1. Monohakobi Technology Institute How ICT Can Assist Energy Efficient Fleet Operations -How Broadband Changes Quality of Weather Routing Digital Ship Singapore 22-23, May, 2012 Ryo Kakuta Technical Strategy Group, MTI (Monohakobi Technology Institute) R&D company of NYK Line

2. Monohakobi Technology Institute Outline Background Energy Efficient Fleet Operations Optimum Weather Routing Weather Routing and Monitoring Improvement of Weather Routing by Broadband Next Challenge 2

3. Monohakobi Technology Institute Background

4. Monohakobi Technology Institute Save bunker activities in shipping company According to increased cost of bunker, shipping companies have applied operational and technical measures for fuel savings – Slow steaming – Weather routing – Propeller cleaning – Energy saving devices Cost benefit and emission reduction by slow steaming e.g. 8,000 TEU container Ship speed24 knot20 knot M/E fuel consumption 225 ton/day130 ton/day M/E fuel cost (@ 600 USD/MT) 134,800 USD/day78,000 USD/day CO2 emission696 ton/day403 ton/day Slow steaming - 42 % - 16 % 4

5. Monohakobi Technology Institute Performance monitoring - compare total fuel consumption Same ship size and same voyage – but total amounts of fuel consumption largely differ More than 30 % difference 5

6. Monohakobi Technology Institute SEEMP - PDCA management for energy efficiency SEEMP (Ship Energy Efficiency Management Plan) – MEPC 62 adopted revisions of MARPOL Annex VI introducing EEDI and SEEMP Entry into force date: 1 January 2013 Operational measures slow steaming weather routing hull and propeller maintenance …. PlanDoDoCheckAct Continuous monitoring & improvement 6 Importance of Energy Efficient Operation is increasing

7. Monohakobi Technology Institute Energy Efficient Fleet Operations

8. Monohakobi Technology Institute Fleet operation Snapshot from NYK e-Missions’ NYK fleet: about 800 vessels now Best balance of safety, economy and environment – No cargo and ship damage – Keep schedule – Maximize charter base (minimize cost) – Minimize emissions 8 Multi-objective optimization

9. Monohakobi Technology Institute Management for energy efficient operation - Needs all related parties participation Do - navigation Check – monitoring Plan – routing PDCA cycle for improvement To encourage all participants efforts for energy efficient operation by sharing information, good communication and right scheme 9 Act – corrective action

10. Monohakobi Technology Institute Challenge to Optimize Fleet Operation in NYK 10 Figure from “More Than Shipping 2013” Monitoring Weather Routing Broadband Real-time Operation Concept to Realization!

11. Monohakobi Technology Institute 11 Introduction of Onboard Broadband on NYK Fleet - Improve Infrastructure Reducing CO2 emissions by introducing onboard broadband

12. Monohakobi Technology Institute IBIS (Innovative Bunker and Idle-time Saving) PJ - Effective Utilization of Broadband Sharing Information including weather, sea forecasts, sea-current, and ship-operation data between land and ships in real time.

13. Monohakobi Technology Institute Optimum Weather Routing

14. Monohakobi Technology Institute Optimum Weather Routing Role of weather routing – (past) Avoiding severe weather – (now) Optimum weather routing Best balance of Safety Schedule keep Economy Environment Necessary technology for optimum weather routing – Ship performance model RPM – speed – fuel consumption – Ship motion and performance in severe weather Way points Routes and weather 14

15. Monohakobi Technology Institute 15 Optimum Weather Routing -Necessity of Ship Performance Model “Courtesy of WNI”

16. Monohakobi Technology Institute Weather Routing and Monitoring

17. Monohakobi Technology Institute Integration of Weather Routing with Monitoring Weather Routing （ PLAN ） Voyage plan + weather forecast + ship performance model + ship motion model Performance Monitoring （ CHECK ） Actual voyage + actual weather + ship performance data + ship motion data Feedback Ship model and weather forecast inherently include errors. Feedback loop with monitoring can make this system work better. 17

18. Monohakobi Technology Institute Example Implementation of Data Collection box Onboard Requirements Interface to onboard equipment, such as engine D/L, GPS, anemometer, flow meter and etc. High reliability … 24 hrs, 365 days work without maintenance Lower cost of implementation Flexibility of customization Flow meter FUELNAVI 18

19. Monohakobi Technology Institute Engine Data Logger GPS (speed, course) NMEA Doppler log (speed) NMEA Gyro compass (heading) NMEA Anemometer (rel. wind) NMEA RPM 4-20 mA F.O. flow meter pulse S.H.P 4-20 mA Master clock pulse F.O. temperature 4-20 mA Sea water temp. 4-20 mA E/R temp. 4-20 mA serial / LAN GOT monitor -Fuel consumption monitor serial / LAN Ship’s LAN Inmarsat-FBB or VSAT Motion Sensor serial FUELNAVI Schematic Diagram Bridge E/C Box Computer (MOXA) -data storage -data transfer FuelNavi (PLC: Mitsubishi MELSEC-Q) -Data processing -Calculate statistics SIMS junction box serial 19

20. Monohakobi Technology Institute SIMS Overview (Ship Information Management System) VDR / ECDIS Engine Data Logger Data Acquisition and Processing SIMS Viewer -Trend monitoring of speed, M/E RPM, fuel consumption and other conditions per hour - Comparing planned schedules and actual schedules Main Engine FO flow meter Torque meter GPS Doppler log Anemometer Gyro Compass Inmarsat-F/FB Viewer Motion sensor Data Center SIMS Monitoring & Analysis System at Shore Operation Center Singapore, …. Technical Analysis (MTI) Voyage Analysis Report Break down analysis of fuel consumption for each voyage Feedback to captains SIMS Data Collection System Onboard Report SIMS auto logging data (per hour) & SPAS electronic abstract logbook data (per day) Communications via Technical Management FuelNavi 20 Weather routing service provider

21. Monohakobi Technology Institute Optimum Weather Routing Performance Model Weather Forecast Voyage Planning Noon Report RPM Speed 2.Model Calibration SIMS Data 1.Model Improvement RPM Speed Calibrate Model based on Actual data Good Performance Model based on actual and detail data SIMS Data COmmunication SIMS Data Noon Rpt. Before Model After Ajustment Real Data 4.Evaluation Feedback to Weather Routing Feedback 3.Monitoring Monitoring Gap between Actual and plan SIMS Data Weather Routing Vessel Operation Communication L 78 rpm 82 rpm Route and RPM 82 rpm Recommendation After Departure Pre Voyage During Navigation Post Voyage SIMS Data Integrating Optimum Weather Routing with SIMS

22. Monohakobi Technology Institute RPM Model – Actual [mt/24h] FOC [mt/24h] Frequency Container Ship Sample Standard deviation reduces from 9.3[mt/24h] to 5.4[mt/24h]. Estimation accuracy improves about 40%. Zero error peak enhancement shows accuracy improvement. σ(old) = 9.3[mt/24h] σ(new) = 5.4[mt/24h] 22 Performance Model Correction(Pre-voyage) “Courtesy of WNI”

23. Monohakobi Technology Institute Improvement of Weather Routing by Broadband

24. Monohakobi Technology Institute Improvement of Weather Routing by Broadband rpm speed Calibration model Calibrated model actual Maritime broadband (FBB, VSAT) Revise schedule by real- time information 15 days forecast1/12 resolution current Voyage simulation onboard vessel Captain and engineer at shore Recommend RPM Actual RPM Recommend speed Feedback to ship performance model Full time connection Large data size transfer Voyage simulation shore Feedback actual weather Actual sea state Actual wind & ship motion 24

25. Monohakobi Technology Institute Rich Weather Content by Fleet Broadband 25 NarrowbandBroadband Frequency2 times/day4 times/day Forecast Range10days15days Grid Size (Current)1/2 degree1/32 degree Current (1/2 degree) Hi-Resolution Current (1/32 degree) “Courtesy of WNI”

26. Monohakobi Technology Institute 26 Error Monitoring Error Minimization Error from Ab-Log analysis or Past performance ● Reported FOC ● Simulated FOC(WNI) ● Reported FOC ● Simulated FOC(WNI) Semi-auto Calibration Vessel Performance DBVoyage Plan Voyage Records Simulation Setting based on the similar voyage recodes Error becomes small About 5mt under- estimation All of data within ±2.5mt difference This process can be applied for BROB-difference or M/E FOC. Estimation of total FOC is improved. Underway process Real-time Performance Model Correction “Courtesy of WNI”

27. Monohakobi Technology Institute Next Challenge

28. Monohakobi Technology Institute Further Improvement Uncertainties Weather Forecast Ship PerformanceShip Motion Continuous effort is required for reducing uncertainties in weather routing -Reducing gap between estimate and actual - Monitoring and feedback Uncertainties

29. Monohakobi Technology Institute Compare Estimated Ship Performance with Actual Comparison Actual Estimate Ship Performance Model Actual Performance and Weather Weather Forecast Wave Height Meter Measuring actual wave height remains a challenge.

30. Monohakobi Technology Institute Compare Optimum Trim Estimation with Actual 30 Optimum trim estimation (reasoning by model test, simulation) Trim trial with performance monitoring Comparison The relation of propulsive performance and trim are physically complex problem.

31. Monohakobi Technology Institute Compare Estimated Ship Motion with Actual ship motion simulation actual ship motion and acceleration cargo securing & ship structural safety criteria 31 [sec]

32. Monohakobi Technology Institute Expectation on Broadband Estimation Monitoring Feedback Weather Routing Enhancement of monitoring plays a key roll to improve weather routing. Installation of broadband will accelerate the cycle of improvement. Improvement Ship performance, ship motion, draft and trim, wave height,,,,,,,,,,,,,,

33. Monohakobi Technology Institute Concluding remarks NYK aims to optimize fleet operation by integrating weather routing, monitoring and broadband Installation of broadband enables sending rich weather content to vessels and real-time weather routing For reducing uncertainties in weather routing, the cycle of estimation, monitoring and feedback is required Broadband will contribute to acceleration of the cycle 33