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Workboat Annual Conference – International Workboat Show
The Internet of Things Comes to the Workboat Industry
P. Jaime Tetrault
Director, Product Support & Asset Intelligence
The global market is changing…
…are you ready?
UBER World’s largest taxi company
…owns no taxis Airbnb
Huge accommodation provider
…owns no real state
Skype, WeChat & Whatsapp
Mega communication companies
…own no telecom infrastructure Alibaba
Retailer more valuable than Walmart
…has no inventory
LendingClub & SocietyOne
Fastest growing lenders
…have no actual money NETFLIX
World’s largest movie house
…owns no cinemas
1. Overview of Caterpillar Marine & Asset Intelligence
2. What is the Internet of Things or Industrial Internet of Things?
3. What does this mean for the Workboat industry?
4. What challenges need to be overcome and how do I get started?
What I am going to talk about today…
Graphic source: www.KPCB.com
Marine Asset
Intelligence
5. Conclusions & Questions
Introduction to Caterpillar Marine
How you might traditionally think of Caterpillar…
…where we are today and moving in the future
Uptime Total Operating Cost
What is the Industrial Internet of Things (IIoT)?
What does it mean for me?
Machines & Sensors
Expert Advisors Intelligent analytics
EQUIPMENT
MANAGEMENT
• Avoid failures
• Reduce cost of
maintenance
PRODUCTIVITY
• Reduce downtime
• Increase productivity
• Increase fuel efficiency
SAFETY
• Reduce unsafe
operations &
conditions
SUSTAINABILITY
• Ensure environ-
mental compliance
Potential value in Workboat Industry
Twitter:
11 Accounts created,
5,700 tweets
YouTube:
2 video hrs. uploaded
2,314 video hrs. watched
Facebook:
52,196 likes
2,314 video hrs. watched
54,976 posts
6 GB of data
LinkedIn:
182
User searches
Pinterest:
238 pins
In the first second we spent on this slide… approximately 22,574 GB of
data was transferred over the Internet.
This is not just ‘social media’
1.7B pieces of industrial equipment expected to be ‘connected’ by 2020
23.6B sensors were shipped in 2014 (up from 4.2B in 2012)
What is Big Data?
Data generated every second…
Source: Peter Fisk, Genius Works, Gartner, World Economic Forum
What is the impact of this?
2020
40ZB 2015
7ZB
2010
1ZB
Total cumulative data ever created 1 zettabyte = 1 trillion gigabytes
How do we avoid being overwhelmed?
Is there value in this?
What does this mean for the Workboat Industry?
Source: Peter Fisk, Genius Works
Capitalizing on the age of IIoT
• New departments with senior leaders • Goal of building an ecosystem of internal and external technology
solutions
Organizational changes
Traditional marine companies expanding through tech acquisition; examples include: • Caterpillar acquisition of ESRG to form MAI, PEPR in Oil & Gas • Wartsila acquisition of L3-Marine/SAM • ClassNK acquisition of NAPA and Helm • Many making investments in telematics, analytics, applications
Acquisitions / Investments
Partnerships Automation, equipment OEMs, class, shipyards, universities, software companies working together, examples include: • Caterpillar partnerships with University of Illinois, GTUIT, Modustri • Hyundai Heavy Shipbuilding partnership with Accenture • Lloyd’s Register partnership with University of Southampton
Focus on using technology to create value from growing data…
0 0.25 0.5 0.75 1
Total
Reduce unsafe operations
Avoid unsafe equipment condition
Reduce compliance/admin labor cost
Reduce risk of environmental fines
Reduce fuel burn at idle
Optimize vessel speed
Optimize vessel plant configuration
Reduce hull & prop fouling
Optimize equipment tuning
Improve maint. & dry-dock planning
Reduce crew costs/skills/risk
Reduce human error maint failures
Extend maintenance intervals
Minimize failure repair costs
Reduce downtime due to failures
Improve vessel productivity
Millions
What value can all this bring to the Workboat industry?
Value creation levers Illustrative OSV potential value Per vessel
SAFETY
EQUIPMENT
MANAGEMENT
SUSTAINABILITY
PRODUCTIVITY
Indicates range of potential value
Caterpillar estimates ~$6B in annual
value creation in the Workboat industry through application of IIoT
• Fewer failures • Less downtime • Lower maintenance costs • Better fuel efficiency • Risk mitigation for compliance & safety
Examples of how the IIoT is being applied by
Caterpillar Marine Asset Intelligence in the Workboat industry
Inland Tug: Predict and prevent engine failure
OSV: Identify fuel injector problem to avoid failure & save fuel
Harbor tug: Optimize operations & tune engine optimally
EQUIPMENT
MANAGEMENT PRODUCTIVITY SAFETY SUSTAINABILITY
Analytics for Equipment Management: How it works
Inputs:
• Electronic Data • Repair History • Fluid Analysis • Site Conditions • Inspections
Equipment
Conditions
Compared
to a
Standard
Equipment
Conditions
Compared
to Similar
Equipment
Equipment
Conditions
Compared
to Itself
Solutions & Analytics for Entire Vessel
• Controllable Pitch Propellers
• Torque meters
• Steering systems
• Main propulsion diesel engines
• Ship’s service diesel generators
• Emergency generators
• Gas turbine main engines
• Gas turbine generators
• Auxiliary gas turbines
• Gas turbine starting systems
Compressors
• High pressure
• Medium pressure
• Low pressure
• De-ballast
compressors
• Air conditioning
• Refrigeration
• Reverse osmosis
• Steam evaporators
• Reduction
gears
• Transmissions
Other auxiliaries
• Waste heat boilers
• Chill water pumps
• Cathodic protection
• Fuel & lube oil
systems
• Purifiers
• Service & transfer
pumps
• Ballast management
systems
• Oily water
separators
• Sewage / gray-water
systems
• Ballast water
treatment systems
• Waterjets
• Fin stabilizers
• Thrusters
Fuel flow
meters
• GPS / Navigation systems
• Control systems
• Environmental factors
• Feed & booster pumps
• Seawater service & fire pumps
• Deck equipment
Tanks levels
• Fuel oil
• Lube oil
• Cargo
• Ballast
Additional data inputs
• Fluid Analysis / SOS
• Visual (manual) inspections
• Additional / aftermarket sensors
(bearing, oil condition, vibration, etc)
• Hull resistance, cleaning,
technologies
• Specialized
equipment
Case Study – Vessel Monitoring and Analytics
• Large inland river tug
and barge operator
• Trying to improve
maintenance, fuel
efficiency, and
operations using data
analytics
Case Study – Avoiding Equipment Failure
Customer
Objectives
• Provide customer with comprehensive solution
– Equipment: Caterpillar and Non Caterpillar
– Vessel: Fuel performance and operations
Impact
• Identified ways to improve decision making
– Reduced fuel consumption
– Avoided failures and associated downtime
– Reduced operational costs
– Real transparency for senior management
Use Case Impact Applicability
Failing fuel pump and
dirty fuel filters
Avoid failure, downtime, additional repair
costs
Engine overspeed Identify potential heavy wear conditions,
reduce
Engine droop Identify high engine stress events (i.e.,
running over log in river)
Alarm monitoring Ensure onboard alarms receive attention
High exhaust temps Focus troubleshooting on specific equipment
in specific situations
Engine performance
vs. baseline
Focus troubleshooting, improve fuel
efficiency
High stress ops (high
power/rate of turn)
Identify potential heavy wear conditions,
reduce
Daily fuel
consumption
Monitor and benchmark fuel consumption to
help reduce
Long idle periods Monitor fuel consumption and high wear
operations
Duty cycle analysis Monitor fuel consumption and high wear
operations, better plan operational calendar
Maintenance
Fuel &
Productivity
One of many “Use Cases” identified for this vessel...
Case study - Avoiding Fuel Pump Failure
Week 1 Week 2 Week 3
Fuel pump
failure & repair
2σ
Baseline
Low Fuel Pressure (2σ from ‘like-new’)
Like
New
7 days
before
failure
4 days
before
failure
2 days before
failure
Potential Impact: $20k/day rev loss + $15k add’l for offsite repair
(vs. preventative) = $35,000 per failure
Fault New -7 days -4 days -2 days
Exhaust
Fuel Cooling Oil Turbo Aux
Case study - Reducing idle time
• Extended periods (8+ hours) at idle while stationary alongside pier
• Multiple occurrences per week
Impact
Issue
• Configured Asset Intelligence analytics to automatically identify periods
greater than 3 hours
• Reducing just one of the extended idle periods per week saved $15,000
per vessel in fuel – over $2M when extrapolated across entire fleet
• Additional benefit of reducing engine hours, etc
Case Study – Vessel Monitoring and Analytics
Customer
Objectives
• Trying to improve maintenance, uptime, and reliability
• Customer asking for increased focus on fuel efficiency
OSV: ~3500 DWT, CAT 3516 engines
Impact
• Identified ways to improve decision making
– Identified fuel injector problem prior to equipment
failure and increased fuel efficiency
Use Case Impact Applicability
Equipment failure Avoid failure, downtime, additional repair
costs
Engine overspeed Identify potential heavy wear conditions,
reduce
Over-cooling Improve engine performance, health and
remaining life
Faulty fuel injectors Avoid failure & associated downtime/repair,
improve fuel efficiency
High exhaust temps Focus troubleshooting on specific equipment
in specific situations
Engine performance
vs. baseline
Focus troubleshooting, improve fuel
efficiency
Daily fuel
consumption
Monitor and benchmark fuel consumption to
help reduce
Long idle periods Monitor fuel consumption and high wear
operations
Duty cycle analysis Monitor fuel consumption and high wear
operations, better plan operational calendar
Maintenance
Fuel &
Productivity
Range of Application – Specific Value Propositions
Caterpillar Case Study – Faulty Fuel Injector
• Automated analytics
identified fuel injector
issue
• High right exhaust
bank temperatures
• Erratic low speed
RPM
• Higher fuel
consumption
compared to other
engine
Impact
Issue
• Replaced faulty fuel injectors:
• Avoided potential catastrophic failure
• Improved fuel efficiency, resulting in $175/day in fuel savings
(>$50,000 per year) - fuel savings based on observed operational
duty cycle
Case Study – Vessel Monitoring and Analytics
Customer
Objectives
• Trying to improve maintenance, fuel efficiency, and
operations using data analytics
• New vessel – Cat® C175 engines and C9 generators
Impact
• Identified ways to improve decision making
– Optimized vessel speed and operations to reduce
fuel consumption
– Tune equipment to increase performance &
reliability
– Reduce risk of failure by identifying and resolving
issues early
Large harbor tug operator
Use Case Impact Applicability
Identifying potential
problems before
failure
Avoid failure, downtime, additional repair
costs
Engine overspeed Identify potential heavy wear conditions,
reduce
Engine droop Identify high engine stress events (i.e.,
running over log in river)
Alarm monitoring Ensure onboard alarms receive attention
Identifying faulty
sensors prior to failure
Focus troubleshooting on specific equipment
in specific situations
Engine performance
vs. baseline
Focus troubleshooting, improve fuel
efficiency
High stress ops (high
power/rate of turn)
Identify potential heavy wear conditions,
reduce
Daily fuel
consumption
Monitor and benchmark fuel consumption to
help reduce
Long idle periods Monitor fuel consumption and high wear
operations
Optimizing transit
speed
Decrease fuel consumption with optimal
transit speed
Maintenance
Fuel &
Productivity
Range of Application – Specific Use Cases
• Port engine fuel pressure is 3 PSIG lower than starboard
• Similar operating situation & conditions
Port Engine
rpm vs. Fuel Pressure
Starboard Engine
rpm vs. Fuel Pressure
Impact
Issue
Tug Case Study: Detailed Engine Optimization
• Identify potential filter or fuel pump issues earlier, before failure
• Fine tune for optimal performance and increased fuel efficiency
0
5
10
15
20
25
Gal
lon
s P
er
Mile
Power or RPM
Transit Speed Before RPM: 1250
~10 Gallons Per Mile
Optimal Transit Speed RPM: 600-800
~3 Gallons Per Mile
Power & RPM both analyzed vs. fuel economy with same outcome
Tug Case Study: Optimize transit speed
• Transit to operations at
1250 RPM, because it
sounds good
Impact
Issue
• Identified optimal transit
speed for situations that
are not time sensitive
• Created visibility for
onboard crew and
shore management
• $110,000 reduced fuel
by transiting at optimal
speed based on
operational profile
Technology
People Process
VALUE
• Varied equipment • Multiple OEMs • Varied sensors • Disparate data sources
& formats • Overwhelming volume
of data • Data transmission
• Different skill sets
• Lack of capacity
• Training • Limited
onboard capabilities
• Existing systems & processes
• Change management
This is not just about technology…
• Varied equipment • Multiple OEMs • Varied sensors • Disparate data sources
& formats • Overwhelming volume
of data • Data transmission
• Different skill sets
• Lack of capacity
• Training
• Existing systems & processes
• Change management
Data collection for wide variety of equipment & data sources/formats
Automated analytics for different OEMs and types of equipment
Onboard analytics to only send valuable data Caterpillar
experts & Fleet Advisors
Expertise across range of equipment
Enable both onboard & shore teams
Local Dealer support
Flexibility to integrate with existing systems (CMMS)
Test Drive to build your business case, engage stakeholders, and develop process
This is not just about technology… How Caterpillar Marine Asset Intelligence
addresses these challenges
Technology
People Process
VALUE
Awareness
Understanding
Trial Use
Adoption Internalization
Time
Most marine operators have yet to adopt technology-based
solutions into their business processes.
2015 ?
2014
Where are you on the adoption curve for the IIoT
or technology enabled solutions?
What is needed to get started?
Get right people
involved
Define your
objectives
Select right
partners
Start (defined
scope, then grow)
…Caterpillar has defined
a ‘Test Drive’ process to help get started
Caterpillar Marine Asset Intelligence Test Drive
helps customers get started and be successful
1 Kickoff &
Alignment
2 Use Cases &
Configuration
4 Validate
value & plan
roll-out
3 Onboarding
• Bring together all relevant stakeholders, including senior management & Champion
• Align on scope, objectives, resources, evaluation criteria and schedule
• Deliverable: Test Drive focus areas and future expansion options
• Define how equipment & vessel is
operated & maintained
• Identify pain points
• Include Maintenance & Operations leaders
• Deliverable: Clear input to assure proper
configuration
• Ship Survey
• Develop install plan
• Technical discussion with
customer IT team
• Configuration
• Deliverable: Installation
• Workshop to review Test Drive
output & validate value proposition
• All relevant stakeholders
• Identify lessons learned for
customer specific situation
• Deliverable: Clear business case
Conclusions:
• Early Adopters: “We’ve tried this and are struggling” – Advanced
Analytics may well be the solution to solving your ongoing challenges.
• New to Technology Enabled Solutions: “This sounds interesting” – Before
you try this on your own, speak to a supplier with experienced domain
expertise and analytics background
EQUIPMENT
MANAGEMENT PRODUCTIVITY
SAFETY SUSTAINABILITY
Asset Intelligence brings IIoT to Workboat Industry
CAT, CATERPILLAR, BUILT FOR IT, their respective logos, “Caterpillar Yellow” and the “Power Edge” trade dress, as well
as corporate and product identity used herein, are trademarks of Caterpillar and may not be used without permission.
©2015 Caterpillar
All rights reserved.
THANK YOU FOR YOUR ATTENTION
& PLEASE VISIT US AT THE
CATERPILLAR EXHIBITION BOOTH!
BACKUP
If you are using Technology Enabled Solutions, how far along
has your initiative progressed?
Regression
Corrective
Maintenance
Planned
Maintenance
Condition
Based
Maintenance
& Operations
Value Added Complexity
Don’t fix it,
delay the fix
Fix it after it
breaks
Fix it before it breaks
Don’t just fix it,
improve & optimize it
Reactive
Urgency
Overtime
Predict
Plan
Schedule
Cost Focus
Eliminate Defects
Shared Vision
System Performance
Value Focus
Rewards
Incentive
Behavior
Run Until Failure
Short Term Savings Overtime Heroes
No Surprises
Competitive
Best in Class
Competitive Advantage
Meet short term
budget Breakdowns Avoid Failures Business Growth
Survival Reactive Organized Optimization
Most companies fall within this range
…creating significant value for
the customer Cat Marine Asset Intelligence
Advanced, automated analytics Based on 30M
hours of machine monitoring, analytics help identify
issues before they become a problem
Expert advisory services Experienced operators,
maintenance and repair technicians and data
analysts provide actionable advisories
Flexible functionality Analytics and advisory
services cover equipment condition, fuel
performance, operations and safety
Broad applicability Can monitor & analyze wide
variety of equipment, both CAT and non-CAT, diesel
engines and auxiliaries
EQUIPMENT
MANAGEMENT
• Avoid failures
• Reduce cost of
maintenance
PRODUCTIVITY
• Reduce downtime
• Increase productivity
SAFETY
• Reduce unsafe
operations &
conditions
SUSTAINABILITY
• Reduce fuel costs
• Ensure environ-
mental compliance
What’s the difference between Remote Monitoring and Asset
Intelligence with Technology Enabled Solutions?
Real Operational Transparency for Management
Recent operations including
position, course, speed, rpm,
power, fuel burn, etc.
Duty cycle analysis shows long periods
at idle, with short period of time at high
power; enables comparison across the
fleet as well as trend throughout time
Fuel and
productivity
analysis
enables
comparison
of boats
and
trending
over time
Sensor issue Potential impact if not resolved
Port engine coolant sensor spikes • Mask of pending failures
• Prevented control system logics from
protecting engine
Sustained high pressure differential for
#2 air filter
• Masked reduced air flow
• Decreased fuel efficiency
• Engine stall
• Crew bypass with unfiltered air
Cylinder exhaust temperature spikes of
over 400 degrees per second caused
by failed thermocouple
• No true monitoring of cylinder
• Unforeseen & unprotected failure
• None of these issues would have been readily apparent to onboard crew
• Likely first indication would be actual equipment issue or failure
• Resolving could help avoid catastrophic failure during operations
Tug Case Study: Resolving Undetected Sensor Issues
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