Cwin16 tls-partner-sas new-open_analytics_platform
Cwin16 tls-partner-sas new-open_analytics_platform
CWIN17 Toulouse / Industrial big data and mes, the winning combination to imp...
CWIN17 Toulouse / Industrial big data and mes, the winning combination to imp...
The Future of Infrastructure: Key Trends to consider
The Future of Infrastructure: Key Trends to consider
Future-Proofing Asset Failures with Cognitive Predictive Maintenance
Future-Proofing Asset Failures with Cognitive Predictive Maintenance
Big Data - A Real Life Revolution
Big Data - A Real Life Revolution
Meetup Spark UDF performance
Meetup Spark UDF performance
Power ai nordics dcm
Power ai nordics dcm
Paris FOD Meetup #5 Cognizant Presentation
Paris FOD Meetup #5 Cognizant Presentation
Capgemini’s Data WARP: Accelerate your Journey to Insights
Capgemini’s Data WARP: Accelerate your Journey to Insights
CWIN17 Toulouse / Additive manufacturing and cognitive augmented design 3 ds-...
CWIN17 Toulouse / Additive manufacturing and cognitive augmented design 3 ds-...
Miguel Angel Perdiguero - Head of BIG data & analytics Atos Iberia - semanain...
Miguel Angel Perdiguero - Head of BIG data & analytics Atos Iberia - semanain...
Data warehouse modernization programme by TOBY WOOLFE at Big Data Spain 2014
Data warehouse modernization programme by TOBY WOOLFE at Big Data Spain 2014
Cwin16 tls-datalab for scientists
Cwin16 tls-datalab for scientists
IBM Power Systems Update 1Q17
IBM Power Systems Update 1Q17
MongoDB World 2019: Data Digital Decoupling
MongoDB World 2019: Data Digital Decoupling
More from Capgemini
Top Healthcare Trends 2022
Top Healthcare Trends 2022
Capgemini
Top P&C Insurance Trends 2022
Top P&C Insurance Trends 2022
Capgemini
Commercial Banking Trends book 2022
Commercial Banking Trends book 2022
Capgemini
Top Trends in Payments 2022
Top Trends in Payments 2022
Capgemini
Top Trends in Wealth Management 2022
Top Trends in Wealth Management 2022
Capgemini
Retail Banking Trends book 2022
Retail Banking Trends book 2022
Capgemini
Top Life Insurance Trends 2022
Top Life Insurance Trends 2022
Capgemini
キャップジェミニ、あなたの『RISE WITH SAP』のパートナーです
キャップジェミニ、あなたの『RISE WITH SAP』のパートナーです
Capgemini
Property & Casualty Insurance Top Trends 2021
Property & Casualty Insurance Top Trends 2021
Capgemini
Life Insurance Top Trends 2021
Life Insurance Top Trends 2021
Capgemini
Top Trends in Commercial Banking: 2021
Top Trends in Commercial Banking: 2021
Capgemini
Top Trends in Wealth Management: 2021
Top Trends in Wealth Management: 2021
Capgemini
Top Trends in Payments: 2021
Top Trends in Payments: 2021
Capgemini
Health Insurance Top Trends 2021
Health Insurance Top Trends 2021
Capgemini
Top Trends in Retail Banking: 2021
Top Trends in Retail Banking: 2021
Capgemini
Capgemini’s Connected Autonomous Planning
Capgemini’s Connected Autonomous Planning
Capgemini
Top Trends in Retail Banking: 2020
Top Trends in Retail Banking: 2020
Capgemini
Top Trends in Life Insurance: 2020
Top Trends in Life Insurance: 2020
Capgemini
Top Trends in Health Insurance: 2020
Top Trends in Health Insurance: 2020
Capgemini
Top Trends in Payments: 2020
Top Trends in Payments: 2020
Capgemini
More from Capgemini
(20)
Top Healthcare Trends 2022
Top Healthcare Trends 2022
Top P&C Insurance Trends 2022
Top P&C Insurance Trends 2022
Commercial Banking Trends book 2022
Commercial Banking Trends book 2022
Top Trends in Payments 2022
Top Trends in Payments 2022
Top Trends in Wealth Management 2022
Top Trends in Wealth Management 2022
Retail Banking Trends book 2022
Retail Banking Trends book 2022
Top Life Insurance Trends 2022
Top Life Insurance Trends 2022
キャップジェミニ、あなたの『RISE WITH SAP』のパートナーです
キャップジェミニ、あなたの『RISE WITH SAP』のパートナーです
Property & Casualty Insurance Top Trends 2021
Property & Casualty Insurance Top Trends 2021
Life Insurance Top Trends 2021
Life Insurance Top Trends 2021
Top Trends in Commercial Banking: 2021
Top Trends in Commercial Banking: 2021
Top Trends in Wealth Management: 2021
Top Trends in Wealth Management: 2021
Top Trends in Payments: 2021
Top Trends in Payments: 2021
Health Insurance Top Trends 2021
Health Insurance Top Trends 2021
Top Trends in Retail Banking: 2021
Top Trends in Retail Banking: 2021
Capgemini’s Connected Autonomous Planning
Capgemini’s Connected Autonomous Planning
Top Trends in Retail Banking: 2020
Top Trends in Retail Banking: 2020
Top Trends in Life Insurance: 2020
Top Trends in Life Insurance: 2020
Top Trends in Health Insurance: 2020
Top Trends in Health Insurance: 2020
Top Trends in Payments: 2020
Top Trends in Payments: 2020
Recently uploaded
Engaging Eid Ul Fitr Presentation for Kindergartners.pptx
Engaging Eid Ul Fitr Presentation for Kindergartners.pptx
AsifArshad8
Chizaram's Women Tech Makers Deck. .pptx
Chizaram's Women Tech Makers Deck. .pptx
ogubuikealex
Testing with Fewer Resources: Toward Adaptive Approaches for Cost-effective ...
Testing with Fewer Resources: Toward Adaptive Approaches for Cost-effective ...
Sebastiano Panichella
General Elections Final Press Noteas per M
General Elections Final Press Noteas per M
VidyaAdsule1
Don't Miss Out: Strategies for Making the Most of the Ethena DigitalOpportunity
Don't Miss Out: Strategies for Making the Most of the Ethena DigitalOpportunity
App Ethena
Testing and Development Challenges for Complex Cyber-Physical Systems: Insigh...
Testing and Development Challenges for Complex Cyber-Physical Systems: Insigh...
Sebastiano Panichella
Application of GIS in Landslide Disaster Response.pptx
Application of GIS in Landslide Disaster Response.pptx
Roquia Salam
Internship Presentation | PPT | CSE | SE
Internship Presentation | PPT | CSE | SE
Saleh Ibne Omar
A Guide to Choosing the Ideal Air Cooler
A Guide to Choosing the Ideal Air Cooler
enquirieskenstar
05.02 MMC - Assignment 4 - Image Attribution Lovepreet.pptx
05.02 MMC - Assignment 4 - Image Attribution Lovepreet.pptx
erickamwana1
GESCO SE Press and Analyst Conference on Financial Results 2024
GESCO SE Press and Analyst Conference on Financial Results 2024
GESCO SE
INDIAN GCP GUIDELINE. for Regulatory affair 1st sem CRR
INDIAN GCP GUIDELINE. for Regulatory affair 1st sem CRR
sarwankumar4524
proposal kumeneger edited.docx A kumeeger
proposal kumeneger edited.docx A kumeeger
kumenegertelayegrama
Quality by design.. ppt for RA (1ST SEM
Quality by design.. ppt for RA (1ST SEM
Charmi13
RACHEL-ANN M. TENIBRO PRODUCT RESEARCH PRESENTATION
RACHEL-ANN M. TENIBRO PRODUCT RESEARCH PRESENTATION
RachelAnnTenibroAmaz
THE COUNTRY WHO SOLVED THE WORLD_HOW CHINA LAUNCHED THE CIVILIZATION REVOLUTI...
THE COUNTRY WHO SOLVED THE WORLD_HOW CHINA LAUNCHED THE CIVILIZATION REVOLUTI...
漢銘 謝
cse-csp batch4 review-1.1.pptx cyber security
cse-csp batch4 review-1.1.pptx cyber security
sandeepnani2260
Recently uploaded
(17)
Engaging Eid Ul Fitr Presentation for Kindergartners.pptx
Engaging Eid Ul Fitr Presentation for Kindergartners.pptx
Chizaram's Women Tech Makers Deck. .pptx
Chizaram's Women Tech Makers Deck. .pptx
Testing with Fewer Resources: Toward Adaptive Approaches for Cost-effective ...
Testing with Fewer Resources: Toward Adaptive Approaches for Cost-effective ...
General Elections Final Press Noteas per M
General Elections Final Press Noteas per M
Don't Miss Out: Strategies for Making the Most of the Ethena DigitalOpportunity
Don't Miss Out: Strategies for Making the Most of the Ethena DigitalOpportunity
Testing and Development Challenges for Complex Cyber-Physical Systems: Insigh...
Testing and Development Challenges for Complex Cyber-Physical Systems: Insigh...
Application of GIS in Landslide Disaster Response.pptx
Application of GIS in Landslide Disaster Response.pptx
Internship Presentation | PPT | CSE | SE
Internship Presentation | PPT | CSE | SE
A Guide to Choosing the Ideal Air Cooler
A Guide to Choosing the Ideal Air Cooler
05.02 MMC - Assignment 4 - Image Attribution Lovepreet.pptx
05.02 MMC - Assignment 4 - Image Attribution Lovepreet.pptx
GESCO SE Press and Analyst Conference on Financial Results 2024
GESCO SE Press and Analyst Conference on Financial Results 2024
INDIAN GCP GUIDELINE. for Regulatory affair 1st sem CRR
INDIAN GCP GUIDELINE. for Regulatory affair 1st sem CRR
proposal kumeneger edited.docx A kumeeger
proposal kumeneger edited.docx A kumeeger
Quality by design.. ppt for RA (1ST SEM
Quality by design.. ppt for RA (1ST SEM
RACHEL-ANN M. TENIBRO PRODUCT RESEARCH PRESENTATION
RACHEL-ANN M. TENIBRO PRODUCT RESEARCH PRESENTATION
THE COUNTRY WHO SOLVED THE WORLD_HOW CHINA LAUNCHED THE CIVILIZATION REVOLUTI...
THE COUNTRY WHO SOLVED THE WORLD_HOW CHINA LAUNCHED THE CIVILIZATION REVOLUTI...
cse-csp batch4 review-1.1.pptx cyber security
cse-csp batch4 review-1.1.pptx cyber security
Cwin16 tls-faurecia predictive maintenance
1.
Maintenance Predictive ou
comment le Big Data révolutionne les usines du futur AIE Suresnes, 26 Septembre 2016 Capgemini, Capgemini Consulting, Sogeti HT
2.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 2 Table of Contents Enjeux, contexte et bénéfices Solutions techniques Big Data Applications IBM PMQ et Braincube
3.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 3 Manufacturing Intelligence => Braincube Predictive Maintenance => PMQ Faurecia Digital Enterprise Project 3- Prepare Rapid Scale-Up 2- Experiment and Learn 1- Explore & Design FEB. 2015 SEPT. 2015 200 digital use cases 40 Proofs of concept 9 solutions Deploy 40 sites Deploy 40 sites END. 2018 2016 2017 2018 Pilot 6 sites Industrialize Deploy 14 sites A systemic approach, at the speed of light
4.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 4 Digital Enterprise Manufacturing Intelligence & Predictive Maintenance Big data benefits Why do we implement Big Data initiative? Improve productivity OEE*, Improve production flows, stock, … Optimization cost of energy, utilities, indirect cost Accelerate run at rate (loss of raw material, FMC) Run Plant respecting standards Reduce product quality issues Reduce scrap Anticipation of non-quality with alerts and recommendations Reduce key equipment issues Minimize unscheduled downtime and breakdowns Manage business opportunities such as insourcing capacity Increased equipment life cycle (*) OEE stand for Overall Equipment Effectiveness (« Taux de Rendement Synthétique » in French) Manufacturing Intelligence Monitor production process in real time And make decisions based on data Predictive Maintenance Predict potential breakdowns of a machine through data analysis and historian 2 families of Big Data tools in Operations Monitor & alert in real time production parameters Display tuning information to the operator on the shop floor Keep production line stability for all shifts Benchmark plants
5.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 5 Table of Contents Enjeux, contexte et bénéfices Solutions techniques Big Data Applications IBM PMQ et Braincube
6.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 6 Commencer par démontrer l’intérêt d’une architecture Big Data au centre de la solution globale via un pilote A pilot… In time boxing (3 months on Big Insights environment with plants data) Thru simulated flow in a first step and then connected to plants Real-time data flows implementation, reusable for industrialization Analytics : demo of some possibilities Manufacturing Intelligence (Braincube) Predictive Maintenance (IBM PMQ) Plants Plants … sensors sensors 1 2 3 3 4 4 1 2 3 4 IBM Cloud/Hadoop infrastructures One shot data initialization Real time simulation alimentation Direct real time alimentation 3 2 5 5 Analytics & discovery Open Data, External Data, etc.
7.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 7 Définir l’architecture Big Data cible en fonction des besoins Architecture Framework for Predictive Maintenance Simplified Architecture Functions and Technologies ❶ Data ingestion of Ticketing Data and Traceability Data ❷ Data storage of Process Data, Traceability Data and Ticketing Data Ticketing Data Traceability Data SAP logs Other Data ❸ Processing to calculate KPI’s, traceability and graphs preparation ❹Visualization of KPI’s Predictive Maintenance (IBM PMQ) Usage Analytics Visualization API / Drivers Structuration Processing SQL NoSQL Storage Hadoop HDFS Warehouse In memory Ingestion Batch Micro Batch Real time 1 2 3 4 1 2 3 4 ❶ Real time ingestion of Process Data from Plants ❷ In memory storage of Process Data ❸ Trans-coding for PMQ and Braincube ❹ Publishing to PMQ with Kafka and Braincube with HTTPs Manufacturing Intelligence (Braincube) Process Data Kafka Kafka Kafka BigInsights 3 5 ❺Data Discovery ❶ Batch layer ❶ Stream layer
8.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 8 Retour concrets et intérêts du Big Data ❶ Single point of entry - reduce the load on PCo side - distribute the process data to all analytical components ❷ Storage capacities - centralization of data in one place - available for any type of request from MI/PM ❸ Analytics & discovery - computing power for custom analytics - direct analytical functions ❹ Data Publishing - compatible with current & new partners - custom data visualization Manufacturing Intelligence (Braincube) Predictive Maintenance (IBM PMQ) PCOOther Data Big Data TraçaStratos
9.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 9 Quelques visualisations possibles des données dans HDFS Ingestion Plants Monitoring Storage Processing Visualization Plants Processing Parts Traceability IT Ticketing Flat filesExternal Databases Real Time Process Data
10.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 10 Table of Contents Enjeux, contexte et bénéfices Solutions techniques Big Data Applications IBM PMQ et Braincube
11.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 11 Predictive Maintenance – Principe et mise en œuvre avec PMQ Visualisation & Usage Data AnalysisData Storage & StructurationData Collect 7.5 5 min. DATA COLLECTION DATA STRUCTURATION MODEL & ANALYSE DEPLOY & IMPROVE OBJECTIVES & DATA IDENTIFICATION Define clear objectives Identify if relevant data are available Prepare Change MIPM DEPLOYMENT Industrial IS Machines connected Data collection Secure & scalable Data structuration Data Lake Analytics platform Monitoring Modeling Dashboarding Deployment Adapt, optimize Change management 1. Récupération des données du data lake en temps réel 2. Traitement sur intervalles puis mise à disposition d’un modèle prédictif (algorithme) 3. Le modèle établit un score d’anomalies 4. Interprétation et décision Machine learning : Détection d’anomalies corrélée à une base d’apprentissage et de connaissances. Performance: Disposer de modèles pertinents avec des données significatives , d’un contexte métier et des process.
12.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 12 Predictive Maintenance – Illustration avec machine de Fine blanking
13.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 13
14.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 14
15.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 15
16.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 16
17.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 17 Into data: a concrete example on Big data for an automotive supplier Data Driven Production • Manufacturing Intelligence What we wanted to achieve with BIG DATA Reduce scraps Quickly investigate a production problem 19 Equipment on the line A measure every 1s 60 000 s in a production day 220 days of production > 20 parameters by equipment followed in real time X X 5 Billions data available for analyse in 1 year of production XX = BRAINCUBE Solution
18.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 18 How we can do that: Reduce scraps on dashboard « It is not knowing what to do, it’s doing what you know » Anthony Robbins 2015 06 Scrap at the FRIMO Manufacturing intelligence is about undestanding what makes your production green and repeat it Guides & Rules
19.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 19 Braincube found a way to adjust production settings that reduce scraps Rule – RHD2 Lookint at only 2 parameters combined (temperature galvano & thickness) ... 1 : Good parts went from 96 to 98,2% 4 ...we were 3,8% time with a setting that generate few scraps... The analytics say that we could be up to 40% time in this favourable situation 4 And save M€ ! 5 ...During the past 27 days... 32
20.
Presentation Title |
Date Copyright © 2016 Capgemini and Sogeti. All rights reserved. 20 A collaborative plateform to share the production status in real time FROM DATA TO FACTS BASED ACTIONS ON THE PRODUCTION LINE Manufacturing Intelligence Site manager, COO, BU manager •Production line manager •Quality manager •Methods •Process engineering •Operator on the shop floor
21.
www.capgemini.com The information contained
in this presentation is proprietary. Copyright © 2016 Capgemini and Sogeti. All rights reserved. Rightshore® is a trademark belonging to Capgemini. www.sogeti.com About Capgemini and Sogeti With more than 180,000 people in over 40 countries, Capgemini is a global leader in consulting, technology and outsourcing services. The Group reported 2015 global revenues of EUR 11.9 billion. Together with its clients, Capgemini creates and delivers business, technology and digital solutions that fit their needs, enabling them to achieve innovation and competitiveness. A deeply multicultural organization, Capgemini has developed its own way of working, the Collaborative Business Experience™, and draws on Rightshore®, its worldwide delivery model. Sogeti is a leading provider of technology and software testing, specializing in Application, Infrastructure and Engineering Services. Sogeti offers cutting-edge solutions around Testing, Business Intelligence & Analytics, Mobile, Cloud and Cyber Security. Sogeti brings together more than 23,000 professionals in 15 countries and has a strong local presence in over 100 locations in Europe, USA and India. Sogeti is a wholly-owned subsidiary of Cap Gemini S.A., listed on the Paris Stock Exchange.
Download now