digitalization and artificial intelligence in shipping.pptx

DIGITALISATION IN
SHIPPING AND
LOGISTICS

INTRODUCTION
The International Maritime Organization (IMO)
supports the implementation of automated
electronic data exchange from ship to ship and
ship to shore to increase efficiency, safety and
security of maritime navigation and
communications.

Digital technologies continue to
transform industrial processes all over
the world.
 Shipping and logistics are no
exception

GPS navigation, real-time weather data
feeds as well as smart containers are just
some of the technologies redefining the
movement of goods.
In future, ships will inform ports of what
goods are in which containers on board
long before docking
 Allowing better planning and faster
unloading

Containers equipped with sensors and radio- frequency
identification (RFID) transponders will be registered and tracked for
optimized transport and distribution.
Perishable goods, for example, will be monitored and delivered
before spoilage.
T
elematics systems and databases in freight trucks will help reduce
waiting times and bottlenecks in ports , by keeping drivers informed
of precisely when and where containers will be unloaded.

The benefits in energy savings

MODERN SHIP
AUTOMATION AND
CONTROL SYSTEM

Onboard and shore-based application services that use data
from navigation, machinery, and other onboard equipment,
including the ones listed below, are increasingly common.
Weather routing
Optimum trim
Performance monitoring
Engine monitoring
Condition monitoring
Power plant energy management
Remote maintenance

Automation and control system is a
fully integrated systems covering
many aspects of the ship operation
that includes the propulsion plant
operation, power management
operation on the auxiliary engines,
auxiliary machinery operation, cargo
on-and-off-loading operation,
navigation and administration of
maintenance and purchasing of
spares

digitalization and artificial intelligence in shipping.pptx

PLC ship system
Washington State Ferry control
cabinet. This vessel uses an
engine order telegraph and
electric propulsion – a mix of old
and new.

Our objectives today
• Existing commercial ship automation
• Where did shipboard automation come from?
• How fast is it changing?
• What limits its growth?
• How automatic are ships today?
• Remote and autonomous commercial ships
• Are they possible technically? Are they possible socially?
• Is ROV/AUV technology scalable?
• Are present rules sufficient for the ship of the future?

Some points to look for
• What kind of commercial ships are likely to automate further?
• Is the autonomous ship really unmanned?
• How limiting is the lack of technology transfer between the
ROV/AUV community and surface craft designers?
• What if the first automated vessels in the US are built to
American Boat and Yacht Council (ABYC) standards?

Existing Automation
• Engine room automation
• Power management and automated systems such as ballast water,
control air, anti-heeling, fuel purification, bilge treatment, etc.
• ACC and ACCU from ABS; similar notations from other class societies
• Bridge electronics
• Integrated bridge systems prove the whole greater than the sum of its
parts. ECDIS and ARPA; solid-state gyro-compasses with
accelerometers.
• Auto-pilot systems with memory, like a pilot’s
• Safety systems
• Fire systems with graphic interfaces and automated responses
• Intrusion and perimeter control; auto-ballasting systems; CCTV

Existing Automation
• Propulsion systems
• Twin-screw synchronization systems - old school
• Hybrid propulsion
• Batteries and “power take-off/power take-in” systems (PTO/PTI)
• Slow speed marine engine dynamic optimization is now available from
large engine manufacturers to optimize for fuel cost or for schedule.
• Water and cargo systems
• Auto-ballasting; anti-heel systems; automated tank-washing;
automated loading and discharge systems; auto-loading bulkers

A matter of degree
Ships already have centralized
lineups of switchgear actuated
remotely.
Each of these motor controllers
has a “Hand/Off/Auto” or
“Hand/Off/Remote” switch.
It is only a question of how
remote or how automatic.

Automation possibilities - Remote
• Complete remote operation is possible
• Transas and Kongsberg training simulators resolved many issues
• ROV/AUV developments are largely scalable to commercial vessels
• Department of Defense drone deployments are more challenging than
operating a ship at 12 knots.
• Refining oil or building a car on an assembly line are each more complicated
than operating a ship at sea.
• Remote operation is limited by telecommunications reliability and
bandwidth. In short – weather
.

Old school
STD and VME Busses allowed
plug-in modules, unlike this
more typical shipboard
installation. This board would
take longer to repair and have
a greater chance of repair
error than plug in board.

Automation possibilities – Autonomous
• Completely autonomous operation is possible
• Early programmable logic controllers (PLCs) did what relay-logic and bread-
board op-amp controls could not do. They were special because they were
modular and reprogrammable; expandable and scalable. PLCs automated
discrete activities well and automated processes less-well.
• Process control took PLC batch control to real-time. Continuous process
control streamlined commodity production but in so doing made control of all
real-time processes possible. Still expandable and scalable, the software
possibilities expanded beyond Relay Ladder Logic (RLL) with ASCII subroutines
to C++ and more advanced languages capable of better utilizing processor
power in real time. Batch processing of oil refineries made autonomous ships
possible.

Central monitoring
Ships like this have push-button
redundancy, often automatic
lead/lag or master/slave
redundant motors or pumps.
Pushing the selector switch can
be automated – but can
changing the motor or cleaning
the strainer?

Automation has been around
• Completely autonomous operation has been possible for a long time
is possible
• STD Bus was 8-bit
• VME Bus opened up 16-bit process control using 6800 Motorola processors
• VME expanded to 32-bit and 64-bit versions
• These industrial bus standards, later becoming IEC and DIN standards,
facilitated the equivalent of the “internet of things” on an industrial scale in
the 1980s.
• The heart of the Apple, the heart of the MAC – the 6800, was now ready for
service in producing other things, not “merely” processing data.
• But how do things become represented as data?

Early shipboard
automation
8088 and 8086-based modules
ran many European ships in
the 1980s. EEPROM chips
were burned with the program
– all 16K of it.
We can still program those
chips in assembly language
and burn them in our PROM-
burner. Around 2000, we had
to buy a gross of the memory
chips to replace one chip.
Anyone need 143 16K 8-bit
chips?

Input/output modules –
The five senses of data
• Unlike humans, data has many more senses: pH, salinity, specific
gravity, viscosity, x-ray vision, sonar-sensing, thermal imaging. The
machine is only limited by the I/O.
• Even the most primitive ACCU system aboard ship can monitor any
and every characteristic in 24 milliseconds. Even midshipmen do not
move that fast.
• Analogue to digital converters allow proportional integral derivative
(PID) algorithms to run in stable software instead of as thermally-
sensitive capacitive shorting circuits used in the 1960s.
• Input/Output modules use more than five senses.

Modern
Input/output
This is a marine-rated analogue
input/output device that would
replace six card slots in one of
the previous slides. These are
more reliable that the old ones
and may last the life of the ship.

Input/output modules –
The “five senses” of data
• Each subsystem is a self-sufficient loop doing its part in a larger loop
and answering to the demands of the central processing unit.
Distributed I/O systems use a pyramid structure to keep most of the
processing local and the supervision not burdened with massive data
flows.
• This hierarchy of interdependent self-reliance is the key to a ship without a
crew.
• Existing ACCU standards will have to be expanded for autonomous ships.
• Required redundancy: N+1 becomes N+2 or N+3 on a ship without a crew
• The technology is all here, the specification has not been completed

1980’s human machine interface

Modern human
machine interface
Removable programming unit
on the left side of the photo
that replaces a PROM burner
in a modern ship.
Touch screen to the right
replaces a wall of
annunciators and ten-turn
potentiometers.

The 1980s ship was
almost as automated
as the 2015 ship.
The technology has improved
but not the culture – at least
not in the US. This three-panel
lineup would be a half panel
today but the ship probably
has the same number of
points monitored...maybe a
few more.

The learning-capable automation system
• An automation system can apply simultaneous analysis and
comparisons in real time, learning from system history to better
anticipate responses providing more appropriate system corrections
with each iteration of its ever-improving response curves.
• In an autonomous ship, the system learns the ship just as a crew would, but
all system information is shared, not subjectively compartmentalized, as with
a human crew.
• The engineering challenge is to parse and save the data while gleaning all that
can be learned from it. A complex system has large data needs. There is no
data center at sea.
• What is done at sea and what is done on land is part of the developing
methods of control.

The price of
success
One benefit of rapid response
to change is reduced failure of
equipment – problems are
caught sooner.
The inconvenient side of this
responsiveness is nuisance
trips.
How do you evaluate nuisance
trips without a crew?

Ship-automation limitations
• The limitations on autonomous vessels are not technical; they are
social. We can build and operate a remote-controlled or autonomous
vessel today. But our neighbors may not let us.
• Only scientific risk-analysis can determine actual risk
• Perceived risk is often at odds with science
• Here it is a relative risk, not an absolute risk. We compare an autonomous
vessel to a crewed vessel and compare the cargo risk and vessel risk.
• The actual risks include equipment failure and malicious interference –
hackers on line or pirates on speedboats.

Ship-automation limitations
• The limitations on autonomous vessels are social. Anticipated
skeptics include labor unions and environmental organizations.
• The likely cargoes are water, crude oil, coal, iron, bauxite, Portland
cement, pet coke or other low-cost, heavy cargoes with no time
constraints.
• The ideal autonomous ship will slow-bell across the earth with
steadfast determination and maximum efficiency.
• The first autonomous ships will not be box ships with frequent stops
and complex loading procedures.
• Tankers and bulkers natural auto-ships, especially in the Pacific Ocean.

Computers are getting smarter and deep level of machine learning are used to understand several sectors better
.
The Maritime sector can use these technologies in the new generation of operations hubs that are beginning to
emerge.

Computers and automation systems are becoming more
intelligent allowing this way vessel computers to
understand the environment and the maritime
conditions they encounter
.
Sophisticated algorithms (AI) not only provide onboard
computers with methods to solve problems encountered
but and can also predict possible future problems.
Worth noting that AI also is important for Maritime
Security as it can be used for in image, video, and audio
recognition
ARTIFICIAL INTELLIGENCE

How AI is Influencing the Shipping Industry
Today
Page1
HowAI is Influencing the
Shipping IndustryT
oday
By Captain Onur Yildirim,APCGlobal Marine Manager
Artificial intelligence (AI) plays a role in many industries, from
banking and cybersecurity to retail, automotive, and more.

Barriers to Artificial Intelligence
Implementation
How AI is Influencing the Shipping IndustryToday Page 44
There are pros and cons to everything, and AI is no different. Despite the benefits, which we will discuss in the
next section, the fear surrounding more intelligent solutions can often be a controversial topic.
T
oday, there are still barriers to the widespread adoption of AI, and not just in the maritime industry. Globally
some challenges need to be addressed and overcome before moving forward and implementing AI.
In general, there are four key obstacles:
• data integration
• trust issues
• time and energy limitations
• shortage of talent on specific skills needed

1. Poor Quality of Data
As an industry, there is a need for shared data to make high-quality decisions. The industry must move past the idea of
competitive challenges around data sharing to benefit all involved. The quality of data in the sector could slow down its adoption
of artificial intelligence (AI) technologies. The principal aim would be to improve decisions through the availability of data-driven
insights.
2. Lack of “Solid Information”
Furthering the quality of data would be the lack of reliable information across the entire supply chain, which would also prevent
its development. Analytic insights need sourcing from accurate data. Data-driven decisions are only as right as their
insights.Proper data collection and consistent data collection would be needed.
3. Fear of Job Replacement
There are concerns that computers and technology will have an impact on the type of jobs being created or replaced. The kind of
work is likely to shift when AI is fully adopted. Workers will need to spend time understanding and learning new technology in
their workplace. The industry as a whole will need to keep pace with the innovations of artificial intelligence, the Internet of
things, sensor technology, etc.
4. Transforming the BusinessThroughDigitalization will be a Process
Digitalization transformation is a process. There will be time constraints, limitations, and development costs. The process will
enhance ways of working smarter, simpler, and more efficient.
5. Lack of a Clear Strategy How AI is Influencing the Shipping IndustryToday Page 45

Advantages ofArtificial Intelligence in
Shipping for an Improved Future
The technology of using data as a tool to learn from the past to help you improve decision-making in the future is
invaluable. Some of the outstanding benefits of AI in the shipping industry include but are not limited to,
improved analytics for decision-making, automation, safety, route optimization, and increased efficiencies.
1.Advanced analytics - Advanced analytics are used to make valuable business insights from many data sources.
This will help ensure your decisions are based on data-proven methods.
2.Automated equipment - AI and automation play a role in the shipping industry. Machine learning capabilities
will help in the analysis of historical data by considering such things as weather patterns or busy/slow shipping
seasons. Automating processes can help identify problems before they happen. This allows time to make
adjustments.
3.Safety and improved security - Accidents can be reduced using artificial intelligence. AI can also be used to
detect threats and other malicious activities.
4. Route optimization - Route optimization would build optimization modelsto determine the most efficient route
to take. With the help of AI, a prediction of the best path with minimum fuel consumption, and considering the
weather can be calculated.

5. Performance forecasting - Performance forecasting could take the relationship between speed and power to predict changes in
performance due to underwater fouling. You could use historical data to understand what is the rate of the degradation of the
performance of the vessels.
Arundo offers software capabilities to connect real-time data to machine learning, analytical models, and simple interfaces
for better decisions. In the video below,they discuss how AI can help with route optimization and performance forecasting.
AI usually refers to Machine Learning, where computers learn over time by applying algorithms that will improve with
experience. For example, as stated above, AI in the shipping industry can be utilized to enhance shipping routes. AI can
determine the best course at the best speed.

The power of data allows the shipping industry to forecast and optimize future performance and so much more.
Below we also highlighted a quick side-by-side comparison of the pros and cons in the shipping industry when it comes to AI. It
is just the beginning.
How AI is Influencing the Shipping IndustryToday
Page10

Implementing DigitalTechnology
in Shipping - Use Cases
New technologies bring shifts in the way things are done. Below are just a few studies of AI in the works. It can
cut down on fuel consumption, improve shipping operations, and enable sustainable societies with smart
technologies. You can use AI in different areas of your business for better results.
1. Cut fuel consumption
Hitachi Europe Ltd., a subsidiary of Hitachi, Ltd., has partnered with Stena Line, one of the largest shipping
companies in Europe. Their goal is to implement artificial intelligence technology on ships to reduce fuel
consumption costs and become an essential tool in the company’s efforts to minimize environmental impact.
2. Using AI to improve shipping network operations
Orient Overseas Container Line (OOCL) teamed up with Microsoft’s research arm in Asia to use AI to enhance
shipping network operations. OOCL has a proud track record of adopting new technologies with real business
impact.
It has fully embraced a hybrid cloud infrastructure with auto-switching and auto-scaling throughout its
business. [source]

Internet of things (IoT) is making inroads into shipping especially
in using this technology for container tracking and reefer
monitoring.
IoT is increasingly being used for monitoring onboard machinery
for performance management and predictive maintenance
purposes.
IoT technology is improving dramatically with the use of deep
learning and high-volume data analytics
Industrial IoT

A controversial subject but a reality.
Limited scale autonomous surface vessels are already demonstrated
and trialed, illustrating how unmanned commercial craft could be
developed.
However, conservative views and the controversy surrounding this
concepts might not allow liberal investment and questions such as
how autonomous vessels can cope with congestion might
remain unanswered for quite sometime.
AUTONOMOUS SURFACE VESSELS

This process technology can revolutionize supply chain logistics and
cargo trade over maritime routes.
Blockchain processes can improve cyber security in maritime
transactions, even with future developments in cloud computing and
machine learning. Use of the Blockchain technology by Ship Registries
should not be ruled out.
BLOCKCHAIN

Augmented reality (AR) is an interactive experience of a
real-world environment where the objects that reside in the
real-world are "augmented" by computer-generated
perceptual information, sometimes across multiple sensory
modalities, including visual, auditory, haptic,
somatosensory, and olfactory.
Ship Bridges and ship remote operating centers already are
utilizing AR and deliver different levels of information to
end-users.
AUGMENTED REALITY

Even though robotics research has been performed for many decades, robotics adoption has not flourished in maritime.
However, with increasing interest in developing autonomous vessels, there will be greater need for robotics. Taking
humans off ships not only leads to navigational issues, but also adds challenges to maintenance and other manual
operations, such as line handling. Perhaps robots can be built to perform these operations with remote control
assistance.
ROBOTICS

In the new order of fuels, arriving in 2020, Power
generation must and will be changed dramatically,
with alternative fuels, energy-saving devices,
renewable energy and hybrid power generation all
potentially playing their part.
As the challenges are two-fold: environmental and
commercial, the use of machine/intelligence will
play a major role in achieving the envisaged goals.
Power and propulsion: new technologies

4.1 Propulsion (Main Engine) and Power
(AuxiliaryEngines) Monitoring & Control
Monitoring and control of the ships propulsion
and power is essential for its efficiency and safety
and there are many systems and parameters to
consider like: fuel consumption, combustion
temperature, engine temperature, diesel engine
safety and start/stop, generator voltage and
frequency control, generator load in KW and %,
load control, torque, heavy consumers logic,
control of diesel electric propulsion, thrusters
monitoring and control etc..

4.2 Auxiliary Machinery Monitoring and Control
Auxiliary machinery monitoring and control covers
several systems like: main sea & fresh water
cooling system – pumps, system pressure, temp.
etc., Potable and fresh water control, Air
compressors, Bilge & sludge control – Tank level,
pumps, Fuel oil system – Tank levels, temp.,
viscosity, flow, purifiers, heaters etc., Other cooling
systems, Boiler/steam system – pumps, valves,
pressure temp. etc., Air Conditioning, ballast water
treatment, exhaust gas treatment equipment.

4.3 Cargo & Ballast Monitoring &
Control
For safe on and off loading of
cargo, especially on tankers, this
process is closely monitored and many
times incorporates functions like: Level
gauging, Control of cargo pumps, Valve
control, Ballast & ballast pump control,
Heeling control, Remote monitoring of
temperature, pressure, and flow.

In order to further improve the ships efficiency many equipment manufacturers are
looking into feeding the main control and monitoring system with opportunities for
condition based monitoring. This would further improve the possibilities of
preventing breakdowns on board.
1. Temperatures of lube oil, JCW, exhaust gas, etc. are
2. measured.
3. Pressures of lube oil, JCW, fuel oil, and starting air etc. are measured.
4. Flow of fuel oil is measured while running.
5. Tank levels of Heavy fuel oil, diesel oil, and lube oil are measured.
For measuring the parameters we make use of the transducers, in turn sending
the input signal to the automatic control system.
Condition based monitoring

Ship operation and maintenance are also
affected by the technological advances.
On-board machinery and equipment can be
fitted with sensors and transmitters that report
performance and early signs of malfunction via
Wi-Fi to the ship’s central computer.
Real-time updates on weather systems, wind
and ocean currents will enable captains to
readjust navigation for lower energy
consumption.

Reliability
Centered
Maintenance
(RCM)

Evolution of Maintenance
At the very beginning, Maintenance was an appendix
to Operations / Production:
It existed only to fix failures, when they happened.
These were the days of absolute
Corrective Maintenance

As times went by, it was detected that many failures
have an almost regular pattern, failing after an
average period. Therefore, one could choose regular
intervals to fix the equipment BEFORE the failure:
Preventive Maintenance
Also know as Time Based Maintenance.

However, very often these failures happen in irregular
periods. To avoid an unwanted failure, the periods of
Preventive Maintenance are shortened. If equipment
conditions were known, the maintenance could be later.
Technology development enabled to identify failure
symptoms:
Predictive Maintenance
Also know as Condition Based Maintenance.

Many pieces of equipment have sporadic activity (alarms, stand-by
equipments, etc.). However, we must be sure that they are ready to run.
These are "hidden faults“. Detect and prevent hidden failure is called:
Detective Maintenance

The different failure modes mean that there’s not
one only approach, about Corrective, Preventive or
Predictive Maintenance Programs.
The correct balance will give in return better
equipment reliability, thus the name:
Reliability Centered Maintenance
Remember, my
kid, Prevention
is better than
Cure....
Take it easy,
grandma, not
always!

Reliability Centered Maintenance (RCM)
John Moubray 1949-2004
After graduating as a mechanical engineer in 1971, John Moubray worked
for two years as a maintenance planner in a packaging plant and for one
year as a commercial field engineer for a major oil company.
In 1974, he joined a large multi-disciplinary management consulting
company. He worked for this company for twelve years, specializing in the
development and implementation of manual and computerized
maintenance management systems for a wide variety of clients in the
mining, manufacturing and electric utility sectors.
He began working on RCM in 1981, and since 1986 was
full time dedicated to RCM, founding Aladon LCC, which
he led until his premature death in 2004.
John Moubray is today considered a synonym of RCM.

Its
What about a failure rate of 0.00006/event?
Quite good, no?
This was the average failure rate in commercial flights
takeoffs, in the 50’s. Two thirds of them caused by
equipment failures.
Today, this would mean 2 accidents per day, with
planes with more than 100 passengers!!!
That’s why Reliability Centered Maintenance has begun
in the Aeronautical Engineering. Pretty soon, Nuclear
activities, Military, Oil & Gas industries also began to
use RCM concepts and implement them in their
facilities.

Reliability and Availability
Bibliography: Kardec, Alan y Nascif, Julio - Manutenção- Função Estratégica, Editora Qualitymark
Reliability
Reliability is a broad term that focuses on the ability of a product
to perform its intended function. Mathematically speaking,
reliability can be defined as the probability that an item will
continue to perform its intended function without failure for a
specified period of time under stated conditions.
Reliability is a performance expectation.
It’s usually defined at design.
Availability
Depends upon Operation uptime and Operating cycle.
Availability is a performance result.
Equipment history will tell us the availability.

ENERGY
EFFICIENCY
MAINTENANCE
RELIABILITY
© RMCPL All rights reserved
COST & SAFETY
ENVIRONMENT
WORK LIFE

RCM – some definitions
 Maintenance: Ensuring that physical assets continue to do what their users
want them to do.
 RCM: a process used to determine what must be done to ensure that any
physical asset continues to do what its users want it to do in its present
operating context.
 RCM helps people determine the best maintenance tasks in a cost
effective manner for managing the functions of physical assets – and for
managing the consequences of functional failures.
 RCM does not challenge the design of the equipment or system

Why RCM?
 IN ORDER TO SUCCESSFULLY COMPETE TODAY,
PLANT AVAILABILITY AND RELIABILITY MUST
BE MAINTAINED AT DESIRED LEVELS WHILE
OPERATING COSTS MUST BE KEPT AS LOW AS
REASONABLY ACHIEVABLE.
 A KEY ELEMENT IN THIS COST REDUCTION IS
CONTROLLING MAINTENANCE PRACTICES.

RCM - features
 Structured - Logical – nothing done without a reason
 Reduces intrusiveness and improves flexibility of maintenance teams
 Auditable -- Quantifiable results and benefits
 Induces higher skills (cognitive and physical) of technicians
 Living document

RCM – Benefits
 Choosing the appropriate maintenance strategies/tasks
 Formulating a structured maintenance plan and schedule
 Avoid/minimize consequence of a failure
 Reduction in maintenance tasks (25% to 50%)
 Reduction in number of failures (15% to 25%)
 Reduction in costs (25% to 50%)
 Improved quality of maintenance actions
 Maximizing Reliability, Availability, Safety
 Optimum use of maintenance resources

Main Benefits
1. PHASE-OUT COSTLY INTRUSIVE
INSPECTIONS
2. DEVELOP CBM PROGRAM TO
CONDITIONALLY DIRECT MAINTENANCE
ACTIVITIES.
3. DISCOVER “BAD ACTORS”
4. IDENTIFYING MORE COST-EFFECTIVE
TASKS
5. REFINE PRIORITIZATION Of Maintenance

Maintenance Strategies & Evolution
 On-Failure maintenance (OFM)
 Time Based Maintenance (TBM)
 Condition Based Maintenance (CBM)
 Detective Maintenance
 Design Out Maintenance (DOM)
 Opportunity Maintenance (OM)

On-Failure Maintenance
 Advantages:
 Can be effective where consequence of a failure is zero
 Disadvantages:
 Affects production (undesired downtime)
 Affects quality
 Large stand-by crew
 Large stock of spare parts

Time Based Maintenance
 Advantages:
 Can be applied to components purely subjected to time based wear (2%)
 And consequences of a failure is relatively low
 Disadvantages:
 Scheduled overhaul; however intensive; of complex equipment has little or no effect
on in-service reliability
 Increase in cost
 Lack of time
 Large stock of spare parts
 Large crew needed

Condition Based Maintenance
 Advantages:
 Maintenance can be done as needed
 Can be applied to random failures (minimum 68%)
 Applied where consequences of a failure ranges from Low to high
 Detects incipient and hidden failures in time
 Prevents secondary damage
 Maintenance can be planned in advance to fit production windows
 Resources can be optimized as per need and operating context
 Can be operator driven or system driven or IOT driven
 Disadvantages:
 High skill needed to implement and run a CBM system
 Multiple failures can happen at the same time stressing the maintenance system

Design Out Maintenance (DOM)
 Advantages:
 Can be applied to prevent repeat failures
 Minimizes or eliminates failure rate
 Generally applied where consequences of a failure is high
 Maintenance can be minimized
 Minimum resources needed to maintain assets
 Disadvantages:
 High skill needed
 Time

EXISTING STRATEGIES
© Dibyendu De
OFM
no control on failures
TBM
Preventing age related failures
(2% to 5%)
Detects random failures(>68%)
RCM
prevents consequences of failures
CBM

© RMCPL All rights reserved
On-Failure
Fix it when it fails
Condition Based
Maintain based upon known condition
Maintenance Plan
Fixed Time
Maintain based upon
calendar or running time
Design Out
Identify & design out root cause of failure

MTBF = Mean Time Between Failures
MTTR = Mean Time To Repair
A first definition:
MTBF
Availability =
MTBF + MTTR

Availability definitions
MTBF = Mean Time Between Failures
MTTR = Mean Time To Repair
MTBM = Mean Time Between Maintenance actions
M = Maintenance Mean Downtime (including preventive
and planned corrective downtime)
Inherent Availability: consider only corrective downtime
Achieved Availability: consider corrective and preventive
maintenance
Operational Availability: ratio of the system uptime and total
time
MTBF
Inherent Availability =
MTBF + MTTR
MTBM
MTBM + M
Uptime
Operation Cycle
Achieved Availability =
Operational Availability =

MTBF = (250 + 360 + 200 + 120) / 4 = 232.5 days
MTTR = (9 + 6 + 2) / 3 = 5.67 days
Availability = 232.5 / (232.5 + 5.67) = 97.62 %
250 days 360 days
9 d 6 2
200 days 120 days
Downtime
= 947 days
Downtime
MTBF = (180 + 400 + 120 + 233) / 4 = 233.25 days
MTTR = (7 + 4 + 3) / 3 = 4.67 days
Availability = 233.25 / (233.25 + 4.67) = 98.04 %
= 947 days
180 days 400 days 120 days 233 days
7 4 3

To improve Availability:
Improve MTBM:
•Reduce Preventive Programs to a minimum, or, have Preventive intervals as well
defined as possible.
•Using Predictive techniques whenever possible
•Implementing Maintenance Engineering (RCM, TPM...)
Minimize M:
•Implementing Maintenance Engineering (Planning, Logistics...)
•Improving personnel technical skills (training)
•Developing Integrated Planning (Mntce+Ops+HSE+Inspection+...)
Achieved Availability↑ = MTBM↑/ (MTBM+M↓)

Improving Produ
Productivity Improvement Factors:
Detailed work planning
Delivering equipments to Maintenance as clean as possible
Check-list at the end of Maintenance activities
Complete and comprehensive Equipment data available
Supplies available on job site
Skilled personnel

Availability benc

Translating percents to daily routine...
Availability % Downtime per year Downtime per month* Downtime per week
90% 36.5 days 72 hours 16.8 hours
95% 18.25 days 36 hours 8.4 hours
98% 7.30 days 14.4 hours 3.36 hours
99% 3.65 days 7.20 hours 1.68 hours
99.5% 1.83 days 3.60 hours 50.4 min
99.8% 17.52 hours 86.23 min 20.16 min
99.9% ("three nines") 8.76 hours 43.2 min 10.1 min
99.95% 4.38 hours 21.56 min 5.04 min
99.99% ("four nines") 52.6 min 4.32 min 1.01 min
99.999% ("five nines") 5.26 min 25.9 s 6.05 s
99.9999% ("six nines") 31.5 s 2.59 s 0.605 s

Maintenance Programs costs
Maintenance Program Cost US$/HP/year
Corrective (unplanned) 17 to 18
Preventive 11 to 13
Predictive / Planned Corrective 7 to 9
NMW Chicago

Benchmarking balance between Mtce programs
NMW Chicago
Maintenance activities %
Corrective actions 28
Preventive actions 36
Predictive actions 19
Maintenance studies 17

Definitions
Failure rate (λ)
Failure rate (λ) is defined as the reciprocal of MTBF:
Bibliography: Lafraia, João Ricardo - Manual de Confiabilidade, Mantenabilidade e Disponibilidade, Editora Qualitymark
Reliability: R(t)
Let P(t) be the probability of failure between 0 and t; reliability is defined as:
R(t) = 1 – P(t)
MTBF
(t) 
1

Some math...
Considering rate failure (λ) constant, it is proven (check at www.weibull.com),
that R(t), meaning the probability of having operated until instant t, is given by:
R(t)  et
This reinforces the idea that Reliability is function of time, it isn’t a definite
number. So, it’s incorrect to affirm: “This equipment has a 0.97 reliability
factor...”. We should rather say: “This equipment has 97% reliability for
running, let’s say, 240 days...”

Tricks and
Historically, an equipment has 4 failures per year. Which is the
reliability of this equipment for a 100 days run?
λ =4/365 λ =0.011/day R(100) = e-0.011x100
= e-1.1
= 0.333 = 33.3%
The probability of having no failure until 100 days is 33.3%
Some upgrades have been made, so failure rate now is 2 per year
(meaning that MTBF has doubled). Which is the reliability for a 100
days run?
λ =2/365 λ =0.0055/day R(100) = e-0.0055x100
= e-0.55
= 0.577 = 57.7%
The probability of having no failure until 100 days is 57.7%.
As seen, doubling MTBF doesn’t double reliability.

Trick and
Historically, an equipment has a MTBF = 200 days. To improve
10% its reliability to operate on a 100 days run, which percent
should MTBF be improved?
λ =1/200 λ =0.005/day R(100) =e-0.005x100
= e-0.5
= 0.607 = 60.7%
To improve this reliability in 10%, new reliability should be:
R’(100) = 1.1 x 0.607 = 0.668 = e-λ’x100
Ln 0.668 = -λ’ x 100 -0.403 = -λ’ x 100 λ’= 0.00403
1/MTBF’ = 0.0043 MTBF’ = 232 days
232/200 = 1.16 MTBF should improve 16%

Trick and
As per the manufacturer, an equipment has a 90%
reliability to run over one year. If you want to have a 95%
confidence that it will not fail, how long should it take
until the equipment undergo a Preventive maintenance or
some predictive technique?
0.9 = e-λx365
ln 0.9 = -λ x 365 -0.1054 = -λ x 365
λ = 2.89 x 10-4
/day
0.95 = e-λt
ln 0.95 = -λt -0.0513 = - 2.89 x 10-4
x t
t = 177.5 days
For practical purposes, this equipment could be in a
semester preventive / predictive program.

Tricks and
Reliability and MTBF
1.2
0.368 0.368 0.368 0.368 0.368 0.368
0.368
0
0.2
0.4
0.6
0.8
1
1 51 101 151 201 251 301 351
Days
MTBF=50
MTBF=100
MTBF=150
MTBF=200
MTBF=250
MTBF=300
MTBF=365

System in
1 2 3
Let P1=5%, P2=10% and P3=20% be the failure probability of each component of
this system, in a certain period. Which is the reliability of this system, in series?
This system will run, provided that ALL its components run. So, their reliabilities
are multiplied.
R1 = 1 – P1 = 1 – 0.05 = 0.95
R2 = 1 – P2 = 1 – 0.10 = 0.90
R3 = 1 – P3 = 1 – 0.20 = 0.80
R = R1 x R2 x R3 = 0.95 x 0.90 x 0.80 = 0.6840 = 68.4%
System failure probability 31.6%
System failure probability is bigger than each individual component. System
reliability is less than each component.

System in p
1
2
3
Let P1=5%, P2=10% and P3=20% be the failure probability of each component of this
system, in parallel, in a given period. Which is the reliability of the system, in parallel?
This system will run until ALL components fail. In this case, the failure probabilities
are multiplied.
P = P1 x P2 x P3 = 0.05 x 0.10 x 0.20 = 0.0010
R = 1 – P = 0.999 = 99.9%
System failure probability 0.1%
System failure probability is less than each component. System reliability is bigger
than each component.

Mixed sy
1 2 3
4 5
If P1=10%, P2=5%, P3=15%, P4=2% and P5=20%, which is the system reliability?
123
45
R1= 1 – 0.10 = 0.90
R3= 1 - 0.15 = 0.85
R4= 1 – 0.02 = 0.98
R5= 1 – 0.20 = 0.80
R45 = 0.98 x 0.80 = 0.7840 P45= 0.2160
System
P123= 0.2733 Psystem = 0.2733 x 0.2160 = 0.0590

Redun
A
B
C
Failure probability is P= 0.1 (10%), and reliability is R=1-0.1= 0.9 (90%)
Three pumps in parallel, so:
(R + P)3 = R3 + 3R2P + 3RP2 + P3= 0.93 + 3x0.92x0.1 + 3x0.9x0.12 + 0.13
(R + P)3 = 0.729 + 0.243 + 0.027 + 0.001
The pumps A, B y C are feed pumps of a plant. To
operate in full condition, it’s necessary that at least
two of these three pumps are running. Failure
probability of each one is 10%. Which is the
Three running: 0.729
Two running and one off: 0.243 Reliability = 0.972 = 97.2 %
One running and two off: 0.027
None running: 0.001 No full production = 0.028 = 2.8 %

Redun
A
B
C
The pumps A, B y C are feed pumps of a plant.
Pump A flow rate is 2,000 gpm, pump B flow rate is
1,800 gpm and pump C flow rate is 1,700 gpm. To
operate, the plant need at least a feed rate of 3,600
R =0.85. Which is the plant reliability?
C
As the plant needs at least 3,600 gpm, to supply this, there will be these cases:
A ∩ B ∩ C 0.95 x 0.90 x 0.85 = 0.72675
A ∩ B ∩ notC 0.95 x 0.90 x (1 – 0.85) = 0.12825
A ∩ notB ∩ C 0.95 x (1 – 0.90) x 0.85 = 0.08075
Plant reliability = 0.93575 93.6%

Systems in series
Systems in series
1
1 component
2 components
3 components
0.4
4 components
0.3
10 components
0.1
0
Component reliability
0.2
0.5
0.6
0.7
0.8
0.9
0.5
0.52
0.54
0.56
0.58
0.6
0.62
0.64
0.66
0.68
0.7
0.72
0.74
0.76
0.78
0.8
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0.98
1
System
reliability
1 component
2 components
3 components
4 components
10 components

Systems in p
Systems in parallel
1.2
1 component
2 components
0.8
4 components
3 components
10 components
0
Component reliability
0.2
0.4
0.6
1
0.5
0.52
0.54
0.56
0.58
0.6
0.62
0.64
0.66
0.68
0.7
0.72
0.74
0.76
0.78
0.8
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0.98
1
System
reliability
1 component
2 components
3 components
4 components
10 components

System and Component Redundancy
B A B
A’ B’
Component Redundancy
AA’ and BB’ subsystems’ reliability: 1
- (1-R)2
=1 – 1 + 2R – R2
= 2R – R2
System reliability:
2 2
R = (2R-R )
component redundancy
A
A’ B’
System Redundancy
Which of these systems would have a better overall reliability
(let’s assume all components have the same reliability R)?
AB and A’B’ subsystems’ reliability:
R2
System reliability:
R
R
R
system redundancy
system redundancy
= 1 – (1-R )
2 2
= 1 – 1 + 2R -R
2 4
system redundancy = 2R2
- R4
R comp red - R syst red = (2R-R ) - (2R - R
2 2 2 4
) = 4R – 4R + R - 2R + R
2 3 4 2 4
R comp red - R syst red = 2R4 3
– 4R + 2R = 2R (R – 2R + 1) = 2R (R-1) ≥ 0
R comp red ≥ R syst red
2 2 2 2 2

Active and Passive Redundancy
A
B
Active Redundancy:
Both equipment are
operating at the same
time, sharing the load.
If one fails, the other
one will carry the load
alone.
Passive Redundancy:
One equipment is
operating, and the other
one is at stand-by,
starting operating after
the failure of the first
one, pending upon a
switch system.

Getting closer to real world...
In systems with active redundancy all redundant components are in
operation and are sharing the load with the main component. Upon
failure of one component, the surviving components carry the load,
and as a result, the failure rate of the surviving components may be
increased.
The reliability of an active, shared load, parallel system can be
calculated as follows:
where: λ1 is the failure rate for each unit when both are working and
λ2 is the failure rate of the surviving unit when the other one has
failed.
If 2λ1 = λ2, then:

e 20.00041
100

R(100)  e0.082
 4e0.0615
e0.082

R(100)  0.9213 4(0.9404 0.9213)
R(100)  0.9977
If there were no increase in failure rate, system reliability would be 0.9984. Look
like nothing, but this means a 30.5% decrease in system MTBF!!!
20.000410.000615
20.00041
R(100)  e 0.000615
100

20.00041x100 


 
e
In a system with active redundancy, reliability of each of the two components for
100 days is R=0.96, when sharing the load. If one compontents fails, the
surviving one will have a 50% increase in its failure rate. Which is it the system
reliability for 100 days?
R(100) = 0.96 = e-λx100
ln 0.96 = -100λ λ = 0.00041
1
λ2 = 1.5 x λ1 = 0.000615

The redundant or back-up components in passive or standby systems start
operating only when one or more fail. The back-up components remain dormant
until needed.
For two identical components (primary and back-up) the formula is:
R(t) = e-λt
(1+λt), considering a perfect switch
If the reliability of the switch is less than one, the reliability of the system is
affected by the switching mechanism and is reduced accordingly:
R(t) = e-λt
(1+R λt),
sw sw
R switch reliability
The reliability of a standby system consisting of one primary component with
constant failure rate λ1 and a backup component with constant failure rate λ2 is
given by:

Two feed pumps in a nuclear power plant are connected in a
stand-by mode. One is active and one is on standby. The
power plant will have to shut down if both feed pumps fail. If
the time between failures of each pump has an exponential
distribution with MTBF = 28,000 hours, and the failure rate of
the switching mechanism λsw is 10 what is the probability that
the power plant will not have to shut down due to a pump
failure in 10,000 hours?
-6
 e0.01
 0.9900
6 4 2
 e10 10
 e10
Rsw
R(t) = e-λt
(1+Rswλt),
Switch reliability:
λ = 1/MTBF
 1 10000
R(10000)  e 28000  (1 0.9900 
R(10000)  e0.3571
 (1 0.3536)
R(10000)  0.6997 1.3536
R(10000)  0.9471
10000)
28000
1
R(t) = e-λt
(1+R λt)
sw

Bathtub
Early Life (Burn-in, infant mortality)
•large number of new component failures which decreases with time
Useful Life
•small number of apparently random failures during working life
(λ constant)
Wear-out
• increasing number of failures with time as components wear out

Bathtub Curve
Early Life:
•sub-standard materials
•often caused by poor / variable manufacturing and poor
quality control
•prevented by effective quality control, burn-in, and run-in, de-
bugging techniques
• weak components eventually replaced by good ones
•probabilistic treatment less important
Useful Life:
• random or chance failures
•may be caused by unpredictable sudden stress
accumulations outside and inside of the components beyond
the design strength
•over sufficiently long periods frequency of occurrence (λ) is
approximately constant
•failure rate used extensively in Safety & Reliability analyses
Wear-out period:
• symptom of component ageing
•prediction is important for replacement and maintenance
policy

Different bathtub curves
These statistics are from
aeronautical industry. In a
process plant, like a
refinery, do you think the
percent of each one
would be about the
same?

Different bathtub curves
Which of these curves
would be applicable to:
A pump?
An electronic instrument?
A tire?

Failure
Common sense tells that the best way to optimize the availability of plants is to
implement some Preventive maintenance.
Preventive maintenance means fixing or replacing some pieces of equipments and/or
components in fixed intervals. Useful lifespan of equipments may be calculated with
Failure Statistical Analysis, enabling Maintenance Department to implement Preventive
Programs.
This is true for some simple pieces of equipment and components, which may have a
prevailing failure mode. Many components in contact with process fluids have a regular
lifespan, as well as cyclic equipment, due to fatigue and corrosion.
But, for many pieces of equipment there’s no connection between reliability and time.
Furthermore, as seen in Reliability curves, defining the optimum interval for Preventive
maintenance may be a hard task. Besides, fixing or even replacing the equipment may
bring you back to Infant Mortality period...

Preventive maintenance may cause failures earlier....
Time
The failure likelihood is earlier!!!!
λ
Let’s
define
Preventive
maintenance
here…
Here
begins
wear-out
period.
Failures
are
likely
to
happen…

Turna
Turnarounds are often seen by Operations as an unique opportunity to have all
problems solved, all equipment fixed…
Meanwhile, for Maintenance, a Turnaround is a huge event, time & resources & costs
consuming, in which ONLY should be done whatever CANNOT be done on the run,
during normal operation.
Frequently, Maintenance is asked to perform General Maintenance in ALL rotating
equipment of a Unit, during its Turnaround. Matter of fact, if these equipment have
spares, this General Maintenance should be done out of the TAR.
Why do Operations want everything to be done during the TAR?
1) Because Ops don’t have enough confidence that it will be done during routine
maintenance.
2) Because they don’t feel comfortable running with an equipment momentarily without
spare… the same way when we have a flat tire, we just drive with the spare tire
enough to hit the tire repair shop…

Turna
1) Ops don’t have enough confidence that it will be done during routine maintenance.
To improve TAR results, reversing the vicious cycle below, Maintenance
management has to improve Routine Maintenance!
To much to
be done
during TAR
TAR won’t be
able to
perform all
that has to be
done
Many
equipments
left to
Routine
Maintenance
Many
equipments
left to TAR
Not in excess
equipments to
be done
during TAR
TAR will carry
out all services
needed
Unit running
well
Good routine
maintenance

Turna
2) Because they don’t feel comfortable running with an equipment momentarily without
spare… the same way when we have a flat tire, we just drive with the spare tire
enough to hit the tire repair shop…
Consider these two pumps in a Passive Redundancy
(one will be as stand-by). Assume that during the first
100 h after a General Maintenance such a pump will
have a 70% reliability, and after this, for an one year
period, it would run with 97% reliability (which are
reasonable assumptions!!!).
If General Maintenance is performed in a Preventive or Predictive Program, during
normal operations, during repair time the unit will be running pending upon a unique
pump, with a 97% reliability.
If during TAR both pumps will be under General Maintenance, during the first 100
hours the system reliability (considering a perfect switch) would be 94.5% (using the
R(t) = e-λt
(1+λt) formula) . So, the unit would run for a period of time with two
available pumps, but with an overall reliability below if it would be running with only
one pump!

RCM Implementation Flowchart
Will the failure affect
directly Health, Safety or
Environment?
Will the Failure affect
adversely the Mission, Vision No
and Core Values of the
Company?
Will the failure cause
major economic losses?
(harm to systems and / or
machines)?
Is there some Cost-
effective Monitoring
Technology available?
Deploy Monitoring
techniques
Predictive Maintenance Preventive
Maintenance
Run-to-fail?
Re-design the system,
accept failure risk, or
install redundancy
Yes
No
Yes
Yes
Yes
No
No
No
Are there regular failure
patterns (time intervals)?
Yes

Another RCM Implementation Flowchart
If this thing breaks will it
be noticed?
Can preventing it break
reduce the likelihood of
multiple failures?
Is it cheaper to prevent it
breaking than the loss of
production?
Is it cheaper to prevent
it breaking than to fix it?
No
Yes
Yes No
Yes No
Can preventing it break
reduce the reduce the
risk to the environment
and safety?
Yes Yes No Yes
No No
If this thing breaks will it
hurt someone or the
environment?
No If this thing breaks will it
slow or stop production?
Yes
Prevent it Check to see Prevent it Re-design it Prevent it Let it break Prevent it Let it break
breaking if it is broken breaking breaking breaking

Non-lethal anti-boarding systems

Driving Digital Transformation
A Framework
and Process
Action
Decision-
Making
Analysis &
Modeling
Planning &
Design
Visualization &
Mapping
Data Management
& Integration
Geographic
Knowledge
Web
GIS

International Hydrographic Organization
Organisation Hydrographique Internationale
The Fourth Industrial revolution
• Lineal Growth vs Exponential growth
• We can’t use the past to predict the future
• Change is accelerating
- Faster changes in the next 50 years than in the past few hundred
- a new “Seaconomics” era
- GDP and cargo volumes are decoupled
• Change creates new opportunities – new technologies
• A Digital Vision  powered by Data (in time and space)
Image by Christoph Roser. "Christoph Roser at AllAboutLean.com.”- Own work, CC BY-SA 4.0,https://commons.wikimedia.org/w/index.php?curid=47640595

Key technological factors
• Big Data
- Volume, Velocity and Variety
• Internet of Things (IoT)
• Artificial Intelligence (AI)
- Deep Learning
• Augmented Reality

We can see their effects: Autonomous Ships
Fast developments
around the world
Bigger, more efficient, more complex: new machine readable products

MRFs
SSDM*
SBP**
Media
SSDM & SBP
GDBs
Tiled*
Geotiffs
Cloud Storage
Processing VM
#2 (ArcGIS Pro)
ArcGIS HA Enterprise Cluster:
ArcGIS Server, Image Server, Subsurface Server,
Geoevent Server, Enterprise GDB,
Pixels
Kognifai
(Azure)/AWS
Media, seg-y
Processing VM
#1 (ArcGIS Pro)
Storage VM(s)
Import Source Data
AGOL
KognifAI
Apps
SmartOcean
Offshore
SmartOcean
Onshore
Ext.
ArcGIS
Portals
SmartOcean Offshore
NAS
SmartOcean Web Services
and Apps
SmartOcean Portal
Connect
New Apps being produced and a Cloud Ecosystem

𝑡𝑛𝑜𝑤 𝑡𝐴𝑢𝑡𝑜𝑛𝑜𝑚𝑜𝑢𝑠 𝐴𝐼
Machine
assisted
decision
support
Information
Technology
S-100
implementation
Post S-100 era
Evolve with Technology ( The Hydrographic Universe expansion)
Too slow, steep curve = too late
Too fast, away from
standards = costly, unrealistic
Graph not at scale, conceptual only
Full Automation
No Automation

AUTONOMOUS SHIP
smartphone, the smart ship will revolutionise
the landscape of ship design and operations”
“Autonomous shipping is the future
maritime industry
. As disruptive
of the
as the

Maritime Autonomous Surface Ship (MASS)

World’s First Autonomous Shipping Company
Wilhelmsen and KONGSBERG joined forces to take the next step in
autonomous shipping by offering a complete value chain for autonomous
ships, from design and development, to control systems, logistics services
and vessel operations.

ROLLS-ROYCE AND GOOGLE PARTNER TO
CREATE SMARTER, AUTONOMOUS SHIPS
Rolls
this
use
Royce announced
month that it will
Google’s Cloud
Learning
Machine
Engine across a range of
applications, designed
today’s
to both make
ships safer and
efficient, and to
more
launch
the ships of tomorrow.

Ship Intelligence will make greater use of ship systems and
sensors to enhance both crew and vessel operating
efficiency.

Yara Birkeland is set to be the world's first all-
electric, autonomous shipping container vessel .

World’s First Fully Autonomous Ferry Demonstrated
Rolls-Royce and Finnish state-owned
ferry operator Finferries successfully
demonstrated the world’s first fully
autonomous ferry in the archipelago
south of the city of Turku, Finland.
The car ferry Falco used a combination of
Rolls-Royce Ship Intelligence
technologies to successfully navigate
autonomously during its voyage between
Parainen and Nauvo. The return journey
was conducted under remote control.
The vessel detected objects utilising sensor fusion and artificial intelligence
and conducted collision avoidance. It also demonstrated automatic berthing
with a recently developed autonomous navigation system. All this was achieved
without any human intervention from the crew.

“SEA HUNTER,” WORLD’S LARGEST
AUTONOMOUS SHIP, U.S. NAVY
The U.S.
Defense
Projects
Department of Defense’s
Advanced Research
Agency (DARPA) has
completed trials of the “Sea Hunter”
– the
ship.
which
world’s largest unmanned
The vessel demonstrator,
was tested as part of the
agency’s Anti-Submarine Warfare
(ASW) Continuous Trail Unmanned
Vessel (ACTUV) program, has
officially been transferred to the
Office of Naval Research (ONR) for
further development.

FOR THE SMART SHIP REVOLUTION TO BECOME
A REALITY A NUMBER OF CRITICAL QUESTIONS
NEED TO BE ANSWERED

A ship’s ability to monitor its own health, establish
and communicate what is around it and make
decisions based on that information is vital to the
development of autonomous operations
Technology
The need is to develop a set of electronic senses that inform an
electronic brain and allow the vessel to navigate safely and avoid
collisions.

A typical autonomous ship command and control system.

Onboard autonomous ship systems and the Shore Control Centre

Advanced Sensor Module
On an unmanned ship, sensors and sensor data processing are
replacing the perceptions of the officer of the watch and thus are
critical elements in the realization of autonomy.
The Advanced Sensor Module is responsible for object detection and
classification and environmental perception. It uses input data from
infrared and visual spectrum cameras as well as radar and AIS data
to detect objects and determine if they are a danger to the ship or if
they need to be investigated further, e.g., to identify life rafts,
flotsam, or dangers to navigations.
It maintains a proper lookout for ship traffic and obstacles and
monitors the environmental conditions in the vicinity of the ship.
Sensor information is mainly used by the autonomous Deep Sea
Navigation System but is also presented on an integrated situation
display in the Shore Control Centre.

Deep Sea Navigation System
The Deep Sea Navigation System ensures that the ship follows its planned route
within the allowable deviations given by the present operational envelope.
Deviations can be caused by developing severe weather conditions or to avoid
complex traffic situations.
In order to handle a ship on trans-oceanic voyages without on-board crew, the
project has introduced the Deep Sea Navigation System, which:
Determines COL REG-obligations towards other ships and maneuvers the
autonomous ship accordingly to the rules.
Optimizes trans-oceanic voyage plans based on meteorological forecasts.
Operates the ship safely in immediate and harsh weather conditions in
accordance with the IMO weather guidance criteria.
The Deep Sea Navigation System can operate fully autonomously but also allows the
Shore Control Centre operator to interact and thus to remotely control the ship.

Remote Maneuvering Support System
Remote Maneuvering Support System aids
while
in carrying out
navigating in
maneuvers for collision avoidance,
constrained waterways and in ports.
By providing the anticipated
essential importance to safe
autonomous ship operation.
ship motion
and
trajectory, it is of
efficient unmanned and
The Remote Maneuvering Support System provides calculations
and displays for anticipated ship movements under constraints of
maneuvering ability.

Engine Monitoring and Control System
The Engine Monitoring and Control System is an enhancement to
existing ship automation and control systems.
The main aim is to add more advanced condition-monitoring
functionalities. Besides condition monitoring, adding of increased
digital interfaces to the navigation systems and the Shore Control
Centre are necessary to allow autonomous and unmanned
operation of engine room and other technical systems.
It allows very compact information to be sent to the Shore
Control Centre with the possibility to request lower level
measurements or intermediate calculations where needed.

Shore Control Centre
autonomous ships. Most of the time, the ships are operating without
any need for intervention from shore.
In cases where the automated onboard systems cannot safely
handle a situation, assistance will be provided. The limits for what is
considered safe are customizable within the so-called operational
envelope, setting navigational boundaries.
The operational envelope will also include other factors such as
visibility, wave height and traffic.
The Shore Control Centre acts as a continuously manned
supervisory station for monitoring and controlling a fleet of

Engine Monitoring and Control System
The Engine Monitoring and Control System is an enhancement to
existing ship automation and control systems.
The main aim is to add more advanced condition-monitoring
functionalities. Besides condition monitoring, adding of increased
digital interfaces to the navigation systems and the Shore Control
Centre are necessary to allow autonomous and unmanned operation
of engine room and other technical systems.
It allows very compact information to be sent to the Shore Control
Centre with the possibility to request lower level measurements or
intermediate calculations where needed.

AUTOMATED
ELECTRONIC DATA
EXCHANGE

Automation of ship reporting functions
has taken a big step forward with two
important decisions by IMO.
One concerns the introduction of the
electronic exchange of information as a
universal, binding requirement for the
purpose of facilitating the business of
international maritime traffic.
The other concerns the standardisation
and harmonisation of ship reporting in
support of e-navigation developments
aimed at simplifying the communication
of navigational safety information
between ship and shore and its
harmonised display on ship bridge

IMO’s ongoing work on standardisation and
harmonisation of ship reporting, which is within
SOLAS Regulation V/11, involves the revision of
the associated guidelines and criteria for ship
reporting systems. It concerns one of the five
selected priority tasks under IMO’s four-year
work programme (2016-2019) on the
implementation of e-navigation
The latter type of information should not unduly
burden ship bridge personnel, and it should
preferably be transmitted using standard
electronic tools such as internet, e-mail and
electronic data interchange (EDI).

South Korean delegates raised the
possibility of the maritime cloud
providing the communications
framework to support the seamless
exchange of electronic data for ship
reporting systems.

AFTER
Partner logo
Photos: TT
Both crew
members died

Autonomous- sensing modality and software process
Source : Analog devices, Chris Jacobs
Source : Bhat 2017
• Video camera and AI technology (Tesla)
• Precise sensor and Mobile Mapping System (Google)

Different automation strategies
• Everything Somewhere (ES) and Something Everywhere (SE) strategies
• Different requirements for Marine AtoN between coastal and ocean navigation
• Density of traffic of the area (Mix with conventional vessels)

Infrastructure support levels for automated driving (ISAD)

Intelligent Infrastructure_maritime
• Development of Big data, AI, IoT
, Block chain, 5G, sensors
• How does a Marine AtoN become smart?
• Safety of navigation, Smart Port, logistics
• Complementary use of Marine Aids to navigation
Korean SMART AtoN project Virtual AtoN navigation test

Today there are more than 470,000
refrigerated “reefer” containers,
carrying anything from bananas to
pharmaceuticals to sashimi-grade
tuna.
The system enabling this is RCM,
which stands for Remote Container
Management.
It’s simple technology – a modem,
GPS, wireless SIM card and satellite
link deployed on a global scale, and it
is changing the concept of supply
chain visibility, and the costs and

If you think about a basic supply chain, it
stretches across the world. It involves trucks,
terminals, depots, an ocean carrier and time.
There is no end-to-end visibility and very little
control, which for refrigerated cargo is very risky.
perishable commodities are time sensitive and
require precise temperature and atmospheric
conditions.
If the power goes off on the reefer or a
malfunction occurs and it is not discovered quickly
enough in the terminal, on the truck or ship, an
entire container of goods can be spoiled.
As a result, shipping companies spends
thousands of hours and about USD 200 million
every year on physical inspections of its containers
before customers use them and continuous
monitoring of their functionality during a journey.

And since people make mistakes and accidents
happen, shipping companies also pays millions in
claims to customers for damaged cargo – most of
which is related to the power on the reefer being off
for too long.
With RCM, all of that changes. Instead of counting
on human eyes and hands to inspect and monitor
reefers all over the world, the technology does it
instead – removing much of these costs, along with
many others including the danger associated with
people walking among container stacks and handling
electricity.
If the conditions inside the container change or the
reefer malfunctions, an alarm instantly appears on
the screens of the RCM teams on shore. In the same
instant, the alarm, which describes the problem and
the level of urgency, also goes to the closest local
repair vendor.

With the physical preparation, handling and
monitoring of these containers every hour of
every day for a supply chain journey that can
last more than a month. This technology gives
us total visibility into our operations, our
suppliers, performance and our customers,
supply chains, in real-time. That’s a powerful
capability, particularly for sensitive perishable
cargo.

It starts with the hardware mounted on all
smart containers. A GPS allows global tracking
and a modem and SIM card enable the reefer’s
atmospheric conditions and power status to be
collected, stored and shared.
A satellite transmitter mounted on vessels
picks up the data streaming from the modem
and sends it real-time to a satellite that beams it
back to the RCM teams located around the
globe.
T
echnology and the data flow and capture it
enables, whether it is “smart” containers or the
development of a comprehensive e-platform for
customers, is driving Shipping companies next
phase of operational and commercial
excellence.

Individual sensors on ships already provide valuable
insight. One example is bunker consumption flow
metres, approximately 3,000 of which will be installed on
370 vessels by the end of 2017. These metres measure
fuel consumption and relay this data in real-time to the
vessel bridge and to shore, enabling shipping
companies to continually optimise the fleet’s operational
performance
Shipping Company’s Online Portal into a
comprehensive online shipping platform is well
underway. The majority of customers say they want a
predictable, self-service type process for handling their
shipping needs. An online platform will also reduce the
millions of phone calls and emails related to transaction
support that companies handles, enabling it to increase
the time it spends on developing business. The data
collected will also provide a rich source of insight into
customer behaviour

The collection and analysis of the data
the business produces across its global
footprint are also increasingly important
Companies. Here, a growing team of data
scientists in the Advanced Analytics team
are using mathematics and computer
programming code to save Companies
millions by further optimising empty
container flows, developing more accurate
container supply and demand forecasts,
and providing insight into customer
behaviour and profitability.

Future of Vessel Traffic Services
• Conventional role of VTS (management of the traffic)
• Information hub
• Implications of Autonomous ships (MASS) – opportunities and issues
• Managing ship traffic comprising both MASS and conventional ships
• Digital interaction with ships, Remote Control Center (RCC), and others
• Provision of advice, warning, and instruction to the RCC
• Emerging situation where the ship needs to be contained/controlled to
mitigate incidents
• Use case studies on trials and testbeds

VesselFinder vessel tracking system may offer the users chance for
vessel tracking in real time totally for free. There is also a new
version of the VesselFinder website that was launched with
OpenStreetMap interface, which is very simple and easy for the users
for AIS Live vessel tracking.
AIS Live ship tracking is a place where people may search for their
own vessel, vessel of their competitors, all worldwide ports, latest
news for the maritime industry and business.
AIS Live vessel tracking service by VesselFinder is a totally Free
internet-based service, that does not require any registration, it is
also with really fast interface and quite simple navigation facility.
There is also a modified simple map with little icons for the
vessels’ positions which is better for the users for their vessel
tracking.

6.1 MAIN FEATURES OF THE VESSELFINDER
SHIP TRACKING SYSTEM:
Worldwide coverage
Android and iOs applicaiont
Users may search ships by Name, IMO number,
MMSI. It is really easy for the users to enter the
vessel details in the search bar and find the desired
information.
There is detailed information in the VesselFinder
database for over 150k vessels such as: name, IMO,
MMSI, ship type, destination, master data, port
calls. Following the link, you will see detailed ship
info for container ship CMA CGM Wagner.
For all the vessels, users can find the ship
positions, track and history.

Latest marine news about incidents,
pirates, finance, new vessels, ports,
and many other curious events.
With the VesselFinder’s port database
users can check for any arriving and
departuring vessel
There is also a gallery with vessel
photographs.
VesselFinder is very friendly looking,
with really simple design and easy for
using.
Continuously expanding coverage for
ports and vessels.

MASS and IALA standards
Committ
ee
Section to develop in the Guideline
ENAV • General
• Communication
• Data transfer standards
• Cyber Security
VTS • VTS interraction with MASS
• Safe and efficient operations
ARM • Management
• Portrayl
• Spatial Awareness
• Interaction with manned vessels
• Risk Management & Assessment
ENG • PNT
• Position augmentation
• Power availability
• Conventional AtoN visibility to MASS
LAP • Legal aspect

Smart Ports
• Maasvlakte2 terminal in
the Port of Rotterdam
• Unmanned electric AGVs
• Remote operated
unmanned cranes

Primary data sources
ENCs, Paper,
Shoreline, etc.
Bathymetry Tides, Currents,
SVPs
Portal
Apps
Desktop
APIs
Online
Management, Production and Publishing
Sharing and Collaboration (Hybrid)
Internal External
From Production to a
Dissemination Strategy

NOAA PORTS: Physical Oceanographic Real-Time System
https://arcg.is/1v14Dn

Ecological Marine Units (EMUs)

HOs have the opportunity to play a key role

They all come together for the future of Maritime…
…and the future is here

While real-time data on goods in transit will allow a
better overview – where a given package or container is
at what time, what goods it contains, its condition, has it
been tampered with – yet these large volumes of precise
data could also be exposed to cyber-attacks and
accidental data leakage.
Container ships reliant on digital navigation systems
could potentially be manipulated to go off course or even
run aground.
Alongside cyber and property risks, exposures include
liability, business interruption and extortion.
Whether caused by criminal intent or by accident, a
single system failure can have extremely far-reaching
consequences in an interconnected digital environment.

It will become more important than ever
for insurers to dedicate resources to risk
management as well as to understand and
model accumulation risks.
In addition, active loss prevention
focusing on digitalisation in marine
insurance will take on a greater role.
Shipping and logistics companies, software
and hardware manufacturers as well as
insurers will need to work together to
ensure maximum data security.

Marine liability issues can be expected to
become considerably more complex. Especially
in shipping through different national waters
and jurisdictions. Reliance on technology and
software also raises questions
who is responsible for a given failure or
accident? The prospect of unmanned operation
further complicates the matter. Here again, the
risks are moving targets and the insurance
industry must follow the technological
developments and legal decisions closely.
Knowledge gathered in other lines of
business, specifically cyber risks, can and must
be applied in the marine sphere.

CYBER CRIMES
AND SHIPPING
INDUSTRY

Savvy criminals around the globe are exploiting
cyber vulnerabilities to perpetrate a wide range of
crimes from longstanding physical ship-related
dangers like piracy and smuggling to more recent
financial-related frauds like the diversion of
payments.
The challenge for ship owners is even more
complex because cyber criminals are targeting
diverse facets of the shipping industry. For
example, there was a well-documented case of drug
smugglers subverting an IT system at a major port
in order to facilitate the smuggling of contraband in
containers.
The rise of targeted piracy and drug smuggling
reflects how criminal organizations have become
more sophisticated. They will seek detailed
intelligence on potential targets and will use
modern technology to source information and data
to assist in their planning and execution of criminal

While shipping and logistics companies are expert at
maritime transport, they may not have the same experience
with IT security. It will be essential to invest time, effort and
capital into security measures to ensure these cyber risks are
appropriately managed. Companies leave themselves open to
great danger when they do not take into account all the
potential risks and loopholes when designing and
implementing their company-wide cyber security strategy.
Modern maritime ships are considered a privileged target for
hackers and pirates that are increasing their pressure on the
Maritime Shipping Industry.
Modern maritime ships are often monitored and controlled
remotely from shore-based facilities thousands of miles away
to ensure efficiency. This creates a new platform for hackers
and pirates to conduct targeted cyber attacks on ships

5.1RISKS POSED BY TECHNOLOGY
Over the past five decades, computer
controls have been integrated into
innumerable operational and business
processes across diverse industries,
including the shipping industry,
resulting in considerable
improvements in safety, accuracy and
profitability. There is another side to
the digital revolution, however. In the
absence of appropriate protection and
loss prevention measures, the
increased reliance on technology for
even the most basic operations can

Cyber security threats today are increasing
in variety, frequency and sophistication — be
it from a Trojan USB stick that introduces
malware aimed at acquiring sensitive
commercial information… an email with
detailed vessel itineraries sent to a large
group of unknown people… the full-scale
subverting of a company’s IT system… or the
potential compromising of the Automatic
Identification System (AIS) and Electronic
Chart Display and Information System
(ECDIS) on board ships. The number of
potential risk scenarios is significant and
keeps growing. Fraudsters employ whatever
hacking technology works, often tailored to
specific targets of opportunity.

Some organizations may be more at risk
than others depending on the type and
value of data they store. However,
experience has shown that hackers will
generally gravitate toward the low-
hanging fruit of victim networks that are
more easily breached. As such, it is
essential that companies prepare for and
expeditiously address identified
vulnerabilities.

Cyber threats in the shipping industry
can be divided into five major types,
Threats to
Ships and safe navigation
Satellite communication
Cargo tracking systems
Marine Radar systems
Automatic Identification systems

 5.2 RISKS POSED BY INSIDERS
, CARELESSNESS OR
INTENTIONAL?

5.4 HOW TO GUARD
AGAINST THE RISK
There are warning signs that an employee
might be committing cyber crime. Some of
these signs include working odd hours without
authorization; disregarding company policies
about installing personal software or hardware;
taking short trips to foreign countries for
unexplained reasons; buying things they can’t
afford; and taking proprietary or other
information home in hard copy form and/or on
thumb drives, computer disks or email.

However, you can’t let your guard down
when an employee leaves the company,
voluntarily or involuntarily. Strict
termination procedures should be in place
to ensure that all network access privileges
are terminated immediately.
Likewise, just as a company employs
security guards to monitor the parameter
of a building, to check IDs, to log who
enters and leaves, to watch security
monitors, or to implement the ISPS Code
regulations on board a vessel, the same
precautions should be taken for data.

For example, if an employee is
logged in from her work
computer and the same
credentials are used to log in
from an external location, a red
flag should immediately appear.
Similarly, if an employee is
uploading or downloading a large
amount of data for the first time,
those responsible for data
security should be alerted.

5.5 OTHER SECURITY
RECOMMENDATIONS
INCLUDE:
1. Educate staff about the need
for IT and information
security. Develop guidelines for the
use of email and safe custody of
sensitive information. Consider
who actually needs to be copied in
to emails and who should have
vessel itineraries. Also, where
possible, avoid sending messages
to third party “group email”

2. Establish clear guidelines
on the custody of key
information. Pirates and
smugglers often appear to
act on the basis of precise
information as to vessel
movements and cargo on
board.

3. Integrate elements of
both physical and logic
security to protect your
data. These should also be
fully integrated into
business continuity/disaster
recovery plans and regular
staff training.

4. Secure your supply
chain. Suppliers and contractors
are a risk because often, they have
intimate knowledge of your
operations as well as access to key
information systems. Alternatively,
they can unwittingly introduce
malware where their systems
intersect with yours.

5. Establish the extent of insurance
required so that your business has
specific cyber coverage if
required. This may include cover for
business interruption and increased
costs incurred as a result of any cyber
crime event. The use of a third party
insurer is one way to mitigate against
the financial impact of cyber crime.

6. Conduct a cyber-risk
assessment. Engage a qualified expert
to conduct penetration testing and a
thorough review of security protocols to
determine what kind of data you hold;
where that data is and where it goes;
and what processes are utilized and
why. Of the hundreds of such risk
assessments Kroll has conducted, there
has never been one in which security
measures could not be improved.

7. Establish continuous digital
monitoring so that your
information technology staff
— in conjunction with your teams
in legal, operations, marketing,
finance, etc. — will know what is
going on in your networks at all
times. In the event your system is
compromised, this will help isolate
exactly what happened and when,
which in turn will aid in recovery
efforts.

8. Work with partners who have
knowledge of the risk
landscape. It is not enough to
take all precautions for current
risks; you must also keep up with
emerging threats and situations.
While you might consider hiring
dedicated staff to monitor
emerging threats, this can prove
not only costly, but also
ineffective simply because these
resources tend to get
compartmentalized or “silo-ed,”

9. Integrate data security/cyber
risk with cyber policies and breach
response and preparedness
plans. The simple fact is that no
one is immune to an attack.
Unfortunately, without a
preparedness plan, decisions can
be made that inadvertently
compromise evidence and make
your job immeasurably harder
when trying to resolve matters.
These plans should be constantly
evolving and rigorously tested.

10. Be actively involved with
local law enforcement. This
will give your IT team and
management an opportunity to
engage with law enforcement
outside of an event and learn
more about current and
emerging risks as well as best
practices to combat them.

8. WORLDWIDE VESSEL
TRACHING BY VESSEL
FINDER

industrial processes all over the world. It
also transformed shipping and logistics
Huge increase in efficiency, security and
energy savings fueled the transformation.
And the same time cyber security risks
became an issue.
With the emergence of big data and
increasingly interconnected technologies, a
second digital revolution is taking shape.
Shipping and logistics are benefiting from
these developments.
CONCLUSION
Digital technologies continue to transform

Conclusion
The potential of artificial intelligence is hard to ignore. The number of successful case
studies and examples will continue to grow as we look toward the future, for the integration
of AI in the shipping industry.
Artificial intelligence can deliver considerable benefits to the supply chain and shipping
operations. Some advantages include reduced cost, less risk, improved forecasting, faster
deliveries through more optimized routes, and more.
Digital change has its benefits for the port, supply chain, customer, and environment. The
ability to move swiftly between various cargoes is also essential. Selecting the right coating
extends the range of cargoes, reduces the time needed to switch them, and delivers the
highest return on investment (ROI)
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