BCT & PTC together explain how live monitoring of key assets using analytics helps to understand utilization, asset behavior and performance history and prevent breakdowns and dramatically improve operational performance. Delivering these solutions takes a combination of smart technologies and operational know how, specific to the industry and assets. The BCT-PTC partnership offers just that. We also showcase real world examples of how applying analytics has helped organizations – both the industry & OEMs’ asset related challenges.

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IoT & Asset Analytics – Where do you start?
BCT – PTC Webinar

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Agenda
• About BCT & PTC
• BCT’s IIoT Ecosystem
• Asset data types and Analysis methods
• Equipment data for predictive maintenance
• Analytics Value creation
• Success Stories
• Discussions

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• Connect, federate, aggregate, and contextualize
• Provide useful, timely, shareable information
• Information from many disparate systems
• SOA eliminating duplicated systems, functionality
• Open integration with legacy and new
technologies
• Work process centric user interfaces
• Role-based decision making, collaboration
• Business process authoring and enforcement
PTC and the Digital Thread
LNS Research 2014

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Market trends - top IIoT use cases in the factory
PTC FY16 customers (Corp. Strategy interviews)
LNS Research (2016)McKinsey Global Institute (2015)
Bain IIoT report (2016)

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• Digitization of processes
• Connected assets and sensors
• Interoperability
• Cloud, mobile, augmented reality
• Big data
technology is transforming manufacturing And Operations

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Smart Manufacturing Industrie 4.0
a wave of transformation is coming to manufacturing
Made in China 2025
33% (majority) of IoT economic value will come
from the “Factories” setting
McKinsey Global Institute

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CONVENTIONAL Manufacturing IT landscape – ISA S95 MODEL
LNS Research 2015

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The manufacturing opportunity – With IoT
Source: LNS Research, 2015
Suppliers EnvironmentalLogistics
“Rip and replace” gives way to
“wrap and extend”
Role-based IoT applications

9. 9
• Many data sources, formats, types
• Manufacturing process diversity
• Lack of system interoperability, flexibility, visibility
• Changing business, products, processes
• Demands on IT resources
• Deployment disruptions, risk, and cost
TYPICAL CHALLENGES
ERP
ERP MES SCADA FleetVendorWeb
Systems Assets People
Line RobotTank Plant Office HQ

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• Open and extensible platform
• Connecting systems, people, assets
• Rapid application development
• Easily create native mobile apps
• Predictive and prescriptive analytics
• Deploy: hosted, cloud, onsite, hybrid
Next generation orchestration

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Desktop/Laptop
TODAY
Mobile
AR/Wearables
TOMORROW
VR/Wearables
Context Driven Physical/Digital orchestration
Desktop/Laptop
TODAY
Mobile
Analyze
Business/IT
Systems
CAD & PLM
AEC & BIM
Digital Context
AWS IOT
Azure IOT
Predix
Edge/OT
Environments
Controllers Sensors
Historians
Model
Digital Map
Digitize via scan, photo, or video
Simulate
AR/Wearables
TOMORROW
VR/Wearables
AWS IOT
Azure IOT
Predix
Edge/OT
Environments
Controllers Sensors
Historians
CAD & PLM
AEC & BIM
Digital Context
Business/IT
Systems
Analyze
Simulate
Model
Digital Map
Digitize via scan, photo, or video
Computer
Vision
Computer
Vision
CONTEXTUALIZE
(Map Data
to Context)
SYNTHESIZE ORCHESTRATE
ENGAGE
(Multi-Channel,
In Context
Role Based)
SOURCE
(Data &
Context)

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We transform or enable
transformation of businesses
through innovative products and
services
Bahwan CyberTek Group
Digital
Mobility Analytics Cloud
Connected Vehicle
Predictive Analytics
Digital Marketing
Risk Analytics
Outcome-based business models
IP-led Products
Solution Accelerators
2800+
Associates
1000+
Customers
$ 242 M+
Revenue
20 countries
4 continents
Bahwan CyberTek included in the Gartner Report
on ‘Choosing the Right Vendor for Payment
Modernization Initiatives
Oil Telecom Power Government Banking SCM / Logistics
Vertical
Focus
Predictive Analytics SJM & Connected VehiclesSocial & MobilityBCT’s Digital IP
suite
IOT Community

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BCT – Reliable Expert for your IoT Ecosystem
Sensors Connectivity People Processes
Business
Value
Integration || Dashboards || Contextualize || Analytics || Applications || Workflows
Cloud to on-Premise
Integration
Devices & Plant Control
Systems Integration
SOA / FMW Application
Integration
Enterprise Apps /
Portals
BI and AnalyticsM2M

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Asset Data types and Analysis Methods
PLC, SCADA ,
Historian
Process Data –
Flow, Pressure, Temp, Level
Vibration Solutions
Vibration data with Outliers,
Alarms and Conditions
Pattern Analysis
Outlier/Anomaly
Relationships
Contextualization
Root Cause
FindingsEAM/CMMS
Asset Data – OEM, Model,
Specs, Maintenance History,
Fault codes, Spares
Equipment Data –
Current, Voltage, Ramp time
VFD, Controller

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Equipment Data for Predictive Maintenance
Calendar
Calendar Time / Day / Month
Equipment Conditions
Parameters of the equipment
Process Conditions
Process Parameters related to
Equipment
Equipment Maintenance
PMEffectiveness
Manual Entry
Manual Entry
Auto Trigger in
CMMS/EAM
Existing Scenarios
Condition Monitoring
/Meters Preventive Maintenance Approval
Asset Management Process Flow --------------------------------------------------------------------
Auto Trigger in
CMMS/EAM
Efficient Scenarios
PLC , SCADA , Historian
Integration
Integration and
Computation Engine
Performance Efficiency /
Predictive Analysis /
Root Cause Analysis
Work order
Results
Run Hours
Running Hours of the equipment
Interfaces
PLC
SCADA
HISTORIAN
MES
• Reduces Unplanned Downtime
• Avoids Deterioration of Equipment

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Predictive Solutions - Failure / Problem Predictions
0
1
2
3
4
5
0 5 10 15 20 25 30
Intelligent Alarm Capture
Current Alarm Limit
Benefits
• Capture abnormal Behavior's
• Operations info for decision making
• Well informed Equipment Information
• Avoid failures
• Better prepared
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Applicable Scenarios
• Process Improvements
• Equipment Efficiency
• Accurate Loss calculations
Deviation Analysis

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• Run Hours
• Counts – On/Off
• Efficiency Calculations
• Performance Indicators
• Energy Calculations
• 80-20 / Top 5 reasons
• Parameter
• Patterns / Clustering
• Contextualization
• Condition Logics
• Failure intervals
• Root Cause Analysis
Analytics
Report
What happened?
Analyze
Why did it happen?
Monitor
What's happening now?
Predict
What might happen?
Prescribe
What should happen?
Meters
PLC, SCADA ,
Historian
Enterprise Systems
– EAM / ERP
Vibration &
Thermal Solutions
Data Sources
A
n
a
l
y
t
i
c
s
Categories Analytics Examples
• Asset Utilization
• Operational Cost
• Worker Productivity
• Worker Safety
• Sustainability
• Customer Experience
• New outcome model
Value

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17 to 13
Value Proposition
2% Less
30,000
Hours
0.5 to
1 %
1 - 1.5
Years
Less No. of Maintenance Visits
(PM task Consolidation, Custom PM Plans)
Less Downtime
(Increased Availability & Revenue)
Less Maintenance Labor Hours
(Utilize it for Detailed, Quality Inspection)
Less Spare Holding Cost
(Better Spare Management)
Higher Economic Life
(Better Spare Ratio)
Unified PM plan
Customized
Maintenance
Fault Prediction

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Power Generation,
T & D
•Operations efficiency &
Heat Rate Degradation
Advisor
•Asset Analytics
•T&D Distribution Analytics
•Renewables: TOMS &
SOVA
15%
Reduction in
load Planning
time
5%
Improvement in
Equipment
Availability
1%
Increase in
production
20%
Reduction in
field visits
Oil & Gas
•E&P Monitoring
•Predictive
Maintenance and
WO automation
7% -
10%
Reduction of
non
productive
time
Verticals
What we
did for
them
VALUE
Analytics – Value creation
Minerals, Metals
& Resources
•Plant performance
improvement
•Quality Mgmt.
•Enterprise Integration
3%
Improvement
in Productivity
4%
Reduction in
Energy
Consumption
50%
Improvement
in Quality
Adherence
Discrete
Manufacturing
•Operations
Management
Platform
•Predictive
Maintenance and
WO automation
5%
Improvement
in Equipment
Availability
3%
Operations
Efficiency
Building
Energy Mgmt.
•Analytics Platform
•Predictive
Maintenance
•Energy Management
15%
Reduction in
Energy use
$$$
Millions
saved in Law
Suits

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Top 5 Learnings on Asset Analytics
Outcome Definition
Data sufficiency
Integration
Scenario Definition
How to Deliver?

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BCT’s “Real Time Asset Optimization Model”
– using Predictive Analytics
Asset
Optimization
Model
Condition
Monitoring
Performance
Indicators
Root Cause
Analysis
Cost of
Operation
Active
Truth Table
Optimization - to minimize the whole-life cost in Operation,
Maintenance and Replacement or disposal
Condition Monitoring  To CMMS /EAM
- Normal Operations
- Needs Maintenance during next opportunity
- Needs immediate Maintenance/Overhaul
Performance & Sustainability Indicators / Intelligence
Level 1 - 100% to 80%
Level 2 - 50% to 79%
Level 3 - < 50%
Of Manufacturer
Recommendations (or)
Plant Best Practices
Real Time Cost of Operation
- Normal Cost
- Higher than normal by 25%
- Higher than normal by > 25%
Truth Table Type of Failure Reasons Consequences Corrective Actions
Equipment 1
Equipment 2
Root Cause Analysis
• Immediate access to problem source
• In Real Time
• Forward Chaining