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DNV GL © 2014 20.10.2014 SAFER, SMARTER, GREENER DNV GL © 2014 J.C.Kadal 20.10.2014 Big data in Maritime and Oil and Gas industries 1 The new data reality.

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Presentation on theme: "DNV GL © 2014 20.10.2014 SAFER, SMARTER, GREENER DNV GL © 2014 J.C.Kadal 20.10.2014 Big data in Maritime and Oil and Gas industries 1 The new data reality."— Presentation transcript:

1 DNV GL © 2014 20.10.2014 SAFER, SMARTER, GREENER DNV GL © 2014 J.C.Kadal 20.10.2014 Big data in Maritime and Oil and Gas industries 1 The new data reality and Industry impact

2 DNV GL © 2014 20.10.2014 In a challenging world we make businesses better prepared Reliable and affordable energy Long-term competitiveness Trust and transparency Safe Low carbon energyShort-term cost efficiency Complexity and lack of global governance Efficient and fast 2

3 DNV GL © 2014 20.10.2014 DNV GL – Industry consolidation 3

4 DNV GL © 2014 20.10.2014 Global reach – local competence 4 400 offices 100 countries 16,000 employees 150 years

5 DNV GL © 2014 20.10.2014  How Big data can transform our industries  How Big data con contribute to make our industries safer, smarter and greener  Some examples from DNV activities 5

6 DNV GL © 2014 20.10.2014 Big data–some key identifiers and business value 6 SourcesBusiness value Volume (real time) CharacteristicsNew Capabilities Behavioural data Velocity (real time) Variety (Sensor, transaction, text etc.) Veracity (VERITAS) Sensor data Geospatial data Transaction / Contributory data Technology Competence Data management & Governance Target marketing Interconnectedness and data sharing Health diagnostics Logistics and optimisation

7 DNV GL © 2014 20.10.2014 Big data - the new data reality 7 "The Internet has changed the way we consume information and talk with each other, but now it can do more, by connecting intelligent machines to each other and ultimately to people, and by combining software and big data analytics, we can push the boundaries of physical and material sciences to change the way the world works.“ General Electric CEO Jeff Immelt

8 DNV GL © 2014 20.10.2014 Impacting DNV-GL’s industries – main trends 8 1.Increased number of sensors 2.Increased ability to exploit sensor data 3.Cross system data analytics Example from Aviation: + = Applications; Use of sensor data across systems for performance-, condition-monitoring, predictive maintenance, and system optimization as well as automation of problem solving and decision making

9 DNV GL © 2014 20.10.2014 Impacting DNV-GL’s industries 9 Integrated operations Efficient drilling and production Asset and operational risk management Pipeline risk management Oil and Gas Maritime Technical operation and maintenance Energy efficiency Safety performance Commercial operation (logistics chain optimization) Automation of ship operations Management and monitoring of accident and environmental risk from shipping traffic Energy Grid management Technical operation Asset and operational risk management Energy efficiency advice, assessment and verification Health Diagnostics Patient monitoring and management Management of patient care processes across system barriers Epidemiology

10 DNV GL © 2014 20.10.2014 Impacting DNV-GL’s industries 10 Maritime Oil and Gas EnergyHealth

11 DNV GL © 2014 20.10.2014 Industry impact – What are the patterns? 11  Automation of insights and decisions  Increased willingness to share/combine data across barriers  New entrants in established industries with new business models and operation modes  Established actors transform their business models and operation modes  New roles like industry specific data aggregators and data stewards emerge

12 DNV GL © 2014 20.10.2014 How to succeed commercially with Big data enabled services? 12 Business models Operation modes Service delivery Commercialisation Capabilities

13 DNV GL © 2014 20.10.2014 Big data and analytics impacting the future of shipping 13 SourcesBusiness value Volume (real time) CharacteristicsNew Capabilities Behavioural data Velocity (real time) Variety (Sensor, transaction, text etc.) Veracity (VERITAS) Sensor data Geospatial data Transaction / Contributory data Technology Competence Data management & Governance Safer Operations Smarter Operations Greener Operations Interconnectedness and data sharing

14 DNV GL © 2014 20.10.2014 Big data and analytics impacting the future of shipping 14 Improved maintenance levels through increased transparency Higher reliability through risk based maintenance Reduce risk related to human error through increased automation and simulation Increase navigational safety through real time analysis of shipping traffic Higher Value chain efficiency through analysis of data across the logistics chain and the environment Improved Operational Efficiency through the improved value chain efficiency and optimisation of operation Reduced emissions as result of the reduced fuel consumption Reduced environmental impact from accidents due to increased safety Safer Smarter Greener

15 DNV GL © 2014 20.10.2014 DNV GL: Ambitions for the shipping industry 15 CO 2 emissions 900 million tonnes per year Lives lost at sea 900 ship accident fatalities per year Average 2003-2012 Freight cost 7-11% of cargo value 60 % reduction in CO 2 emissions 90 % reduction in fatalities in shipping Maintain or reduce present freight cost levels Ambition: Vision for Big data and analytics as one of many means to achieve these ambitions: “Bring the power of trusted, refined and combined data to our customers for them to gain competitive advantage through new information and insights.”

16 DNV GL © 2014 20.10.2014 Analytics and big data already impacting all service lines 16 Ship classification and ship board applications – operational quality Ship emission monitoring services – monitoring emissions to air from shipping traffic Electric cars – managing battery life for vehicle fleets DNV Petroleum services - Benchmarking of fuel suppliers Monitoring emissions to air and managing energy efficiency Predictive maintenance based on Sensor data from components and systems (COMPASS) Environment monitoring, Stewarding role for Component reliability database, Analytic and Big data services DNV Safety Insight – benchmarking safety culture Utilities - load balancing and smart metering Wind– field assessment and monitoring and benchmarking operational quality Pipeline risk monitoring

17 DNV GL © 2014 20.10.2014 Safer - The power of analytics 17 Augmenting class services with analytical insights from Class surveys, Port state inspections, Incidents, Fuel quality etc. “This is a tool for us to stop managing on perceptions and start managing on facts”. Customer feedback

18 DNV GL © 2014 20.10.2014 Safer with smarter class - standardisation 18

19 DNV GL © 2014 20.10.2014 Safer with smarter class - Survey Findings 19

20 DNV GL © 2014 20.10.2014 Safer with smarter class - Class survey findings – examples Machinery Fixed Gas Detection System was found out of order. The gas detection function for ballast tanks and pump room was totally shutdown. Main generator F: - Main Stator Lead cables burnt damaged between the Stator Coils and Terminal Box - Terminal bar supporting bracket iwo the Terminal box burnt. - Control transformers & accessories damaged in the fire. - Outgoing cables between the Alternator to the Main Switchboard burnt iwo the Terminal Box. Oveboard piping for SW cooling line of IGG scrubber found leaking i.w.o. a flange near the ship's shell (under the ER lowest platform). Jury-rigged bucket found.

21 DNV GL © 2014 20.10.2014 Safer with smarter class using Big data – What data? 21 Analysing survey findings on entire fleet in barrier format Reporting survey findings in barrier format Evaluate and trend barrier performance and report barrier status after survey Online integrated performance monitoring with customers management systems As data gets bigger and richer through direct integrations, it is important to focus on the key questions

22 DNV GL © 2014 20.10.2014 Smarter and greener through operational efficiency analytics 22 Know your fleet performance instantaneously Benchmark against your own fleet and history Benchmark against other players in the market Data analytics powered by DNV GL experts “You cannot improve what you do not manage.” “You cannot manage what you do not measure”

23 DNV GL © 2014 20.10.2014 Creating services on public data 23

24 DNV GL © 2014 20.10.2014 Smarter and greener through ship tracking analytics 24 Augmenting class services and creating new analytic services from AIS data and environmental models towards existing and new customer groups. Cutting edge Big data solution e.g. Energy savings through better voyage and speed management

25 DNV GL © 2014 20.10.2014 Eco Insight illustration for home page 25 Weather Hull/Propeller Trim Speed Engine Basic fuel consumption Total fuel consumption (up to 70% of total operational cost) Potential reduction in fuel consumption (up to 20% of total fuel cost)

26 DNV GL © 2014 20.10.2014 Vessel consumption and emission rank 26

27 DNV GL © 2014 20.10.2014 27

28 DNV GL © 2014 20.10.2014 Insights can be used in daily operations, tactical planning or strategic decision making 17. October 2014 AIS Business Intelligence 28 Network & Fleet Port operations Voyage operations Overall operations Purchasing (e.g. port, bunker) AIS Business Intelligence Improved basis for strategic decision making  Benchmarking against partners and competitors  Understanding of underlying business performance drivers 1 1 2 2 3 3 4 4 5 5 Daily operationsTactical planningStrategic decisions Fuel consumption monitoring Charter fleet performance Off-hire analysis New fleet operating profile Carbon footprint profiling Berth availability in next port of call Turnaround time Anchorage waiting times Change port of call Recent bunkering activity in upcoming ports Choose experienced repair yard Competitor bunkering footprint Schedule integrity versus peers Speed profiles Delay management tactics of peers ECA zone routing Average trade lane utilization Pro forma schedules (port/ anchorage/ sea passage) Cost curve modelling (fuel, asset, port, etc)

29 DNV GL © 2014 20.10.2014 Port Operations – berth availability, turnaround times etc. 29

30 DNV GL © 2014 20.10.2014 Big Data can enable transition from rule based via condition based to risk based maintenance also in maritime and Oil&Gas Monitoring signals Diagnostics Prognostics

31 DNV GL © 2014 20.10.2014 Smarter – exploring data collection and diagnostic and prognostic methods 31 Timely maintenance based on prognosis from real time machinery sensor readings

32 DNV GL © 2014 20.10.2014 Safer – New Autonomous short sea ship concept 32 “How far can we go with respect to energy efficiency, emissions and safety and still maintain cost effectiveness?”

33 DNV GL © 2014 20.10.2014 Greener – reducing environmental impact 33 Licence to drill and operate in sensitive areas Managing impact on the environment through sensor based Big Data platform and environmental risk models

34 DNV GL © 2014 20.10.2014 34

35 DNV GL © 2014 20.10.2014 Safer and smarter - Industry data aggregation – data steward 35 Component failure data across competitive barriers stewarded by DNV GL. “The most valuable database in the offshore industry”

36 DNV GL © 2014 20.10.2014 SAFER, SMARTER, GREENER www.dnvgl.com 36


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