Unsolved problems in freight transport - climbing the three mountaintops of real-time data
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The current paradigm in freight transport is based on economies of scale, batch handling and standardization. In order to make the transport system more efficient, the industry may need to enter the real-time data world where informed decisions must be made in seconds on a large scale.
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Unsolved problems in freight transport - climbing the three mountaintops of real-time data
- 1. CC-BY PER OLOF ARNÄS UNSOLVED PROBLEMS IN FREIGHT TRANSPORT CLIMBING THE THREE MOUNTAINTOPS OF REAL-TIME DATA Per Olof Arnäs Chalmers University of Technology @Dr_PO per-olof.arnas@chalmers.se about.me/perolofarnas Slides: slideshare.net/poar En la cima! by Alejandro Juárez on Flickr (CC-BY)
- 2. Northern LEAD Logistics Research Centre Founded by: Chalmers University of Technology University of Gothenburg Logistics and Transport Society LTS
- 3. Northern LEAD coordinates and supports logistics research at Chalmers and University of Gothenburg in order to increase volume, quality and relevance of the research What we do stairs by Denis Jacquerye on Flickr
- 4. Tomorrow’s logistics. We are finding the answers. Around 70 researchers Research centre for sustainable logistics solutions Five core research groups Organises, facilitates, disseminates highly relevant logistics researchCollaboration between Chalmers and University of Gothenburg
- 5. Physical Distribution Production Logistics Industrial marketing & purchasing Logistics & Transport Optimization Professors 10 Visiting Professors 6 Associate Professors 5 Post docs 6 Faculty 14 PhD students 32 Total 73 Five core research groups
- 6. Thought leadership through high quality research and innovation Challenges and trends Outcomes for policy and business Volatility and risk Demographic changes Complexity and structural flexibility Resource limitations Manufacturing and retail revolution Environmental impact Focused areas Urban Transport Long Distance Transport Purchasing of transport Logistics and Production Networks Information, planning and control Measurements and measuring Service development in networks Resource utilisation Intermodality
- 7. Per Olof Arnäs The Transport industry 3 things: Carbon-free transport by Stéfan on Flickr
- 8. …physical 3d boxes by crystaljingsr on Flickr
- 9. Technology Management and Economics Logis4kcs and Transporta4onCC-‐BY Per Olof Arnäs …public Traffic Jam by Giorgio Minguzzi on Flickr
- 10. Technology Management and Economics Logis4kcs and Transporta4onCC-‐BY Per Olof Arnäs …analogue 542 miles by Jason on Flickr
- 12. Per Olof Arnäs Stage Coach Wheel by arbyreed on Flickr Development of transportation technology has been fairly linear …for the last 5500 years
- 13. We are in the middle of a gigantic exponential development curve beginning
- 14. A new global eco system where new types of, knowledge based, industries compete with traditional ones
- 15. http://bryce.vc/post/18404303850/the-problem-with-innovation Startups don’t compete with airlines... by purchasing a bunch of planes hiring a bunch of pilots and locking up a bunch of terminals at airports. Miniature Airport by disparkys on Flickr
- 16. Startups compete with airlines by inventing videoconferencing. http://bryce.vc/post/18404303850/the-problem-with-innovation Startups don’t compete with airlines... Miniature Airport by disparkys on Flickr (CC-BY,SA) by purchasing a bunch of planes hiring a bunch of pilots and locking up a bunch of terminals at airports.
- 19. Safety imbalance Variation in resource demand Chain imbalance Caused by the chain Technological imbalance E.g. mismatch in equipment Operational imbalance Goods and resource flow not compatible Structural imbalance Uneven transport demand
- 20. Safety imbalance Variation in resource demand Chain imbalance Caused by the chain Technological imbalance E.g. mismatch in equipment Operational imbalance Goods and resource flow not compatible Structural imbalance Uneven transport demand Several of these imbalances can be reduced by reducing uncertainties
- 21. InSearchOfLostTimebybogenfreundonFlickr But the biggest problem in transportation is time. There is not enough of it. Ever.
- 22. The transport industry does not like real-time decisions. At all. DSC_9073.jpg by James England on Flickr (CC-BY)
- 23. The transport industry does not like real-time decisions. At all. Batch-handling Zip codes Zones Time-tables DSC_9073.jpg by James England on Flickr (CC-BY)
- 24. Image: Alain Delorme, alaindelorme.com The current model is focused on economy of scale and standardization
- 25. Image: Alain Delorme, alaindelorme.com The current model is focused on economy of scale and standardization
- 27. So… What are we doing about all this?
- 28. CC-BY PER OLOF ARNÄS Strategic Tactical Operational Predictive Time horizons We are approaching this boundary …and we are starting to move past it! Real-time!
- 30. Goods Vehicle Business process Infra- structure Barcodes RFID Sensors ERP systems TMS systems E-invoices Cloudbased services Order handling Driver support Vehicle economics RDS-TMC Road taxes Active traffic support Digitization fronts
- 31. CC-BY PER OLOF ARNÄS Business processes Infra- structure Paperbased Phone Papers Road signs A nalogue tools R D S M onitorfuel cosnum ption Digitization version 0 0.5 1.0 1.5 2.0E-mail Fax TMS- systems Excel Route planning G PS fornavigation Electronically generated freightdocum ents Barcodes RFID-tags Simple order handling Advanced order handling Openinterface W eb based UI Platform based system s Hardware- oriented Datacollection systems (proprietary) Communication withvehicles E-invoice W eb based booking Route optimisation ThesocialwebOpenconnectivity Integrated prognosis Data collection system s (open) Tolling system s Webservices with traffic data Dynamic routing systems Performance BasedaccessPerformanceBasedaccess Mashups Multipledata sources Probedata Individual routing inform ation Platooning Platooning Exceptions handling Smartgoods Manual Computers Software Functions Distributed decision making G oods as bi- directional hyperlink Paperbased CC-BY Per Olof Arnäs, Chalmers Goods Vehicle
- 32. Goods Vehicles Business processes Infrastructure Stra- tegic Tac- tical Opera- tional Pre- dictiveWhat happens when access to real-time data increases? not quite clear on the concept by woodleywonderworks on Flickr (CC-BY)
- 33. http://www.gartner.com/newsroom/id/2575515 Source: Gartner August 2013 Augmenting humans with technology Machines replacing humans Humans and machines working alongside each other Machines better understanding humans and the environment Humans better understanding machines Machines and humans becoming smarter Gartners Hype Cycle for Emerging Technologies
- 34. http://www.gartner.com/newsroom/id/2575515 Source: Gartner August 2013 Gartners Hype Cycle for Emerging Technologies
- 35. http://www.gartner.com/newsroom/id/2575515 ? Source: Gartner August 2013 Gartners Hype Cycle for Emerging Technologies Transportation/ logistics?
- 36. Opportunities Digitization Increasinggoods volumes New technology Political interest Quad Aces by fitzsean on Flickr
- 37. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) 3 mountaintops to climb…
- 38. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) Fixed Historical 3 data types Mountaintop #1 Collection of data in real-time Snapshot
- 39. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) 5 data domains Vehicle CargoDriver Company Infrastructure/ facility at least… Mountaintop #1 Collection of data in real-time
- 40. Length Weight Width Height Capacity + other PBS-criteria Emissions Fuel consumption Route Position Speed Direction Weight Origin Destination Accepted ETA Temperature + other state variables Temperature + other state variables Education/training Speed (ISA) Rest/break schedule Traffic behaviour Belt usage Alco lock history Schedule status (time to next break etc.) Contracts/ agreements Previous interactions Backoffice support Fixed Historical Snapshot Vehicle Cargo Driver Company Infrastructure/ facility Map + fixed data layers Traffic history Current traffic Queue Availability DATA MATRIX
- 41. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) Mountaintop #2 Processing of data in real-time Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr
- 42. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) Mountaintop #2 Processing of data in real-time
- 43. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) Mountaintop #3 Exploiting data in real-time Connected. 362/365 by AndYaDontStop on Flickr (CC-BY) Lisa for I/O Keynote by Max Braun on Flickr (CC-BY) Fulham-Manchester United 24-02-2007 by vuhlser on Flickr (CC-BY)
- 44. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) Mountaintop #3 Exploiting data in real-time Boeing-KC-97 Stratotanker by x-ray delta one on Flickr (CC-BY)
- 45. CASES (MANY)
- 47. Challenges The Challenger by Martín Vinacur on Flickr (CC-BY)
- 48. The Challenger by Martín Vinacur on Flickr (CC-BY) Not all ideas age with grace
- 49. The Challenger by Martín Vinacur on Flickr (CC-BY) Someone must do the work
- 50. The Challenger by Martín Vinacur on Flickr (CC-BY) Not everyone will want to adopt new things…
- 52. CC-BY PER OLOF ARNÄS UNSOLVED PROBLEMS IN FREIGHT TRANSPORT CLIMBING THE THREE MOUNTAINTOPS OF REAL-TIME DATA Per Olof Arnäs Chalmers University of Technology @Dr_PO per-olof.arnas@chalmers.se about.me/perolofarnas Slides: slideshare.net/poar En la cima! by Alejandro Juárez on Flickr (CC-BY)