1
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Smart Ship Applications
13th October 2016
Hideyuki Ando
MTI
(Monohakobi Technology Institute, NYK Group)
The Maritime CIO Forum Singapore - The future of iShipping -
2
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Outline
1. IoT and Big data in shipping
2. NYK activities on IoT and Big data
3. IoT open platform for marine industry
4. Concluding remarks
3
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Outline
1. IoT and Big data in shipping
2. NYK activities on IoT and Big data
3. IoT open platform for marine industry
4. Concluding remarks
4
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Machinery
IoT (Internet of Things)
“Operation Technology (OT)” and “Information Technology (IT)” are to be bridged.
The era of “transparency” where user can access field data.
Automation
PLC*
Sensor Actuator
IP Network IP/Ethernet
Serial, Serial Bus, Analog
Operation Technology (OT) Information Technology (IT)
Serial, Serial Bus IP connected computer
* PLC: Programmable Logic Controller
5
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Coming IoT applications in marine industry
Target
• Prevent unpredicted downtime (owner)
• Reduce maintenance cost (owner)
• Energy efficiency in operation (operator)
Measure
• Condition monitoring
• Big data analysis
• Support service engineer
• Intelligent machinery – Self diagnostics
Change way of working
6
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Digital Twin - An approach of Product Lifecycle Management(PLM) -
Reference) http://www.gereports.com/post/119300678660/wind-in-the-cloud-how-the-digital-wind-farm-will/
Real Space
(Product, Plant…)
Virtual Space
(3D model, simulation)
IoT data
Information
7
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Big data in shipping
Examples of Big data in shipping
Voyage data
• Automatically collected data (IoT)
• Noon report
Machinery data
• Automatically collected data (IoT)
• Manual report data
• Maintenance data
AIS data
• Satellite AIS / shore AIS
Weather data
• Forecast / past statistics
Business data
• Container transport data
8
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
IoT and Big data application areas
Role Function Example of Big data application
Ship owner
Technical management
• Safety operation • Condition monitoring & maintenance • Environmental regulation compliance • Hull & propeller cleaning • Retrofit & modification
New building • Design optimization
Ship operator
Operation • Energy saving operation • Safe operation • Schedule management
Fleet planning • Fleet allocation • Service planning • Chartering
Other partners in value chains, such as cargo owners, shipyards, equipment manufacturers, and class societies, have also interests in ship IoT and Big data.
9
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Outline
1. IoT and Big data in shipping
2. NYK activities on IoT and Big data
3. IoT open platform for marine industry
4. Concluding remarks
10
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
IoT platform in NYK SIMS (Ship Information Management System)
Data Center
SIMS IoT data
+ SPAS manual data
VDR
Integrated Automation
System
Shore Dashboard
- For operation
- For ship manager
• Main Engine
• Power plant
• Cargo control
• Auxiliary machineries
• GPS
• Doppler log
• Anemometer
• Gyro Compass
Sat Com (VSAT, FBB)
<Navigation Bridge>
<Engine Room & Cargo>
Onboard dashboard
Motion sensor
SIMS Monitoring & Analysis at Shore
Operation Center (Tokyo, Singapore …)
Technical Analysis (NYK, MTI)
Performance Analysis
- Long term analysis
- In service performance
SIMS Data Collection Onboard
Analysis SIMS unit
Data Acquisition and Processing
11
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
@ engine rev. 55rpm
<Calm sea performance>
speed:
FOC:
<Performance in the rough sea(BF8)>
speed:
FOC:
Ship performance – key technology for analysis
6000TEU Container Ship
Wave height 5.5m, Wind speed 20m/s
BF scale 8, Head sea
8 knot
60 ton/day
Effecting factors 1. Weather (wind, wave and current), 2. Ship design (hull, propeller, engine), 3. Ship condition (draft, trim, cleanness of hull and propeller, aging effect)
14 knot
45 ton/day
12
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
In-service ship performance
<Target vessel> 6000TEU Container Draft 12m even
0deg (wind, wave) – head sea
ビューフォート階級
風速(m/s)
波高(m)
波周期(sec)
BF0 0.0 0.0 0.0BF3 4.5 0.6 3.0BF4 6.8 1.0 3.9BF5 9.4 2.0 5.5BF6 12.4 3.0 6.7BF7 15.6 4.0 7.7BF8 19.0 5.5 9.1BF9 22.7 7.0 10.2
Sea condition
Beaufort scale wind speed wave height wave period
13
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Ship performance model in service
• Digital Twin of ship performance in-service
• Performances under all possible conditions (draft, trim, wind and wave)
• IoT data are used for correction of the model.
14
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Optimum weather routing with performance monitoring
Weather Routing(PLAN)
• Voyage plan
+ course, speed, RPM, FOC, weather
+ ship performance model
Monitoring(CHECK)
• Voyage actual
+ actual speed – RPM, RPM - FOC
+ actual weather Feedback
Ship model and weather forecast are inherently include errors.
But feedback loop by monitoring can make this system work better.
15
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Performance analysis - long term analysis -
Performance analysis
Semi-automate the long
term analysis process
Pick-up target vessels
Visualize performance drops
of fleet vessels after last dry
dock
Cleaning hull & propeller
Expand service available
ports
Hull & propeller Cleaning
Service Provider
Performance Management
Operation Management
16
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Operation optimization
Voyage simulation with past weather data
Estimation of - Sea margin - FOC and etc.
Ship performance model
Service route
Combine ship performance model with weather data to optimize ship services
17
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Energy saving hull modification
Operation profile
23 % CO2 reduction was confirmed
Energy saving modification
• Bulbous bow modification • Install energy saving device (MT-FAST) • Etc.
• Speed, RPM, Power • Draft, trim, displacement • Weather • Sea margin • Etc.
18
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Prognostics and health monitoring in shipping
Target
• Prevent unpredicted downtime
• Reduce maintenance cost
• Predict remaining useful life
Measure
• SCADA data analysis
• Condition monitoring by additional sensors
• Big data analysis
T State T T T T T F F
Observation data data data data data data data data
time
…
true fault
Ship main engine
Estimate true state from observed data KIRARI NINJA 360-degree panoramic camera to take photos inside the dark combustion chamber
19
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Outline
1. IoT and Big data in shipping
2. NYK activities on IoT and Big data
3. IoT open platform for marine industry
4. Concluding remarks
20
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Ship IoT
• Combination of IoT platform and marine domain knowledge are necessary
• Collaborations with industry partners are important to make practical solutions
IoT platform
Marine domain knowledge
Ship IoT
platform application services
21
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Concept of Ship – Shore Open Platform for Ship IoT
LAN
Ship Shore
broadband
Se
cu
rity
/ a
cce
ss c
on
tro
l
User
request
Software
agent
data
Data center (operated by
neutral bodies)
Ship owner
Ship
Management
company
Shipyard
Performance monitoring
Service Provider
Energy management
Onboard application
• Weather routing • Performance
monitoring • Engine
maintenance • Plant operation
optimization
Weather routing
Data Center
Ship operator
M/E
D/G
Boiler
T/G…
VDR
Radar
ECDIS
BMS
….
Engine maker
Engine monitoring
Asia
Ship
equipment
maker
Remote maintenance
Se
cu
rity
/ a
cce
ss c
on
tro
l
Europe
Marketing and
Big data analytics
Cargo
crane
.
.
.
Class Society
Onboard
data
server
Open IoT platform (Industry standard)
Application / services (Competition)
22
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Standardization activities of Ship IoT platform (SSAP2: Smart Ship Application Platform 2 Project by JSMEA)
VDR
Engine D/L
IAS
…
Machinery & Equipment
Ship LAN
Broadband Fleet management
Shore Ship
Own application
Performance
Performance
3rd party application
Condition monitoring
Fleet management
Performance
Weather routing
Own application
3rd party application
Remote diagnostics
Ship Data
Center
Ship – shore open platform
Operator
Cargo owner
Owner
User
Class
Manufacturer
Shipyard
…
Ship manageme
nt
Onboard data
server (standardized)
Proposal of new ISO regarding Ship IoT • ISO/CD19847 - Shipboard data servers to share field data on the sea
• Specifications of ship onboard data server
• ISO/CD19848 - Standard data for machinery and equipment part of ship • Specifications of dictionary and format
Onboard data
server (standardized)
JSMEA: Japan Ship Machinery and Equipment Association
23
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
SSAP2
Process for ISO (ISO CD19847, ISO CD19848) *
• ISO PWI 19847/19848 were accepted as NP in Aug 2015
• The first ISO/TC8/SC6/WG16 meeting was held in June 2016 in Tokyo
• 2 CDs will be distributed soon for comment and voting to the P-members of ISO/TC8/SC6
NP
WD
CD
DIS
FDIS
IS
2016
2017
2018 Aug 2018 Final dead line
2015
Aug 2015 Registered as NP
Now
Dec 2017 Fastest path
・NP: New work item Proposal, WD: Working Draft ・CD: Committee Draft, DIS: Draft International Standard ・FDIS: Final Draft International Standard, IS: International Standard
24
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Expected activities on ship IoT and open platform
Role Activities on Ship IoT and open platform
Shipping Ship owner and operator needs applications for energy saving, minimize downtime, safety transport and environmental conservation
Manufacturer Remote diagnosis, preventive maintenance and self diagnostics
Shipyard Data analysis services for ship owners, life-cycle support and feedback to new design
Service provider Fleet management system, big data analysis services, condition monitoring services and IoT platform
Academy Research on big data analysis, numerical simulation methods and digital twin. Education and trainings.
Class society Shore data center. Class inspection
Government … utilization for e-navigation and MRV
25
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Examples of ship IoT projects in NYK
Collision avoidance and autonomous ship
Simulation of LNG cargo transport
Cargo crane condition monitoring
i-Shipping: Japanese government funding projects
Ship IoT for safety (2016-2020)
Damage prevention of engine-power plant
Propulsive efficiency monitoring
Multi-layered Doppler log
Structural Health Monitoring
i
i
i
i
i
26
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Outline
1. IoT and Big data in shipping
2. NYK activities on IoT and Big data
3. IoT open platform for marine industry
4. Concluding remarks
27
Monohakobi Technology Institute
@ Copyright 2016 Monohakobi Technology Institute
Concluding remarks
In the coming era of ship intelligence, we need open collaborations to pursue wide variety of possibilities to improve all aspects of safety and efficiency in shipping