Monohakobi
Technology InstituteMaritime Digitalization Summit China 2019

NYK’s Approach
To Maritime Digitalization
26th June 2019

Jungo Shibata
MTI (NYK Group)1@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteOutline
1. Introduction
2. IoT and Big data in Shipping
3. NYK’s Activities for digitalization
4. Open Platform and Standardization
5. Way forward2@ Copyright 2019
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NYK Corporate Profile• NYK LINE (Nippon Yusen Kaisha)• Head Office: Tokyo, Japan• Founded: September 29, 1885
• Business Scope• Liner (Container) Service• Tramp and Specialized Carrier Services• Tankers and Gas Carrier Services• Logistics Service• Terminal and Harbor Transport Services• Air Cargo Transport Service• Cruise Ship Service• Offshore Service

NYK Head Office in Tokyo• Employees: 35,711 (as of the end of March 2019)• Revenues: $ 20.5 billion (Fiscal 2018)

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NYK Fleet (as of the end of March 2019)
Container vessels(including semi-container shipsand others)

63 vessels

118 vessels

Bulk Carriers (Capesize)

Tankers

105 vessels

56 vessels

Bulk Carriers

LNG Carriers(Panamax & Handysize)

194 vessels

75 vessels

Wood-chip Carriers

Others

44 vessels

42 vessels

Cruise Ship

1 vessel

4

Car Carriers

757 vessels( Owned 334 vessels)@ Copyright 2019
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MTI Company Profile•••••••

MTI is “Monohakobi ( = quality transport) Technology Institute”
Established : April 1, 2004
Equity capital : JPY 99 million
Stockholder : NYK Line
Number of employees : 70 (as of end of March, 2019)
Head office : 2-3-2 Marunouchi, Chiyoda-ku, Tokyo, 100-0005, Japan
URL : www.monohakobi.com/en/SINGAPORE BRANCH
1 Harbourfront Place #13-01HarbourFront Tower One
Singapore 098633)

NYK SUPER ECO SHIP 2050
(Emission-free Concept shipfor future)

YOKOHAMA LAB.
(Transportation Environment Lab.)
5-32-84, Sugita, Isogo-ku, Yokohama,Kanagawa, JapanNYK SUPER ECO SHIP 2030
( 69% less CO2 emission Concept ship for future)5@ Copyright 2019
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Smarter ship and operation in NYK/MTI

Now

Future
LNG

OIL

Wind Resistance Reduced
MT-COWLHYDROGEN

Ship(Hardware)Super Eco Ship2050

Super Eco Ship2030
Alternative Marine
PowerMeasurement around propeller

30％ Energy Saving PCTC

Hybrid T/CShin Koho

LNG-Fueled Tugboat
Sakigake

Solar Panel
Auriga Leader

Wind Power Generator
Andromeda Leader

LNG-Fueled PCTC
Delivery in 2016
Innovative
Air Lubrication System
SOYO
Air Lubrication System
YAMATO, YAMATAI

MT-FAST

Hybrid Electric Power Supply
Auriga Leader

Improved
Electronic Controlled Engine
Governor Controller

LNG Bunkering Vessel
Delivery in 2016

Operation(Software)

IBIS Project
Fuel Consumption

MTI Founded

NYK’s own safety andEnvironment standard
NAV9000

Indicator

Prediction ofCurrent

FUELNAVI

Onboard Broadband
NYK SATCOM Project
Integrated Operation
Management System
NYK e-missions’

LiVEOperation Portal Site

ShipDC &IoS-OP

Detection of Mach. Trouble
with monitoring data

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

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Monohakobi Technology InstituteMonohakobi
Technology InstituteOutline
1. Introduction

2. IoT and Big data in Shipping
3. NYK’s Activities for digitalization
4. Open Platform and Standardization
5. Way forward

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What is IoT and big data in shipping
Examples of IoT and bigdata in shipping
Voyage data
• Automatically collected data (IoT)• Noon report
Machinery data
• Automatically collected data (IoT)• Manual report data
• Maintenance data / trouble data
AIS data• Satellite AIS / shore AIS (IoT)
Weather data
• Forecast / past records• Anemometer / wave measurement (IoT)
Business data
• Commercial data
• Market data

8@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteUtilize IoT data in shipping
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• Digital twin

Change way of working !
9@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteMethods of utilizing Big data #1

Identifying issues with deep domain knowledge,
skill of data analytics and Big data
Identified issues

Big data

AnalysisIoT Data

Engineering knowledge
e.g. vessel performance

Optimum operation-

Fuel saving
Reasonably minimized margin

Report data

Support businessdecision-AIS data

Tactical ship/fleet allocation

Safe operation

Any useful data

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Data analytics & IT

Weather data

Operation data

Technical data••••••••ScheduleRouteCB/HBAIS

Performance
Sea trial
Particular
Paint

Market data•••

Bunker cost
Hiring costMarketCommercial data•••

Contract
Fleet plan
Owner info.

@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteMethods of utilizing Big data #2

The process of issue solving with domain knowledge, skillof data analytics and iterative prototyping.
--> It is a collaborative process.

Identify issues
to solve

Choose right data,technology andpartner

Iterative
prototyping &communication

Implement indaily operation

Identify issues
with rich domain
knowledge

Combine domainknowledge &skill of data analytics

Good communication
Between technicians and users

Cooperation withuser dept., IT dept.
and other cooperate dept.

To realize the issue solving process, “Organizational Support” is necessity.

11@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteMethods of utilizing Big data #3

Operate and maintain data managing infrastructure
E.g. Data collection, error handling, data quality and data standardization.

Reference) DNV-GL, STANDARDISATION AS AN ENABLER OF DIGITALISATION IN THE MARITIME INDUSTRY,GROUP TECHNOLOGY & RESEARCH, POSITION PAPER 201712@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteOutline
1. Introduction
2. IoT and Big data in Shipping

3. NYK’s Activities for digitalization
4. Open Platform and Standardization
5. Way forward

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IoT Platform of NYK - Data Acquisition and Visualization Data Acquisition

Data Cleansing

Communication

Data Integration

Visualization
For Operator
For Ship Manager

Onboard Visualization

Database

Other Data

SIMS (Ship Information Management System)

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Monohakobi Technology InstituteMonohakobi
Technology InstituteCase1

Ship performance in service
6000TEU Container Ship
Wave height 5.5m, Wind speed 20m/s
BF scale 8, Head sea @ Trans-Pacific (Oakland, US – Tokyo, JP)@ engine rev. 55rpm<Calm sea performance>
speed:

14 knot

FOC*:

45 ton/day* FOC: Fuel Oil Consumption<Rough sea(BF8) performance>
speed:

8 knotFOC:

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)15@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteCase1

In-service ship performance model<Target vessel>
6000TEU Container
Draft 12m evenWind and wave effectBase line performance

Beaufort scale
ビューフォート階級

wind
speed wave
height wave
period
風速
波高波周期

BF0
BF3
BF4
BF5
BF6
BF7
BF8
BF9(m/s)
0.0
4.5
6.8
9.4
12.4
15.6
19.0
22.7

(m)
0.0
0.6
1.0
2.0
3.0
4.0
5.5
7.0

(sec)
0.0
3.0
3.9
5.5
6.7
7.7
9.1
10.2

FOC [MT]Sea condition

0deg (wind, wave) – head sea

speed [knot]

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Case1

Operation optimization

Ship performance modelService route with past weather

Estimate data

Estimation of- Sea margin- FOC and etc.
Voyage simulation with past weather data

Combine ship performance model with weather data to optimize ship services
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Monohakobi Technology InstituteMonohakobi
Technology InstituteCase2

Improve bad performance ship

23 % CO2 reduction
was confirmed

Operational profile

•
•
•
•
•

Speed, RPM, Power
Draft, trim, displacement
Weather
Sea margin
Etc.

Energy saving modification• Bulbous bow modification• Install energy saving device (MT-FAST)• Etc.

‘Ship IoT data’ will be more used not only for energy efficiency
but also for improving safety18@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteCase3Anomaly detection from IoT data- Find trouble phenomenon in engine & power plants -Case）M/E (Main Engine) No.3 cylinder abnormal exhaust gas temperature
Increase No.3cyl
ext. gas. temp

Crack on Main Engine Exhaust Valve

Crack !

1. Visualize IoT data
2. Analysis with domain experts knowledge(marine engineer) . Accumulate cases.
3. Implement automatic anomaly detection
function by using the accumulated data.
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Case4

Utilizing IoT data for safer operation- Open collaboration with industry partners -i Collision avoidanceand autonomous shipi

Simulation of LNG cargo transport

i Structural Health Monitoringi Damage prevention of engine-power planti20

i-Shipping(Operation): Japanese government
funding R&D projects – IoT for safety (2016-2020)
Joint research with ClassNK@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteOutline
1. Introduction
2. IoT and Big data in Shipping
3. NYK’s Activities for digitalization

4. Open Platform and Standardization
5. Way forward21@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteStandardization activities of Ship IoT platform(SSAP3: Smart Ship Application Platform 3 Project by JSMEA)
Ship – shore open platform

VDR

Own application

User
Owner

OnboardOnboarddata
data
serverserverEngineD/L

Fleet management

Broadband

Operator

Ship
Data
Center(standardized)(standardized)

IAS

Performance

3rd party application

PerformanceOwn application…
Ship LAN

Machinery& Equipment

Performance

Proposal of new ISO regarding Ship IoT•

3rd party application •Shipmanagement

Shipyard

diagnostics
ClassISO 19847 - Shipboard data servers to Remoteshare fielddata on the sea• Specifications of ship onboard data server
Manufactu
rerISO 19848 - Standard data for machinery and equipment part of ship
Condition monitoring•

Specifications of dictionary and format

Weather routing

Ship

Cargo
owner

Fleet management

…

Shore
JSMEA: Japan Ship Machinery and Equipment Association

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Technology InstituteISO19847 - Shipboard data servers to share field data at sea • Requirements for shipboard data servers to collect and share fielddataShipboard data server
Output Function

Output Data

Streaming
Transport
service

IEC61162-450ISO/CD 19848
Format data

Request-ResponseTransport
service

ISO/CD 19848
Format data

File based on
ISO/CD 19848

FileTransport
service

File based on
ISO/CD 19848

Input Data

IEC61162-1/2
Sentence data

Input Function
DataStreaming

Data Streaming

Data Stored

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StoredDatabase@ Copyright 2019
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ISO19848 - Standard data for shipboard machinery and equipment Standardized ID of sensors,common data model & format

http://IMO1234567/MainEngine/Cylinder2FO/In/Temp
http://IMO1234567/MainEngine/Cylinder1/ExhaustGas/Temp

ID of sensors• URL compliant naming scheme• Dictionaries (informative)• JSMEA• DNV-GL

Data model

Unit:℃
Range:0-700
・・・

Unit:℃
Range:0-150
・・・• Data channel list (meta data)• Time series data (data)

Data format• XML with schema definition• JSON/CSV (informative)• CSV (informative)

XML/JSONCSV

XMLTimeSeries
Data

DataChannel
List•

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@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteInternet of Ships (IoS) Open Platform
Roles are defined and each player provides their expertise on the Internet ofShips(IoS) platform. Data governance and business rules have been built by IoS-OP
Consortium under ShipDC.
Solution
User (SU)

Platform
User (PU)PP
Ship owner

Platform
ProviderSP
Ship data center

Ship owner

Solution
ProviderOperator
Operator

Ship management

Operator

Provider ofonboard datacollection
equipment andservices

IoS Open Platform

Data collection,
storage,standardization andprovision
Data integrationfrom other sources

Application
serviceproviderbased on IoTdata of
ShipDC

Ship management

Crew

Data Buyer
Shipyard, manufacturer, weather service, insurance etc.

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Outline1. Introduction
2. IoT and Big data in Shipping
3. NYK’s Activities for digitalization
4. Open Platform and Standardization

5. Way forward

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Way Future - Integrated bridge operation Objective• Prevent collisions• Reduce workloads of crews• Contingency backup
Measure• Integrated bridge system• Enhanced situational awareness• Advanced support system• Manned Autonomous ship

Reference) ULSTEIN BRIDGE CONCEPTInfrastructure & regulation
are very important27@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteManned-Autonomous Ship

Provided by Japan Radio Co. Ltd.

• Advanced support system … additional functions to assist cognitive process ofhuman operator based on existing navigation system

Ref 1)• Autonomous operation under approval of human operator

MannedAutonomousInformation
Acquisition

AnalysisPlanning

Approval

Onboard
Equipment
Seafarer

Onboard
Equipment
Seafarer

Onboard
Equipment
Seafarer

Seafarer

Reference：1) Lloyds Register, “Current and Emerging Cyber Risks facing Maritime Industries”, European Maritime Cyber Risk Management
Conference, London, June 201728

@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology InstituteIntegrated Navigation Support System J-Marine NeCSTNYK/MTI and Japan Radio Co. Ltd. jointly
developed navigation support tool thatenables officers to better manage and sharenavigational information.
(Press Released at 17th May 2017)•••

Gathering all necessary information fornavigation by using IoTIntegrated navigation information
management system
Contribution to safe & efficient navigation<Features of J-Marine NeCST>
1. Handwritten inputs
2. Compatibility with ECDIS
3. Implementation of meteorological andhydrographical forecasts
4. Information sharing with other ships and land
5. Flexible customization

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Cyber Security and Cyber Resilient ShipCyber risk management will need to be implemented.
Protection of Industry Control System is crucial
Cyber security guidelines in shipping•
IMO, MSC (98) – Cyber risk management onboard ships
should be included in SMS as of 1 Jan 2021 (Jun 2017)•
BIMCO – the guidelines on cyber security onboard ships –version 3 (Nov 2018)•
ABS, DNV-GL, LR, BV etc. – Guidelines and notations of cybersecurity onboard ships (2016)•
IEC 61162-460 – Safety and security standards for navigation
and radio communication equipment•IACS Maritime Cyber System Recommendations (MCSR)The Guidelines on Cyber Security
onboard Ships - Version 3, BIMCO – Nov 2018

Cyber security guidelines•NIST Framework and 800-53 – computer security policies,procedures and guidelines•
ISO 27001/2 – ISMS: Information Security ManagementSystemSource) BIMCO
https://www.bimco.org/products/publications/free/cyber-security

30@ Copyright 2019
Monohakobi Technology InstituteMonohakobi
Technology Institute“Ship-Shore data sharing and Cyber Security Platform”
in collaboration with Dualog
1. Realization of secure and efficientdata-sharing platform between ship and shore.
2. Raise of on-board cyber risk management levelthrough ship and shore cooperation

Fig.. Image of the ship-shore data sharing systemSource) NYK LINE( https://www.nyk.com/english/news/2017/20170531_01.html )31@ Copyright 2019
Monohakobi Technology InstituteMonohakobiTechnology InstituteThank you very much for your attention

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