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System Integration in an IOT world
Jayraj Nair, Head – IOT Practice and AVP – Engineering Services, Infosys
Content
2
• Infosys at a glance
• Smart, connected products and operations
• Industry 4.0 and survey results
• Capability levels – monitoring, control, optimization
• Rethinking predictive analytics – IIP
• Ecosystem partnership – IIC
Infosys at a glance
3
Infosys Intellect ValuesPeople Clients
Founded in Pune,
India in 1981
$8.7 billion revenues
950 clients
50+ countries
$40.3 billion market
capitalization
176,000+ staff
98 nationalities
97 percent of staff are
university educated
22 percent hold masters
degrees or doctorates
94 percent are
consultants and
engineers
World’s largest corporate
university
2 percent of revenues
invested in R&D
More than 300
researchers
Investing $500 million in
Innovation Fund
505 patents pending and
204 granted
Transparency,
ethics, and respect
98.3 percent of projects
delivered on time
96.6 percent business
is repeat business
2 percent of profits go to
the Infosys Foundation
Topped Asiamoney’s
Corporate Governance
Poll in the Domestic
Country category
4 out of top 5
US banks
6 out of top 10 global
CPG
8 out of top 10
global pharma
4 out of top 5
global aerospace
and defence
6 out of top 10
global telcos
Infosys Engineering Services
4
250+
clients
20+
years
Global
operations
8000+
engineers
Keyengineeringservices
Mechanical, structural and manufacturing engineering
Product lifecycle management
Knowledge based engineering and analytics
Electronics / embedded / electrical engineering
Value analysis and value engineering
Plant automation control services
Networking and telecom engineering
Industries
Aerospace
Discretemanufacturing
Automotive
OEM,SemiconductorandHi-tech
Telecomserviceproviders
Medicaldevicesandhealthcare
Retail,CPGandtransport
ISVandservices
Energyandutilities
Integrating smart, connected products
5
1 2 543
Hardware and
software
embedded design
of intelligent
devices,
intelligent
gateways devices,
device security,
and
multiple protocols
such as MQTT,
AMQP, STOMP
MODBUS,
PROFINET, OPC
Connectivity
solution around
Wi-Fi, ZigBee,
Bluetooth, Zwave,
3G, and 4G
moving to 5G
SIM; M2M
connectivity
management;
traffic
engineering;
network and
device operations
Management of
end devices for
state and status;
data modeling;
cloud hosting;
device software
management;
policy rules
engine;
complex event
processing;
security; and
integrity of data
Database
integration,
CRM integration
data warehouse,
workflow
management,
workforce
management,
enterprise mobility
Stream
processing,
actionable
analytics,
data visualization,
statistical
computing,
business
dashboards,
predictive and
prescriptive
analytics,
business insights,
monetization, and
continuous
improvement
Intelligentdevices
Connectivity
Devicemanagement
Enterpriseintegration
Businessanalytics
Smart, connected products and Industry 4.0
6
Operations
efficiency
Production optimization
(OEE)
Production
planning and scheduling
Productivity modelling
Statistical quality control
Inventory optimization
Maintenance
efficiency
Condition monitoring
Predictive maintenance
Maintenance
planning and scheduling
Reliability-centered
maintenance
Root cause analysis /
anomaly detection
Service efficiency
Remote management /
remote services
Field service
management
Materials management
(spare parts / inventory)
Service life cycle
management
Supply chain analytics
Information
efficiency
iDashboard
Data quality framework
Asset life cycle
information model
Machine-born data
management and
analytics
Knowledge management
Energy efficiency
and sustainability
Energy management
Resource efficiency
Asset sustainability index
Safety performance
(Alarm management,
EHS)
Regulatory / standards
compliance
Impacts value chain  Transforms asset efficiency
Industry 4.0 survey results
7
Study : FIR Institute at the University of Aachen, Germany + Infosys
Participants : 433 Industrial Manufacturing executives
Industry 4.0 survey results
8
Deploying varying levels of IoT capability
Monitoring
visibility
E.g., factory
visibility
Control
operations
E.g., Health
Safety
Optimization
E.g., Predictive
analytics
9
Reference solutions @ booth #220
10
Implemented a real-time plant visibility solution for one of the
largest food and beverage companies in the world
Solution
• Real-time capture of production data from factory floor
equipment and systems
• Mobility solution implemented for ‘on-the-go’ quality inspection
• Intelligent dashboards with real-time and historical performance
reporting
Results
• Overall line and plant effectiveness increased from 45 percent to
60 percent (which has significantly impacted plant throughput
and profitability)
• Manual paperwork reduced by 70 percent
• Enterprise data duplication reduced to 0 percent
• Reduction in frontline resource fatigue and equipment downtime
• Implemented root-cause analysis for quicker troubleshooting
• Increased speed and accuracy in decision-making
• Significant productivity improvement in quality inspection (mobile
on-the-go)
Challenge
A global FMCG company needed to modernize its factories across
multiple locations to improve operational efficiency and effectiveness
11
Developed a manufacturing intelligence system for
one of the largest manufacturers of heavyweight motorcycles
in the world
Solution
Implemented a leading-edge manufacturing integration and intelligence
system, fully integrated with ERP and shop floor systems
Results
• Real-time visibility into production rejects and start-up rejects, reduced
scraps, and improved the quality measure of production systems
significantly
• Enhanced the overall equipment effectiveness (OEE) of the plant
• Implemented preventive maintenance by tracking the order inflow into
production systems and proactively resolving them
• Engaged in innovation co-creation, partnering in their innovation strategy
Challenge
A global automotive company needed better insight into its manufacturing
systems in order to build an intelligent manufacturing enterprise
12
Enabled a real-time information management system
for a global mining major
Solution
• Enabled integration and interoperability between
multiple manufacturing systems, historical data and
legacy systems
• Critical systems moved to newer converters – without
disruption to business continuity
• Established a more stable platform for the existing
quality system for smelter operations
Challenge
A global mining major needed real-time visibility across the
mining value chain – extraction, transportation,
beneficiation and processing
Results
• Improved day-to-day scheduling, resulting in increased
efficiency and productivity
• Improved availability of business-critical applications
• Global roll-out of new KPIs
• KPI standardization across similar operations
Deploying varying levels of IoT capability
Monitoring
visibility
E.g., Factory
visibility
Control
operations
E.g., Health safety
Optimization
E.g., Predictive
analytics
13
Reference Solutions @Booth 220Reference solutions @ booth #220
14
Implemented a biometric field engineer safety monitoring solution
for one of the largest global manufacturers of escalators and
elevators
Challenge
A global manufacturer of escalators and elevators needed real-time
visibility into the safety of their field engineers
Solution
• Implemented a biometric field engineer safety monitoring solution
• Real-time monitoring and reporting of hazardous situations for multiple individuals and teams simultaneously
• Designed for and deployed in harsh and remote environments
• Developed and deployed:
• Mobile app for field engineers
• Remote monitoring sensors
• Mobile app for facility managers
• Integrated directly with other enterprise systems and / or emergency services
Results
• Ensured faster response times in emergency environments
• Reduced the number of accidents as the vital parameters of each
field engineer is constantly monitored
15
Development of a centralized dashboard to implement continuous
and remote monitoring of field-based personnel for a leading mining
company
Challenge
A leading mining company needed to continuously
monitor their field-based personnel and miners, and
provide assistance during life-threatening conditions
Solution
• Developed a centralized dashboard to
continuously monitor field workers
• Identified the severity of the breach or
hazardousness of the situation
• Delivered immediate evacuation alerts and
tracked high-risk workers
Results
• Faster evacuations
• Faster mobilization of specialist
resources
• Reduction in the cost of health
insurance cover for miners
• Improvement in the health and safety
matrix
16
Infosys built a demonstrator to establish the relevance of Industry
4.0 in the delivery of smart services together with a global leader in
power and automation technologies and the largest technical
university in Germany
Solution
• Android-based mobile application
• Applied to a technically complex class of instruments
whose functionality is critical in the process industry
• Real-time QR code scanning to understand current
device status and maintenance needs
• Multiple workflows to manage and maintain complex
gas analyzers
• Cloud-based self-service experience
• Integrated security solution
Results
• Enhanced user experience for both the customer and the
field engineer
• Faster and best-in-class service support from OEM
• Significant reduction in mean time to repair (MTTR)
• Enhanced quality monitoring and reporting
Deploying varying levels of IoT capability
Monitoring
visibility
E.g., Factory
visibility
Control
operations
E.g., Health safety
Optimization
E.g., Predictive
analytics
17
Reference Solutions @ Booth 220
18
Enabled predictive maintenance and corrective action for a mining
major
Analyzed 300 million records in
less than 4 seconds
Reduced the cost by 1000 percent
Helped customer save on costly
downtime caused due to
equipment failure
Provided predictive analytics to
identify when equipment on field is
likely to fail or needs maintenance
in order to maximize uptime / in-
service for equipment
19
Improved service levels of ATMs for a leading ATM
manufacturer
Cleansed 4 million records within
27 seconds
Reduced cost by 18 percent, from
increasing mix to 40 percent
staged calls
Increased efficiency by 14 percent,
from 3 to 4 service calls per
technician per day
Reduced time to identify chronic
defects from weeks to hours
20
Prevented network faults using predictive analytics
for a telecom major
Analyzed 16.7 million records in 5
seconds
Impending network faults in the
next week predicted with a high
degree of accuracy to fix the
network failure points
Solution based on open-source
stack, including Apache Spark and
prebuilt Infosys components, was
delivered in just 5 days
Improved price-to-performance
ratio
Rethinking predictive analytics
21
Scope
All data – not just structured,
not just internal
Speed @ scale
Handle massive scale without
compromising speed (decision time)
Insights
Move from request-response to
self-discovery
Prebuilt
Components
from Infosys
& Partners
Open Source
Data
Scientists
Technical
Experts
Infrastructure
Management
Analysts
Functional
Experts
9
Building blocks – Infosys Information Platform
Ecosystem partnership – IIC
23
• Infosys will focus on the development of future IIC testbeds, leveraging its expertise in
predictive analytics to enable Industry 4.0 essentials of maintenance, operations, information,
service, and energy efficiency
• Solutions will leverage the recently announced Infosys Information Platform (IIP) and be
anchored on open-source and open-access ingredients for rapid innovation by the partner
community
Reach out to us IOT@Infosys.com to collaborate and co-innovate
© 2015 Infosys Limited, Bangalore, India. All Rights Reserved. Infosys believes the information in this document is accurate as of its publication date; such information is subject to change without notice. Infosys acknowledges the proprietary rights
of other companies to the trademarks, product names and such other intellectual property rights mentioned in this document. Except as expressly permitted, neither this documentation nor any part of it may be reproduced, stored in a retrieval
system, or transmitted in any form or by any means, electronic, mechanical, printing,photocopying,recording or otherwise, withoutthe prior permission of InfosysLimited and/ or any named intellectual property rights holders under this document.
Thank you

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Infosys' session on IoT World - Systems Integration in an IOT world: A practitioner’s view

  • 1. System Integration in an IOT world Jayraj Nair, Head – IOT Practice and AVP – Engineering Services, Infosys
  • 2. Content 2 • Infosys at a glance • Smart, connected products and operations • Industry 4.0 and survey results • Capability levels – monitoring, control, optimization • Rethinking predictive analytics – IIP • Ecosystem partnership – IIC
  • 3. Infosys at a glance 3 Infosys Intellect ValuesPeople Clients Founded in Pune, India in 1981 $8.7 billion revenues 950 clients 50+ countries $40.3 billion market capitalization 176,000+ staff 98 nationalities 97 percent of staff are university educated 22 percent hold masters degrees or doctorates 94 percent are consultants and engineers World’s largest corporate university 2 percent of revenues invested in R&D More than 300 researchers Investing $500 million in Innovation Fund 505 patents pending and 204 granted Transparency, ethics, and respect 98.3 percent of projects delivered on time 96.6 percent business is repeat business 2 percent of profits go to the Infosys Foundation Topped Asiamoney’s Corporate Governance Poll in the Domestic Country category 4 out of top 5 US banks 6 out of top 10 global CPG 8 out of top 10 global pharma 4 out of top 5 global aerospace and defence 6 out of top 10 global telcos
  • 4. Infosys Engineering Services 4 250+ clients 20+ years Global operations 8000+ engineers Keyengineeringservices Mechanical, structural and manufacturing engineering Product lifecycle management Knowledge based engineering and analytics Electronics / embedded / electrical engineering Value analysis and value engineering Plant automation control services Networking and telecom engineering Industries Aerospace Discretemanufacturing Automotive OEM,SemiconductorandHi-tech Telecomserviceproviders Medicaldevicesandhealthcare Retail,CPGandtransport ISVandservices Energyandutilities
  • 5. Integrating smart, connected products 5 1 2 543 Hardware and software embedded design of intelligent devices, intelligent gateways devices, device security, and multiple protocols such as MQTT, AMQP, STOMP MODBUS, PROFINET, OPC Connectivity solution around Wi-Fi, ZigBee, Bluetooth, Zwave, 3G, and 4G moving to 5G SIM; M2M connectivity management; traffic engineering; network and device operations Management of end devices for state and status; data modeling; cloud hosting; device software management; policy rules engine; complex event processing; security; and integrity of data Database integration, CRM integration data warehouse, workflow management, workforce management, enterprise mobility Stream processing, actionable analytics, data visualization, statistical computing, business dashboards, predictive and prescriptive analytics, business insights, monetization, and continuous improvement Intelligentdevices Connectivity Devicemanagement Enterpriseintegration Businessanalytics
  • 6. Smart, connected products and Industry 4.0 6 Operations efficiency Production optimization (OEE) Production planning and scheduling Productivity modelling Statistical quality control Inventory optimization Maintenance efficiency Condition monitoring Predictive maintenance Maintenance planning and scheduling Reliability-centered maintenance Root cause analysis / anomaly detection Service efficiency Remote management / remote services Field service management Materials management (spare parts / inventory) Service life cycle management Supply chain analytics Information efficiency iDashboard Data quality framework Asset life cycle information model Machine-born data management and analytics Knowledge management Energy efficiency and sustainability Energy management Resource efficiency Asset sustainability index Safety performance (Alarm management, EHS) Regulatory / standards compliance Impacts value chain  Transforms asset efficiency
  • 7. Industry 4.0 survey results 7 Study : FIR Institute at the University of Aachen, Germany + Infosys Participants : 433 Industrial Manufacturing executives
  • 9. Deploying varying levels of IoT capability Monitoring visibility E.g., factory visibility Control operations E.g., Health Safety Optimization E.g., Predictive analytics 9 Reference solutions @ booth #220
  • 10. 10 Implemented a real-time plant visibility solution for one of the largest food and beverage companies in the world Solution • Real-time capture of production data from factory floor equipment and systems • Mobility solution implemented for ‘on-the-go’ quality inspection • Intelligent dashboards with real-time and historical performance reporting Results • Overall line and plant effectiveness increased from 45 percent to 60 percent (which has significantly impacted plant throughput and profitability) • Manual paperwork reduced by 70 percent • Enterprise data duplication reduced to 0 percent • Reduction in frontline resource fatigue and equipment downtime • Implemented root-cause analysis for quicker troubleshooting • Increased speed and accuracy in decision-making • Significant productivity improvement in quality inspection (mobile on-the-go) Challenge A global FMCG company needed to modernize its factories across multiple locations to improve operational efficiency and effectiveness
  • 11. 11 Developed a manufacturing intelligence system for one of the largest manufacturers of heavyweight motorcycles in the world Solution Implemented a leading-edge manufacturing integration and intelligence system, fully integrated with ERP and shop floor systems Results • Real-time visibility into production rejects and start-up rejects, reduced scraps, and improved the quality measure of production systems significantly • Enhanced the overall equipment effectiveness (OEE) of the plant • Implemented preventive maintenance by tracking the order inflow into production systems and proactively resolving them • Engaged in innovation co-creation, partnering in their innovation strategy Challenge A global automotive company needed better insight into its manufacturing systems in order to build an intelligent manufacturing enterprise
  • 12. 12 Enabled a real-time information management system for a global mining major Solution • Enabled integration and interoperability between multiple manufacturing systems, historical data and legacy systems • Critical systems moved to newer converters – without disruption to business continuity • Established a more stable platform for the existing quality system for smelter operations Challenge A global mining major needed real-time visibility across the mining value chain – extraction, transportation, beneficiation and processing Results • Improved day-to-day scheduling, resulting in increased efficiency and productivity • Improved availability of business-critical applications • Global roll-out of new KPIs • KPI standardization across similar operations
  • 13. Deploying varying levels of IoT capability Monitoring visibility E.g., Factory visibility Control operations E.g., Health safety Optimization E.g., Predictive analytics 13 Reference Solutions @Booth 220Reference solutions @ booth #220
  • 14. 14 Implemented a biometric field engineer safety monitoring solution for one of the largest global manufacturers of escalators and elevators Challenge A global manufacturer of escalators and elevators needed real-time visibility into the safety of their field engineers Solution • Implemented a biometric field engineer safety monitoring solution • Real-time monitoring and reporting of hazardous situations for multiple individuals and teams simultaneously • Designed for and deployed in harsh and remote environments • Developed and deployed: • Mobile app for field engineers • Remote monitoring sensors • Mobile app for facility managers • Integrated directly with other enterprise systems and / or emergency services Results • Ensured faster response times in emergency environments • Reduced the number of accidents as the vital parameters of each field engineer is constantly monitored
  • 15. 15 Development of a centralized dashboard to implement continuous and remote monitoring of field-based personnel for a leading mining company Challenge A leading mining company needed to continuously monitor their field-based personnel and miners, and provide assistance during life-threatening conditions Solution • Developed a centralized dashboard to continuously monitor field workers • Identified the severity of the breach or hazardousness of the situation • Delivered immediate evacuation alerts and tracked high-risk workers Results • Faster evacuations • Faster mobilization of specialist resources • Reduction in the cost of health insurance cover for miners • Improvement in the health and safety matrix
  • 16. 16 Infosys built a demonstrator to establish the relevance of Industry 4.0 in the delivery of smart services together with a global leader in power and automation technologies and the largest technical university in Germany Solution • Android-based mobile application • Applied to a technically complex class of instruments whose functionality is critical in the process industry • Real-time QR code scanning to understand current device status and maintenance needs • Multiple workflows to manage and maintain complex gas analyzers • Cloud-based self-service experience • Integrated security solution Results • Enhanced user experience for both the customer and the field engineer • Faster and best-in-class service support from OEM • Significant reduction in mean time to repair (MTTR) • Enhanced quality monitoring and reporting
  • 17. Deploying varying levels of IoT capability Monitoring visibility E.g., Factory visibility Control operations E.g., Health safety Optimization E.g., Predictive analytics 17 Reference Solutions @ Booth 220
  • 18. 18 Enabled predictive maintenance and corrective action for a mining major Analyzed 300 million records in less than 4 seconds Reduced the cost by 1000 percent Helped customer save on costly downtime caused due to equipment failure Provided predictive analytics to identify when equipment on field is likely to fail or needs maintenance in order to maximize uptime / in- service for equipment
  • 19. 19 Improved service levels of ATMs for a leading ATM manufacturer Cleansed 4 million records within 27 seconds Reduced cost by 18 percent, from increasing mix to 40 percent staged calls Increased efficiency by 14 percent, from 3 to 4 service calls per technician per day Reduced time to identify chronic defects from weeks to hours
  • 20. 20 Prevented network faults using predictive analytics for a telecom major Analyzed 16.7 million records in 5 seconds Impending network faults in the next week predicted with a high degree of accuracy to fix the network failure points Solution based on open-source stack, including Apache Spark and prebuilt Infosys components, was delivered in just 5 days Improved price-to-performance ratio
  • 21. Rethinking predictive analytics 21 Scope All data – not just structured, not just internal Speed @ scale Handle massive scale without compromising speed (decision time) Insights Move from request-response to self-discovery
  • 22. Prebuilt Components from Infosys & Partners Open Source Data Scientists Technical Experts Infrastructure Management Analysts Functional Experts 9 Building blocks – Infosys Information Platform
  • 23. Ecosystem partnership – IIC 23 • Infosys will focus on the development of future IIC testbeds, leveraging its expertise in predictive analytics to enable Industry 4.0 essentials of maintenance, operations, information, service, and energy efficiency • Solutions will leverage the recently announced Infosys Information Platform (IIP) and be anchored on open-source and open-access ingredients for rapid innovation by the partner community Reach out to us IOT@Infosys.com to collaborate and co-innovate
  • 24. © 2015 Infosys Limited, Bangalore, India. All Rights Reserved. Infosys believes the information in this document is accurate as of its publication date; such information is subject to change without notice. Infosys acknowledges the proprietary rights of other companies to the trademarks, product names and such other intellectual property rights mentioned in this document. Except as expressly permitted, neither this documentation nor any part of it may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, printing,photocopying,recording or otherwise, withoutthe prior permission of InfosysLimited and/ or any named intellectual property rights holders under this document. Thank you

Notes de l'éditeur

  1. PLM – Product Life-cycle Management, OEM – Original Equipment Manufacturer, CPG – Consumer Packaged Goods, ISV – Independent Software Vendors
  2. Rio Tinto use case: A mining company operating a fleet of thousands of trucks wanted a predictive maintenance platform to prevent losses incurred due to breakdown of vehicles. The trucks carrying mineral ore were fitted with sensor technologies. The fleet of trucks pinged data that was of little use in the absence of a mechanism that analyzed data in real time. Infosys developed a proof of concept (PoC) using open-source tools and technologies such as Hadoop and cloud-based hardware. It enabled the company to process voluminous amount of data and glean meaningful insights. Predictive maintenance resulted in reducing vehicle downtime. It delivered significant improvements in downstream supply chain operations and profitability. The Infosys solution offered processes-related data in real time. The scalable solution can support the company’s business plan to increase the fleet of trucks by more than 300 percent with a corresponding increase in sensor data load.
  3. Diebold – A leading ATM manufacturing and service company wants to reduce its cost in maintaining ATMs also provide better customer service and SLAs Predict that an ATM is going to fail in the next week (over 80 percent confidence level) based on alert and incident data from XMS and machine data Ticketing data from 8500 ATMs / 4M records was ingested into Spark and then cleaned out (date, spaces, null fields etc.) in just 27 seconds on 10 node AWS cluster (32 CPU, 64GB RAM, 640 GB SSD storage) Enriched data to create the parameters required for analysis. Spark Logistic Regression run on top of this data with data prediction in 60 msecond Data ingested to Oracle and visualization done using Tableau
  4. BT – A global telecom company offering data services to customers using xDSL technology partnered with Infosys. Network faults in the xDSL backbone caused disruptions in data services. The company sought a model to predict the network faults proactively. Infosys developed a ‘control signature’ of healthy lines using signal processing and statistical techniques based on the Hadoop-based Infosys Information Platform. Infosys created a ‘fault signature’ from the connection properties in the days leading up to the reporting of a ‘fault’. The team built a predictive model that reported the probability of an impending fault within a week. The formula for the predictive model was applied to 16.7 million network line characteristic data records, processed within 5 seconds on a medium-sized 5 node cluster. The outcome was a subset of network faults that could be predicted with a high degree of accuracy