Shinkansen oder warum Züge pünktlich kommen (können)! Christian Dornacher Business Manager File & Analytics Solutions EMEA

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1 Shinkansen oder warum Züge pünktlich kommen (können)! Christian Dornacher Business Manager File & Analytics Solutions EMEA

2 Agenda Hitachi und Social Innovation Markttrends und unsere Big Data Analytics Strategie Shinkansen und der Einsatz von Big Data Analytics

3 Agenda Franz Kruckenberg's Schienenzeppelin (Rail Zeppelin), 1931

4 DATA EVOLUTION The Analytics and Data Revolution Bigger and Better Insight Drives Bigger and Better Outcomes THINGS INDUSTRIAL/SOCIAL INFRASTRUCTURE, MOBILE DEVICES. HUMAN EMPLOYEES, CUSTOMERS TRANSACTIONAL (TX) FINANCIAL APPS, BUSINESS APPS THE PAST WHAT HAPPENED? BI AND REPORTING THE PRESENT WHAT S HAPPENING NOW? REAL TIME THE FUTURE WHAT WILL HAPPEN? PREDICTIVE CONTROL FUTURE WHAT SHOULD WE DO? PRESCRIPTIVE ANALYTICS EVOLUTION

5 Deep Innovation Resources Founded in 1910 US$93.4B FY subsidiaries 320,000 employees approx. #1 worldwide for patents in big data analysis US$3.4B INNOVATION BUDGET #78 in the 2014 FORTUNE Global 500

6 How We Achieve Social Innovation Through Big Data Machine data is in our DNA. We think like users because we are users. ROBOTICS I.T. INFRASTRUCTURE AUTOMOTIVE SYSTEMS MINING EQUIPMENT RAILWAY CONTROL SYSTEMS AND TRAINS GAS TURBINES SENSORS MEDICAL IMAGING WEARABLES PROGRAMMABLE CONTROLS WATER TREATMENT SOCIAL INFRASTRUCTURE PUBLIC SAFETY MEDICAL DIAGNOSTICS BATTERY SYSTEMS WIND TURBINES

7 Hitachi Social Innovation We integrate IT and infrastructure technologies for a healthier, safer, sustainable world

8 Hitachi Is Unique Social Infrastructure Information Infrastructure Analytics Innovation We build the things that generate big data We build the IT hardware and software infrastructure to capture, manage, and analyze big data We have the deep domain expertise to turn big data into big value Social Innovation Uses the Entire Hitachi Portfolio

9 Hitachi Global Centers for Innovative Analytics UK / FRANCE Healthcare Automotive USA Energy Oil & Gas Mining IT Analytics CME Automotive Analytics Framework DENMARK Energy Efficiency Digitalization Smart Mobility INDIA Energy Transportation Analytics Framework CHINA Transportation Energy Healthcare JAPAN Mining Transportation Energy Healthcare Automotive Analytics Framework SINGAPORE CME Oil & Gas Transportation Energy Healthcare

10 Shinkansen in Japan some Facts 47 Years of operations (since 1964) Zero fatalities 346 million passenger per year Average delay less than 1 minute (incl. bad weather conditions)

11 Shinkansen Technologies ATP Automatic Train Protection System Services Predictive Maintenance for longer and more reliable fleet operation Automated rail-track control Traffic planning and operations Traffic planning and operations (i.e. Olympics 2020 in Tokio) Train detection and distance Emergency signals and control Temporary speed limit information Combination with other systems (Weather, Seismic information, etc.) Power Solutions Energy efficiency Automatic control and maintenance

12 Smart Operation and Control 1. Current Train Status 2. Actual Diagrams 3. Implemented Diagram 4. Operation Information 5. Power-supply Status 6. Implemented Diagram Approaching Train Information 7. Train Control Status 8. Maintenance-work Input (Plan, start, finish) 9. Infrastructure Status Information 10. Maintenance-work Input (Plan, start, finish)

13 Hitachi & BIG DATA real life use case Hitachi train link program in the uk UK contract with Hitachi Rail Build & supply 100 train sets + 27 years maintenance & support coverage Predictive maintenance based on innovative Big Data Analytics (Hitachi Train Link program / project) The business goal of the Hitachi Train Link Program / project: 1. Quality of Maintenance Service Improvement 2. Increased safety early warning systems 3. Reduced traffic downtime 4. Therefore, optimized & reduced maintenance costs 5. As well as contribute in increasing / optimizing the revenue

14 Smarter business service model for railways

15 Hitachi Trainlink Program Reducing Costs Maintenance Predictive Maintenance through Big Data Analysis Exploiting experience in real-time sensor data acquisition on C395 Fleet Leveraging Data Scientist and Engineering Knowledge from Research Laboratories Managing volume and speed leveraging HDS UCP Platform with Hadoop and Hitachi Analytics

16 Train link program in details Capture the performance status of the train and infrastructure assets Real-time sensor data of the Hitachi C395 train fleet Streaming 1TB / day from 100s of sensors (per train) providing real time metrics on: speed, hydraulic pressure, weight, temperature, BIG DATA sets and engineering knowledge from the Hitachi Train research labs. Analysis produces dashboard allowing to monitor & diagnose bottlenecks Preventive maintenance and identify other issues in real time Predict failures of assets Advanced analytic tools provide insight into real time & provide: what if scenarios ; Predict the required pro-active maintenance Automated actions stop the train and schedule maintenance

17 DELIVERING HITACHI VISION FOR SOCIAL INNOVATION AND BIG DATA TOMORROW TRANSPORTATION Conversion of Intercity Train System from diesel to electric INNOVATIVE ANALYTICS OF: Real-time sensor, ticket data, diagnostics BENEFIT: Active machine maintenance reduces costs and increases safety for passengers INTEGRATED STRATEGY ACROSS HITACHI DECADES OF VERTICAL INDUSTRY EXPERIENCE GLOBAL GO-TO-MARKET FOR BIG DATA OF TOMORROW SOLUTIONS RAIL SYSTEMS INFRASTRUCTURE SYSTEMS GROUP TRANSPORTATION AND CONTROL SYSTEMS INFORMATION AND TELECOMMUNICATIONS DIVISION SMART INFORMATION SYSTEMS SENSOR AND TICKET ANALYTICS IT PLATFORM DIVISION SEARCH, STORE AND ACCESS TRAIN AS A SERVICE FOR UK INTERCITY EXPRESS TRAINS

18 Thank You

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