AI FÖR JÄRNVÄG. JVTC Quality Hotel, Luleå

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1 AI FÖR JÄRNVÄG JVTC Quality Hotel, Luleå

2 OUTLINE (Digitalisation) AI Railway 2

3 DIGIT ALIS ATION 3

4 DIGITOLOGY F A Digit a symbol for numeric representation, which can be used alone or in combination, e.g. binary digits(base2), octalt digits (base8), hexadecimal digits (base16), Arabic digits (base10) Digitisation Refers to the technical process of converting streams of analogue data into digital form, e.g. binary digits (BusinessDictionary, 2018) Digitalisation Integration of digital technologies into everyday life by the digitization of everything that can be digitized (BusinessDictionary, 2018) 4

5 TNC ON DIGITALISATION Digitalisering är från början en teknisk term och innebär att analoga signaler omvandlas till digital form (ettor och nollor) Digitaliseringskommissionen definierade begreppet digitalisering i delbetänkande SOU 2014:13. Här lyftes såväl informationsdigitalisering som samhällelig digitalisering fram. Med informationsdigitalisering avses den process där analog information transformeras till digital information. Det innebär att informationen blir strukturerbar, sökbar och tillgänglig genom digitala kanaler. Samhällelig digitalisering är den förändring av verksamheten, teknikanvändningen och de affärsmässiga förutsättningarna som uppkommer genom de nya möjligheter som tekniken ger, som ofta kan ha en disruptiv och oväntad effekt [ramin.karim@ltu.se] 5

6 DIGITALISATION - CHALLENGES Regelverk behöver anpassas Se data som en del av en modern infrastruktur Både teknisk och affärsmässig kompetens behöver förstärkas Synen på integritet och säkerhet kan förändras [ramin.karim@ltu.se] 6

7 DIGITALISED INDUSTRY (INDUSTRY 4.0) Industry 4.0 is a Germangovernment-sponsored vision for advanced manufacturing Source: (Kagermann et. al., 2013) 7

8 DIGITAL TWIN WHAT IS THAT Industrial perspective A digital twin is a dynamic digital representation of an industrial asset, that enables companies to better understand and predict the performance of their machines (GE, 2018) Data perspective Virtual instance of a customer-unique asset (Microsoft, 2017) Scientific perspective A digital representation of physical asset within a given context. (Karim, 2017) [ramin.karim@ltu.se] 8

9 MATERIALISATION OF CYBER-PHYSICAL ENVIRONMENT (DIGITAL TWIN) Business connectivity Analytics Visualisation Cognitive Data & model connectivity Management Processing Computing Device connectivity IoT Industrial internet DT Services DT Architecture DT Infrastructure 9

10 ARTIFICIAL INTELLIGENCE 10

11 INTELLIGENCE Abilities to learn from experiences, adapt to new situations, understand and handle abstract concepts 11

12 SCIENCE2CONCEPTUALISAION Algorithms 1956 AI Discovery Domain recognition Situation awareness Context adaptation Biased AI Software Liveware Governance Safety Integrity Hardware Policies Security 12

13 ARTIFICIAL INTELLIGENCE Act Adapt Discover See Percept Learn Store Think Compute Feel Emotion 13

14 Level 0: No Automation Level 1: Driver Assistance Level 2: Partial Automation Level 3: Conditional Automation Level 4: High Automation Level 5: Full Automation BIASED AI IN AUTOMOTIVE INDUSTRY Society of Automobile Engineers (SAE) International J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles Human monitors the environment Automated system monitors the environment Adapted from: SAE, Society of Automotive Engineers 14

15 AI IN A NUTSHELL Algorithms Digits Digits 15

16 AI IN RAILWAY 16

17 BIASED AI - EXAMPLE 17

18 BIASED AI - EXAMPLE Pictures of Fastener Deep Learning Type of Failure 18

19 BIASED AI - EXAMPLE 19

20 BIASED AI - EXAMPLE Domain: Train dispatching Problem: Stabilise trian traffic in the network Objective: Our research aim is to generate automated suggestions for human decision making through evaluation of the quality of different disposition strategies. Approach: We want to provide real time suggestions for disposition strategies with minimal network disturbance impact. 20

21 DIGITALISATION & AI SOME TRENDS 21

22 PREREQUISITES IN RAILWAY AI Sustainability Performance Cost Governance Rules Business Biased AI Convergence Cyber/Physical IT/OT Algorithm Reward/penalty Decision Data Availability Accessibility Digitalisation Digital Twin Simulation 22

23 SCIENCE2MATERIALISATION Algorithms 1956 Discovery Domain recognition Context adaptation Situation awareness Information logistics Distributed ledger AI Biased AI emaintenance Software Hardware Liveware Governance Policies Safety Security Integrity Cloud computing egovernance Information quality Data quality Information assurance Data integrity 23

24 EMAINTENANCE - A RAILWAY RESEARCH OBJECTIVE To achieve high level of autonomy in railway asset by How can I help You? enablement Biased AI (BAI) through convergence of SW, HW & LW 24

25 EMAINTENANCE DNA A SYSTEM PERSPECTIVE Data Analytics Mechanical components Electrical components Software components Human components [ramin.karim@ltu.se] 25

26 EMAINTENANCE SCIENTIFIC ROADMAP 26

27 EMAINTENANCE CONCEPTUAL MODEL Application tier Operation Maintenance Dispatch Inspection Analytics tier AI-engine BI-engine Visualisation Integration tier Service-oriented middleware Message-oriented middleware Event-oriented middleware Content tier Data Ontologies Models 27

28 THIS IS ALLA ABOUT DISTRIBUTION AUTONOMY Reduce LW intervention in the system through enhanced utilisation of SW & HW! COMPUTATION DIGITALISATION 28

29 BIASED AI IN RAILWAY CONTEXTS Software (AI) Liveware (I) Repetitive Experience Optimisation Complex Creative Track repair Vehicle driving Maintenance Strategies Science Inspection Fault recognition Operation Architectures Engineering Customer support Condition assessment Spare part Policies & rules Technologies Monitoring Security Route planning System-of-systems Methodologies 29

30 30 Thank You for Your Attention!