Extending intelligent monitoring of onboard machinery

9 September 2020 • 09:00-09:45 BST

Presentation documents:Page 2: Pankaj Sharma, Columbia Shipmanagement Page 9: Capt K.K. Mukherjee, NYK Bulkship (Asia) Page 17: Dr. Ranjan Varghese, Steel Ships

Vessel Optimisation Webinar Week

Part of

7-9 September 2020

OPTIMISE PERFORMANCEREDUCE COSTINCREASE EARNINGS

Artificial intelligence for predictive maintenance

Real-time analytics and improved performance

Pankaj Sharma

Artificial Intelligence for predictive maintenanceModernization Project: Fully connected Yacht

Problems• Lack of existing sensors and integration

• Lagging in Digitalization curve

• High Risk of losses due to hotel equipment failure

Application• Hybrid approach to Digitalization

• Layering of information with new generation IOT sensors

• AI application for predicting trends

Artificial Intelligence for predictive maintenanceVibration sensors & Predictive maintenance

Artificial Intelligence for predictive maintenanceValue delivered: Breakdown averted

• Machine learning AI application was able to create thresholds by benchmarking all 4 AC units• In a very short period angular alignment issue was identified with a potential for motor break down in

future• Timely intervention and alignment check avoided a major breakdown

Real-time analytics and improved performanceValue of monitoring by experts

Issues and Actions list by monitoring analysts (Example)

Ref Boiler Pump II: The Vessel Engineer should investigate the possiblestiffening of the mounting structure of boiler pump II in the horizontal direction to avoid fatigue and potential damage to the mounting structure.

AC Compressors Root Cause investigation: Stop and lock out the compressor after it finished its running cycle. While still at operating temperature,remove the coupling cover and carry out a laser alignment as per laser system instructions. Align motor and compressor. If the motor/compressormounting plate is bowed it will require shimming of both the motor and the compressor feet

Update turbocharger, engine and generator alarm limits based on latest measuring results: New frequency ranges have also been defined, and measurements taken in the background. The dashboards will be updatedwith the revised Alarm limits accordingly.

‘3 P’ of Performance management at Columbia

Platform ProcessPeople

• Expert operators working in a 24/7 environment

• Robust processes key for End to End optimization

• AI capable State of the art system for monitoring

COLUMBIASHIPMANAGEMENTPOCR

Limassol Hamburg

Singapore Shanghai

For information or enquires:

CRManager@csmcy.com

columbia-shipmanagement.com

Extending intelligent monitoring of onboard machinery

Digitalization

Remote Access

Data Exchange

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Extending intelligent monitoring of onboard machinery

Digital Ship, Autonomous Ship, Digital Twin…

Surveys, Inspection , RBI , Maintenance , Training …..

Big data transfer , analytical operation

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Extending intelligent monitoring of onboard machinery

Digitally connecting Shipboard equipment’s, machineries …....

Operational efficiencies, monitoring technology , transition to predictive maintenance -DHM , Inventory control …….

Associated Cost benefit , Reduction of failures , breakdown …Risks: Cyber , Quality of data …..

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Extending intelligent monitoring of onboard machinery

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Extending intelligent monitoring of onboard machinery

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Currently most common remote monitoring : ME , DG , Boilers, Scrubber systems, SCR, VDR , Nav Equipment's

Early Warning / Alarm/Alert Measure , Monitor to Manage

Futures • Strategies used now Augmented Virtual

Reality/Digital Twin which in turn used for:• Training of personnel before they arrive to

the vessel• Ease maintenance activities • Identifying trends of problems • Asset Management • Documentation , record keeping and

maintenance activities• Provide evidence of the ships history of

repair & maintenance over life cycle • Identify potentials areas, systems that need

improvements etc.

• Implementation of various modes of Autonomous shipping

Extending intelligent monitoring of onboard machinery

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Monitoring the ME parameters , FO, Cyl Oil consumption & etc (Sample)

Extending intelligent monitoring of onboard machinery

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Monitoring the running , consumption &load sharing of Diesel Generator(Sample)

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This email will be forwarded to vessel manager in the below format if there is any abnormality with the system –Sample Exh. Temp High

Extending intelligent monitoring of onboard

machinery

by Dr. Ranjan Varghese, Chief Executive Officer,

Steel Ships Limited Hong Kong

DEVELOP, DEPLOY AND TEST A PREDICTIVE COGNITIVE MAINTENANCE DECISION SUPPORT SYSTEM

EMBRACING TECHNOLOGY IN PANDEMIC ACCELERATES THE NEED TO

EMBRACE NEW TECHNOLOGY

Objective Targets

▪ Increase availability and

maintainability by 15%

▪ Reaching 30% of time spent on

predictive maintenance

▪ Reduce failure-related accidents by

30%

▪ Reduce energy consumption by 6-10%

▪ Reduce spares consumption by 7-15%

Responsible with Health Safety and Environment Management

Purpose • Identify and localize d and

assess damage severity• Predict damage evolution• Lifecycle Cost reduction• Preventive maintenance

actions• Optimize maintainability• Increase in-service

efficiency of machines by at least 10%

• Effectively information sharing between users

3© Steel Ships 2020

COGNITIVE ANALYTICS AND DATA SHARE BENEFICIARIES

A SHIP OWNERS PERSPECTIVE

Responsible with Health Safety and Environment Management

Ship Owner

Data Processing

Makers/ Manufactures of

Machineries

Classification society

Ship Management

Charterers

Local Agents

Shipboard Engineers

4© Steel Ships 2020

SensorizationSoftware and

systemsPredictive

Competitive

advantage

COGNITIVE ARTIFICIAL INTELLIGENCE ARCHITECTURE –WITH MULTIPLE CIRCUITS

5© Steel Ships 2020

OVERLAY OF TYPICAL VESSEL PROCESS OIL POLLUTION RISKY OPERATION CASE

Noise

Vibration

Temp

Change

Over Sludge Tank

To

Sea

To

Atm

Manual

Attendance

RestrictedAreas-GPS

Triggered Fuel/ Lube oil Purifiers

Oily Water Separator

Incinerator

Gravity Separated Water

Heated Oil Sludge Pumped

Manual

Attendance

Manual

Attendance

Manual

Attendance

6© Steel Ships 2020 6© Steel Ships 2020

PREDICTIVE / PREVENTIVE COGNITIVE MAINTENANCE SYSTEM INTEGRATION AND TESTS – MACHINE LEARNING

Mathematics

Responsible with Health Safety and Environment Management

Predictive Maintenance Algorithms

Sensing platform

Information Visualization

Augmented reality to support maintenance

Process control (automated actions)

- Genetic Algorithm + Data Structures =

Evolutionary Programs

- Genetic Programming

- Heuristics

- Guardian Architectures

- Combinatorial Optimisation

- Neural Networks

7© Steel Ships 2020 7© Steel Ships. 2020

+Thank YouONLY SAFE OPERATION

MAKES FINANCIAL SENSE

Steel Ships Limited

Hong Kong

info@steel-ships.com