We are building The Matrix in the transport industry

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A talk about the digitization of the freight transport industry. Technologies like 3D printing, wearable tech and big data are revolutionizing the industry.

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We are building The Matrix in the transport industry

  1. 1. Digitization of the transport industry We are building The Matrix ! ! Per Olof Arnäs Chalmers @Dr_PO per-olof.arnas@chalmers.se about.me/perolofarnas
  2. 2. The Transport industry 3 things: Per Olof Arnäs Carbon-free transport by Stéfan on Flickr
  3. 3. …physical 3d boxes by crystaljingsr on Flickr
  4. 4. …public CC-­‐BY  Per  Olof  Arnäs Technology  Management  and  Economics   Logis4kcs  and  Transporta4on Traffic Jam by Giorgio Minguzzi on Flickr
  5. 5. …analogue 542 miles by Jason on Flickr CC-­‐BY  Per  Olof  Arnäs Technology  Management  and  Economics   Logis4kcs  and  Transporta4on
  6. 6. CC-­‐BY  Per  Olof  Arnäs Technology  Management  and  Economics   Logis4kcs  and  Transporta4on
  7. 7. 1989 CC-­‐BY  Per  Olof  Arnäs Technology  Management  and  Economics   Logis4kcs  and  Transporta4on
  8. 8. 1989 Map on the wall with pushpins Delivery notes (3 carbon sheets) Radio Telephone Pens in various colours CC-­‐BY  Per  Olof  Arnäs Prices, phone numbers etc. Technology  Management  and  Economics   Logis4kcs  and  Transporta4on Calculator Cardfile of customers, tank sizes etc.
  9. 9. 1989 Ca 100 customers in west Sweden 6 tanker trucks (7 partitions per vehicle) Products: Gasoline 95 Gasoline 96 Gasoline 98 Diesel Diesel, colored 8-10 Pricing (yesterday’s orders) 10-12 Call and receive tomorrow’s orders 13-17 Planning A FULL TIME JOB! CC-­‐BY  Per  Olof  Arnäs Technology  Management  and  Economics   Logis4kcs  and  Transporta4on
  10. 10. The Internet first became available for Swedish consumers around 1993 + = A (bad and expensive) mix between Teletext and the Yellow Pages Not very pretty Few people with computers
  11. 11. 15 years later, in 2008, Google Flu Trends was launched Based on what people google and where their computer is located www.google.org Ten days ahead of the official flu tracker
  12. 12. How  will  we  use  the  technology  in  10  years? lm a st o We have no idea. ! The girl and the iPad by Niclas Lindh on Flickr (CC-BY)
  13. 13. How  will  we  use  the  technology  in  10  years? lm a st o We have no idea. ! ...and neither does she, but she will be dissatisfied with stuff that we think are pure science fiction and almost magic. The girl and the iPad by Niclas Lindh on Flickr (CC-BY)
  14. 14. Development of transportation technology has been fairly linear …for the last 5500 years Per Olof Arnäs Stage Coach Wheel by arbyreed on Flickr
  15. 15. inning beg We are in the middle of a gigantic exponential development curve
  16. 16. A new global eco system where new types of, knowledge based, industries compete with traditional ones
  17. 17. Startups don’t compete with airlines... by purchasing a bunch of hiring a bunch of and locking up a bunch of planes pilots terminals at airports. Miniature Airport by disparkys on Flickr http://bryce.vc/post/18404303850/the-problem-with-innovation
  18. 18. Startups don’t compete with airlines... by purchasing a bunch of hiring a bunch of and locking up a bunch of planes pilots terminals at airports. Startups compete with airlines by inventing videoconferencing. Miniature Airport by disparkys on Flickr (CC-BY,SA) http://bryce.vc/post/18404303850/the-problem-with-innovation
  19. 19. CC-­‐BY  Per  Olof  Arnäs Technology  Management  and  Economics   Logis4kcs  and  Transporta4on
  20. 20. Addicted to dead trees
  21. 21. Physical flow Original? Copy? Ownership Consignor Consignee
  22. 22. In Search Of Lost Time by bogenfreund on Flickr The biggest problem in transportation is time. There is not enough of it. Ever.
  23. 23. So… What are we doing about all this?
  24. 24. Time horizons Strategic Tactical Operational Prognosis Realtime! We are approaching this boundary …and we are starting to move past it!
  25. 25. Digitization fronts Goods Vehicle Business process Infrastructure
  26. 26. Digitization fronts Goods Vehicle Order handling   Driver support   Vehicle economics Barcodes   RFID   Sensors ERP systems   TMS systems   E-invoices   Cloudbased services RDS-TMC   Road taxes   Active traffic support Business process Infrastructure
  27. 27. ata s gn be d si d Ro a S Pro ed as rb Pa pe D R Route optimisat ion ing n too Pla 2.0 M Mu ash up lti so ple d s
 urc at es a na vi fo r PS G es rvic ata se Web raf fic d t with ng lli ms To ste sy Dy n ro am uti ic sy ste ng ms ga tio l Ex c ha eptio nd lin ns g 1.5 n RF ID tag s ec fr tro ei n gh ic t d ally oc g um en e Pa en ra pe ts ted rb as ed Di s de tribu ma cisio ted kin n g Sma El ce Ex W e bo b ba ok se in d g nce Performa cess Based ac ail pl Rou an te ni ng g e gu lo ls na oo t A E-m STM ms te sys Fax e oic inv E- ity tiv ec nn co en Op eb cial w ion icat mun les Com h vehic wit o The s In pr teg og ra no ted si s 1.0 ni n 0.5 too Pla e
 on rs Ph ape P 0 n ctio olle a c tems ) y Dat sys rietar op ( pr are rdw d Ha iente or Manual UI Computers d se Sim p han le ord dlin er g Digitization version Business processes Pl a ba tfo sy s r st ed m em s B Vehicle Perfor Based mance acces s Software l ue n r f tio ito p on um M sn co rt g ood s Adv anc han ed ord dlin er g ba es d co ar co Da sy llec ta s t (o tem ion pe s n) eb W bi s al a ds tion nk oo c li G ire er d yp h Goods O int pen erf ac e Functions l ua id iv ting ion d In rou at rm fo in Infra- structure CC-BY Per Olof Arnäs, Chalmers
  28. 28. What happens when access to real-time data increases? Strategic Tactical Operational Prognosis Infrastructure Business processes Vehicles Goods not quite clear on the concept by woodleywonderworks on Flickr (CC-BY)
  29. 29. Time to switch birds
  30. 30. What would happen if a pallet had a Twitter account?
  31. 31. Probably nothing.
  32. 32. Probably nothing. Well, that was not exactly true…
  33. 33. 140 characters Hyperlinked @-names Realtime Hyperlinked #-tags Unilateral subscription Automagical geocoding
  34. 34. Reference trigging event Hyperlinked
  35. 35. When the shipment passes a reader, the message is sent automatically
  36. 36. When the shipment passes a reader, the message is sent automatically The shipment reports often Whoever is interested can keep track
  37. 37. Association is done in realtime and is reported instantly
  38. 38. Association is done in realtime and is reported instantly The shipment is associated with Vehicle 18 and Shipment 2345 If you subscribe to one, you subscribe to all of them
  39. 39. But… does this mean that all pallets will have onboard computers now?
  40. 40. But… does this mean that all pallets will have onboard computers now? No, of course not.
  41. 41. But… does this mean that all pallets will have onboard computers now? No, of course not. It is enough that it has a digitally readable identity, like a RFID tag
  42. 42. But… does this mean that all pallets will have onboard computers now? No, of course not. It is enough that it has a digitally readable identity, like a RFID tag All logic is located in the reader
  43. 43. Su Su bs bs cri cr Subscrip ine b ip pti tio n on tion m Co M as hu Create value p Rem ix ion ipt scr ub SETI by Paulo Alegria on Flickr S My own data
  44. 44. ub Su bsc sc r ub riip scr pAti ip oon n tio n scription ion ipt Publish PubSub This is not a social media megaphone by mikael altemark on Flickr SETI by Paulo Alegria on Flickr scr b
  45. 45. ub Su bsc sc r ub riip scr pAti ip oon n tio n scription ion ipt scr b der r O info Cust omer infor matio n Vehic l e/Ves sition y el po ilit /Vess hicle e sab V es cc ya ilit ac F Operational data, not secret Secret data PubSub sel E TA This is not a social media megaphone by mikael altemark on Flickr SETI by Paulo Alegria on Flickr Publish tion rma
  46. 46. ub Su bsc sc r ub riip scr pAti ip oon n tio n scription scr ion ipt b Publish Publish Publish Publish Operational data, not secret Secret data PubSub This is not a social media megaphone by mikael altemark on Flickr SETI by Paulo Alegria on Flickr Publish
  47. 47. ub Su bsc sc r ub riip scr pAti ip oon n tio n scription ion ipt scr b Publish Publish Publish Publish Publish SETI by Paulo Alegria on Flickr New data Combine Operational data, not secret Secret data PubSub This is not a social media megaphone by mikael altemark on Flickr Subscribe
  48. 48. Dialogue between vehicle and infrastructure Footprinting Increase efficiency by sharing data This is not a social media megaphone by mikael altemark on Flickr SETI by Paulo Alegria on Flickr Benefits in transportation
  49. 49. Dialogue between vehicle and infrastructure Access control Journey planning data CC-­‐BY  Per  Olof  Arnäs Probe data Graphic Conversation by Marc Wathieu on Flickr
  50. 50. Footprinting Energy use Environmental Economical Infrastructure use ...and 100! by MarcelGermain on Flickr
  51. 51. Increase efficiency by sharing data Bottle-neck planning Optimize infrastructure use CC-­‐BY  Per  Olof  Arnäs Matchmaking Optimize vehicle use
  52. 52. Gartners Hype Cycle for Emerging Technologies Augmenting humans with technology Machines better understanding humans and the environment Machines replacing humans Humans and machines working alongside each other Humans better understanding machines Machines and humans becoming smarter Source: Gartner August 2013 http://www.gartner.com/newsroom/id/2575515
  53. 53. Gartners Hype Cycle for Emerging Technologies Source: Gartner August 2013 http://www.gartner.com/newsroom/id/2575515
  54. 54. Gartners Hype Cycle for Emerging Technologies Transportation/ logistics? ? Source: Gartner August 2013 http://www.gartner.com/newsroom/id/2575515
  55. 55. bi s al a ds tion nk oo c li G ire er d yp h co Da sy llec ta s t (o tem ion pe s n) Some trends that we are very interested in ed as rb Pa pe D M Mu ash up lti so ple d s
 urc at es a na vi fo r PS G Dy n ro am uti ic sy ste ng ms ga tio n R 2.0 Perfor Based mance acces s ec fr tro ei n gh ic t d ally oc g um en e Pa en ra pe ts ted rb as ed RF ID tag s Sma El S Pro be d s gn si d Ro a ata 1.5 l ua id iv ting ion d In rou at rm fo in Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr ing n too Pla nce Performa cess Based ac 3D Printing Route optimisat ion g l es rvic ata se Web raf fic d t with ng lli ms To ste sy ni n ce Ex pl Rou an te ni ng Ex c ha eptio nd lin ns g too Pla e gu lo ls na oo t ail STM ms te sys In pr teg og ra no ted si s 1.0 Big data Fax W e bo b ba ok se in d g n ctio olle a c tems ) y Dat sys rietar op ( pr e
 on rs Ph ape P 0.5 e oic inv E- ity tiv Ora by cskk on Flickr (CC-BY) 0 A E-m ion icat mun les Com h vehic wit ec nn co en Op eb cial w o The s Wearable tech are rdw d Ha iente or Manual UI Computers d se Sim p han le ord dlin er g Digitization version Business processes Pl a ba tfo sy s r st ed m em s B l ue n r f tio ito p on um M sn co rt g ood s Software Vehicle ba Adv anc han ed ord dlin er g eb W es d co ar Di s de tribu ma cisio ted kin n g Goods Lisa for I/O Keynote by Max Braun on Flickr (CC-BY) O int pen erf ac e Functions Infra- structure CC-BY Per Olof Arnäs, Chalmers
  56. 56. Wearable tech Lisa for I/O Keynote by Max Braun on Flickr (CC-BY) We are becoming cyborgs More than just entertainment Physical interaction with the digital eco system
  57. 57. 3D Printing Additive manufacturing Batch of one Flexible Expensive Ora by cskk on Flickr (CC-BY)
  58. 58. We produce vast amounts of data Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr
  59. 59. All the time. Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr
  60. 60. So what can we do with all this data? Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr
  61. 61. Waze is based on the fact that everybody running the app automagically delivers data. No central ”traffic control”!
  62. 62. rced dsou ap row C nd m ic- a raf f t ata d Exa mp sha le of ring dat tha a wo rks t Man com y-to-m mu any nic atio n or f ee ers Fr um ns co
  63. 63. Data layers that could be applied in freight city apa C dar ra ETA pro jec tion s Mat chm akin ck ne tle s ot tu B ta s g
  64. 64. t a iz it ig D n io Incre asing good s volu mes Opportunities New techn olog y al tic oli P st re te in Quad Aces by fitzsean on Flickr
  65. 65. Northern LEAD 
 Logistics Research Centre Founded by: Chalmers University of Technology University of Gothenburg Logistics and Transport Society LTS
  66. 66. What we do Northern LEAD coordinates and supports logistics research at Chalmers and University of Gothenburg in order to increase volume, quality and 
 relevance of the research stairs by Denis Jacquerye on Flickr
  67. 67. Tomorrow’s logistics. We are finding the answers. Around 70 researchers Five core research groups Collaboration between Chalmers and University of Gothenburg Research centre for sustainable logistics solutions Organises, facilitates, disseminates highly relevant logistics research
  68. 68. Five core research groups Industrial marketing & purchasing Logistics & Transport Physical Distribution Professors Visiting Professors Associate Professors Post docs Faculty PhD students Total 10 6 5 6 14 32 73 Production Logistics Optimization
  69. 69. Challenges and trends Environmental impact Focused areas Logistics and Production Networks Outcomes for policy and business Long Distance Transport Resource limitations Urban Transport Demographic changes Manufacturing and retail revolution Complexity and structural flexibility Volatility and risk Purchasing of transport Information, planning and control Service development in networks Intermodality Resource utilisation Measurements and measuring Thought leadership through high quality research and innovation
  70. 70. Project 1: TRINFO
  71. 71. Project 1: TRINFO
  72. 72. Project 1: TRINFO
  73. 73. Project proposal: Smart access/guidance control
  74. 74. Project proposal: Smart access/guidance control
  75. 75. Project proposal: Smart access/guidance control
  76. 76. Project proposal: Smart access/guidance control
  77. 77. Project proposal: Smart access/guidance control
  78. 78. Project proposal: Smart access/guidance control
  79. 79. haring Data s Exp del andi iver ng y fr ont ic am uts yn tc D or sh Foliate d transp ortatio n netwo rk nd by Sta ents shipm S me o r he ot Realtime applications nt V2I Intellige ication ommun c Super Cat by Photo Extremist on Flickr oon lat g P kin par
  80. 80. Not all ideas age with grace
  81. 81. Someone must do the work
  82. 82. Not everyone will want to adopt new things…
  83. 83. …or change habits
  84. 84. From order to invoice Basic data From/To/What/When Owner: the customer Resource allocation What vehicle?
 Owner: Traffic controller Cargo information Loaded amount Owner: Supplier Proof of Delivery Time/date/signature Owner: Driver Pricing Owner: Financial dept. Enough information to create invoice All of these steps cost money!
  85. 85. An increase in the number of orders lead to increased cost Total cost for administration of all orders Goal: De-couple the dependecy between administative cost and order volume Handle exceptions – not transactions! Number of orders per year
  86. 86. 2 hours 4 hours 2 hours 1989:A FULL TIME JOB! CC-­‐BY  Per  Olof  Arnäs Technology  Management  and  Economics   Logis4kcs  and  Transporta4on
  87. 87. 0 hours 1-2 hours 0 hours 2013: TWO HOURS. MAX. CC-­‐BY  Per  Olof  Arnäs Technology  Management  and  Economics   Logis4kcs  and  Transporta4on
  88. 88. How  will  we  use  the  technology  in  10  years? so e m We have no idea. ! ! Per Olof Arnäs per-olof.arnas@chalmers.se about.me/perolofarnas @Dr_PO Slides published on slideshare.net/poar The girl and the iPad by Niclas Lindh on Flickr (CC-BY)
  89. 89. Exklusiv förhandsvisning av ny design som kommer inom kort! Exclusive preview of the new design that will be released shortly! Kolla gärna in min crowdsourcade logistikblogg Logistikfokus.se (Sveriges första och troligtvis enda) Be sure to check out my crowdsourced logistics blog Logistikfokus.se (Sweden’s first and probably the only one) Yes, It’s in Swedish but Google Translate works wonders these days ;-)

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