Closing the Loop: The Data-First Approach in Digital Railway - PowerPoint PPT Presentation

Closing the Loop: The Data-First Approach in Digital Railway Michele Budetta Senior Vice President Service and Maintenance Hitachi Rail Italy Suhail Jiwani Senior Director, Product Management Lumada IOT Platform

Hitachi Rail offers an Integrated Capability

Rail industry demand is underpinned by strong fundamentals We have a geographically diverse business with the ability to bid effectively on major projects all over the world Europe (excl. UK) Revenue: 32% UK Revenue: 26% Japan Revenue: 17% Americas Revenue: 11% Middle East & Africa Revenue: 4% Asia Pacific (excl. Japan) Revenue: 10% OFFICES / SALES PRESENCE HEADQUARTERS FACTORIES Hitachi Rail Hitachi Rail Hitachi Rail Total global headcount – 11,091 (1) Ansaldo STS Ansaldo STS Ansaldo STS 3

Rail industry demand is underpinned by strong fundamentals Global Population (billions) (1) Population 10.8 Growth 10.2 9.2 7.8 6.1 4.4 3.0 1960 1980 2000 2020 2040 2060 2080 Global population is forecast to grow to approximately 10.8 billion by 2080 § § Rail will play an increasingly important role in the mass transit segment of travel as global population grows

Rail industry demand is underpinned by strong fundamentals Urbanization Percentage of People Living in Urban Areas (2) 70% 66% 60% 52% 43% 37% 34% 30% 1950 1970 1990 2010 2030 2050 § Significant increase in urbanisation over the last century, which is forecast to continue § Urban mobility has been a key factor in enabling this change § Inner-city, metro and commuter rail demand will increase with continued urbanisation

Greenhouse Gas Emissions by Travel (grams of CO 2 per passenger km) (3) Environment 150g 30g – 70g 170g § As population and urbanisation increases, reducing CO 2 emissions will become an increasingly politically sensitive issue § Rail could play a key role reducing CO2 emissions

Hitachi is well placed to compete in growing markets Market Landscape § M&A and Consolidation in the industry to increase § Several pure play system business have been acquired to become part of a full line up rail business § Competitors are all seeking to enhance their technological capability Market Position by FY2016 Revenue (2) ¥ billion Full Line Up 3,776.9 Rolling Stock Systems 947.9 867.3 841.4 497.9 497.7 ~300 297.1 178.2 164.8 Overseas Revenue ~10

Hitachi Rail Service & Maintenance – Very High Speed, Long Haul & Regional fleets Served Electric and diesel loco fleet Frecciarossa fleet ETR1000 TSR fleet 35 Trains (115 cars) 307 loco 50 trains (400 cars)-25 years Class 395 Javelin Trains Caravaggio-Rock fleet (from 29 TRAINS (174 CARS) 2019) 300 trains (1425 cars) Frecciarossa fleet ETR500 59 trains (649 cars) AT300: Class 800 Intercity Frecciabianca fleet Double-Deck CDPTR fleet Express 122 BI-MODE (866 136 loco + 734 cars 706 cars CARS)

Hitachi Rail Service & Maintenance – Mass Transit & Tramways Fleet Rome Line C- 13 Trains (78 Copenhagen Cityringen- Sirio Zuhai-Bejing 10 Thessaloniki 18 Trains cars ) driverless 39Trains (136 cars) driverless Trains (40 cars ) (72cars ) driverless Milan Line 4-5 68 Trains Madrid 46 Trains (216 Honolulu- 20 Trains (80 Taipei 17 Trains (68 (340 cars) driverless cars ) cars) driverless cars ) driverless Lima Line 2 42 Trains 252 Miami- 68 Trains (136 cars) Fortaleza - Linea Sur – Thai Red Line 15 cars driverless 25 Trains (125 cars) Trains (90 cars )

Strategy to Action - Grow Rolling Stock Maintenance An overview of our current rolling stock maintenance business § Hitachi Rail has over 50 maintenance sites worldwide § We have invested in our facilities, most recently in Doncaster and Swansea (UK), to provide the additional capacity required to deliver our recent contract wins § We have won several major maintenance contracts including: § 27.5 year IEP contract Several other UK contracts § Trenitalia ETR1000, ETR500, and TSR § trains

Strategy to action – Focus on IOT and Digital Hitachi Rail is in a unique position in having an integrated supply chain to develop and roll-out its IOT and digital solutions Asset Management § Data Analytics • Transform from fixed maintenance inspections to condition based maintenance Slip detection Pneumatic with predictive interventions to minimise pressure required maintenance and maximise railway asset availability • Utilise data and knowledge gathered to ‘future proof’ new train designs Brake Brake § Delivery thickness temperature • Improve profitability for long-term maintenance contracts • Enhanced competitive position for future bids

CBM and IOT are Customer Requirements Trenitalia collects up to 10,000 parameters per locomotive each second, transmits these in real time via the Internet, and exploits them to better understand the health status of its fleet. Trenitalia CBM and IOT economics Development Investment in IoT €50M Maintenance Annual Cost €1.3B Vehicles where TI applies IOT 4000 Saving expected with IOT and CBM 18 % Saving expected due to penalty reduction €20M

Lumada IOT Platform Connect Collect Analyze Act

Key Tenets of Lumada Platform Speed to Ecosystem Low Friction Value Enablement

Lumada’s Intelligent Asset Avatars Physical Asset Asset Visualization Avatar Apps Asset Avatar Type Physical Asset Data Query Asset Avatar Service Alerts Asset Physical Avatar Asset Analytics § Asset Avatar Type is a digital blueprint for a class of assets (e.g: Trains, Trucks) § Asset Avatars are an instance of an asset avatar type and inherit properties of the physical asset. It is continuously updated with sensor values

Condition Based Monitoring for Hitachi Trains

Digital Thread: Data-Driven Optimization Sensors

Smart Factory, IOT and CBM CBM in IOT and Smart Factory Traditional CBM Goal § Improve design and production § Ensure the reliability of the quality. vehicle operation. Improve vehicle reliability and Reduce maintenance cost. § § maintenance efficiency. Data Time varying data. Multiple data Very limited time varying sources features Scope Component and System level Parts (LRU) level Approach Data driven, Model driven Model driven Tasks • Failure prediction, fault/failure • Failure prediction detection & diagnosis. (prognosis), fault/failure Maintenance actions optimization. detection & diagnosis • Any task that improve Design and (diagnosis) production

Thank You