The document discusses smart plant supervision using Internet of Things (IoT) technology. It describes how IoT can be used to remotely monitor industrial equipment and processes using sensors, aggregate and analyze the sensor data using predictive analytics, and take actions like scheduling maintenance to prevent failures and optimize operations. Implementing such a smart plant supervision system using IoT could reduce costs through minimized downtime and waste while improving productivity, safety, and other benefits for manufacturing and other industries. The document provides examples of potential use cases and components of an IoT framework for smart plant supervision.

1. 2016
Smart Plant Supervision
IBM World of Watson October 24-27 | Mandalay Bay, Las Vegas

2. Copyright © Capgemini 2016. All Rights Reserved
Smart Plant Supervision | IBM World of Watson | October 24-27
Examples of use cases:
 Remote product upgrades
 Remote maintenance
 Data insights for
engineering
Product improvements
Examples of use cases:
 Pay per use models
 Lease + maintain vs. sell
New business models
Examples of use cases:
 Production equipment
management
 Building management
 Inventory management
 Delivery tracking
 Production of customized
products
Operational excellence
Pervasive impact of IoT in Manufacturing
2
IoT use cases

3. Copyright © Capgemini 2016. All Rights Reserved
Smart Plant Supervision | IBM World of Watson | October 24-27
Predictive Maintenance is key priority for Automotive & Manufacturing
3
Combine use cases to yield a greater ROI
Business Case Manu Auto Trans Energy
Predictive Maintenance    
Improve Customer Satisfaction    
Improve Efficiency    
Enable Predictive Ordering/Selling    
Optimize Resources    
Enhance Safety    
Lower Environmental Impact    
Steer Product Development   
Enable New Revenue Models    

4. Copyright © Capgemini 2016. All Rights Reserved
Smart Plant Supervision | IBM World of Watson | October 24-27
Smart Plant Supervision
5
Issues
 Today, manufacturers have access to large amounts of
data. For them, one of the challenges is in storing,
processing and developing insights from the data
 They also face challenges in gaining real-time awareness
of the health of assets (machines), performing proactive
maintenance to reduce downtime, ensuring schedule
adherence, and reducing waste and delivery delays
 Breaking silos to foster collaboration and preventing
malevolent takeover (security breach) of machines are
additional challenges
Solution
 IoT framework based on following approach:
• Acquisition: Using sensors, data is extracted from a
machine and transmitted to a secure database
• Aggregation: Data from multiple sources is
consolidated
• Analysis: The data is interpreted using analytic
software
• Assignment: Based on data interpretation, an
appropriate case is automatically created and
assigned appropriately. The assigned representative
receives an alert prompting action
• Action: The representative can access case data
using cloud-based mobile platforms
Benefits
 Higher productivity:
• Reduced machine downtime
• Adherence to schedule
• Focus on core business and innovation vs. crisis
management
 Reduced costs:
• Reduced maintenance costs (spare parts,
resources, time)
• Reduced waste
• Reduced need for resources around back order
management
MACHINE CONDITION MONITORING MACHINE FAILURE PREDICTION & PREVENTION BUILD SELF-CORRECTING MACHINES

5. Copyright © Capgemini 2016. All Rights Reserved
Smart Plant Supervision | IBM World of Watson | October 24-27
Details
Smart Plant Supervision – Solution
6
Note – A1-A5 refers to our Group Approach for IoT
Enterprise Applications
PMQ
IOT Foundation
Real-time monitoring & Predictive Analytics  Business Logic
 Predictive Analytics
 Database
 Interfaces
 Notification Service
Devices Factory
Service & Spare
Parts Requests
Notifications
Email/Text
Aggregated
Machine Data
Machine
Instructions
Machine
Parameters
A4
A3
A2
A1
A5
Sensor Data Aggregation
Scenarios
Machine Condition
Monitoring
Predict and Prevent
Failures
Predict Spare Parts Needs
Self Correcting Machines

6. Copyright © Capgemini 2016. All Rights Reserved
Smart Plant Supervision | IBM World of Watson | October 24-27
 Tool Planning
 Tool Logistics Management
 Mobile Worker Management
 EHS and GRC
 Smart Bins and Racks
 Workforce Safety
 Smart Facilities
 JIT Call Management
 Enhanced Supply Chain Monitoring
 Lean Manufacturing
Smart Plant Supervision Extensions
7
Track and Trace Connected Warehouses Connected Supply Chain

8. About Capgemini
With more than 180,000 people in over 40 countries, Capgemini is
one of the world's foremost providers of 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. www.capgemini.com
The information contained in this presentation is proprietary. © 2016 Capgemini. All rights reserved. Rightshore® is a trademark belonging to Capgemini.
For more details contact:
Mangirish Herwadkar - Senior Manager - CHROME CoE
mangirish.herwadkar@capgemini.com