CC-BY PER OLOF ARNÄS
UNSOLVED PROBLEMS IN
FREIGHT TRANSPORT
CLIMBING THE THREE
MOUNTAINTOPS OF
REAL-TIME DATA
Per Olof Arn...
Northern LEAD 

Logistics Research Centre
Founded by:
Chalmers University of Technology
University of Gothenburg
Logistics...
Northern LEAD coordinates and supports logistics
research at Chalmers and University of Gothenburg
in order to increase vo...
Tomorrow’s logistics. We are finding the answers.
Around 70 researchers
Research centre for
sustainable logistics
solution...
Physical
Distribution
Production
Logistics
Industrial marketing
& purchasing
Logistics &
Transport
Optimization
Professors...
Thought leadership
through
high quality
research and
innovation
Challenges
and trends
Outcomes for
policy and
business
Vol...
Per Olof Arnäs
The Transport
industry
3 things:
Carbon-free transport by Stéfan on Flickr
…physical
3d boxes by crystaljingsr on Flickr
Technology	
  Management	
  and	
  Economics	
  
Logis4kcs	
  and	
  Transporta4onCC-­‐BY	
  Per	
  Olof	
  Arnäs
…public
...
Technology	
  Management	
  and	
  Economics	
  
Logis4kcs	
  and	
  Transporta4onCC-­‐BY	
  Per	
  Olof	
  Arnäs
…analogu...
Per Olof Arnäs Stage Coach Wheel by arbyreed on Flickr
Development of transportation
technology has been
fairly linear
…fo...
We are in the middle of a gigantic
exponential development curve
beginning
A new global eco system where new
types of, knowledge based, industries
compete with traditional ones
http://bryce.vc/post/18404303850/the-problem-with-innovation
Startups don’t compete with airlines...
by purchasing a bunch...
Startups compete with airlines by
inventing videoconferencing.
http://bryce.vc/post/18404303850/the-problem-with-innovatio...
RESOURCE UTILISATION LOW
Safety imbalance
Variation in resource demand
Chain imbalance
Caused by the chain
Technological imbalance
E.g. mismatch in...
Safety imbalance
Variation in resource demand
Chain imbalance
Caused by the chain
Technological imbalance
E.g. mismatch in...
InSearchOfLostTimebybogenfreundonFlickr
But the biggest problem
in transportation is time.
There is not enough of it.
Ever.
The transport industry
does not like real-time
decisions.
At all.
DSC_9073.jpg by James England on Flickr (CC-BY)
The transport industry
does not like real-time
decisions.
At all.
Batch-handling
Zip codes
Zones
Time-tables
DSC_9073.jpg ...
Image: Alain Delorme, alaindelorme.com
The current model is
focused on economy of
scale and standardization
Image: Alain Delorme, alaindelorme.com
The current model is
focused on economy of
scale and standardization
The current paradigm
So…
What are we
doing about
all this?
CC-BY PER OLOF ARNÄS
Strategic Tactical Operational Predictive
Time horizons
We are approaching
this boundary
…and we are
...
Digitization fronts
Goods Vehicle
Business
process
Infra-
structure
Goods Vehicle
Business
process
Infra-
structure
Barcodes	
  
RFID	
  
Sensors
ERP systems	
  
TMS systems	
  
E-invoices	
...
CC-BY PER OLOF ARNÄS
Business
processes
Infra-	

structure
Paperbased
Phone

Papers
Road
signs
A
nalogue
tools
R
D
S
M
oni...
Goods
Vehicles
Business
processes
Infrastructure
Stra-
tegic
Tac-
tical
Opera-
tional
Pre-
dictiveWhat happens
when access...
http://www.gartner.com/newsroom/id/2575515
Source: Gartner August 2013
Augmenting
humans with
technology
Machines
replacin...
http://www.gartner.com/newsroom/id/2575515
Source: Gartner August 2013
Gartners Hype Cycle for Emerging Technologies
http://www.gartner.com/newsroom/id/2575515
?
Source: Gartner August 2013
Gartners Hype Cycle for Emerging Technologies
Tra...
Opportunities
Digitization Increasinggoods volumes
New
technology
Political
interest
Quad Aces by fitzsean on Flickr
CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
3 mountaintops to climb…
CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Fixed Historical
3 data types
Mountaintop #1
Collec...
CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
5 data domains
Vehicle CargoDriver Company
Infrastr...
Length

Weight

Width

Height
Capacity

+ other PBS-criteria
Emissions

Fuel consumption

Route
Position

Speed

Direction...
CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #2
Processing of data in real-time
Loca...
CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #2
Processing of data in real-time
CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #3
Exploiting data in real-time
Connect...
CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #3
Exploiting data in real-time
Boeing-...
CASES

(MANY)
CASES 

(MANY MORE)
Challenges
The Challenger by Martín Vinacur on Flickr (CC-BY)
The Challenger by Martín Vinacur on Flickr (CC-BY)
Not all ideas age with grace
The Challenger by Martín Vinacur on Flickr (CC-BY)
Someone must do the work
The Challenger by Martín Vinacur on Flickr (CC-BY)
Not everyone will want to
adopt new things…
CC-BY PER OLOF ARNÄS
UNSOLVED PROBLEMS IN
FREIGHT TRANSPORT
CLIMBING THE THREE
MOUNTAINTOPS OF
REAL-TIME DATA
Per Olof Arn...
Unsolved problems in freight transport - climbing the three mountaintops of real-time data
Unsolved problems in freight transport - climbing the three mountaintops of real-time data
Unsolved problems in freight transport - climbing the three mountaintops of real-time data
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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. 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. 2. Northern LEAD 
 Logistics Research Centre Founded by: Chalmers University of Technology University of Gothenburg Logistics and Transport Society LTS
  3. 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. 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. 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. 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. 7. Per Olof Arnäs The Transport industry 3 things: Carbon-free transport by Stéfan on Flickr
  8. 8. …physical 3d boxes by crystaljingsr on Flickr
  9. 9. Technology  Management  and  Economics   Logis4kcs  and  Transporta4onCC-­‐BY  Per  Olof  Arnäs …public Traffic Jam by Giorgio Minguzzi on Flickr
  10. 10. Technology  Management  and  Economics   Logis4kcs  and  Transporta4onCC-­‐BY  Per  Olof  Arnäs …analogue 542 miles by Jason on Flickr
  11. 11. Per Olof Arnäs Stage Coach Wheel by arbyreed on Flickr Development of transportation technology has been fairly linear …for the last 5500 years
  12. 12. We are in the middle of a gigantic exponential development curve beginning
  13. 13. A new global eco system where new types of, knowledge based, industries compete with traditional ones
  14. 14. 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
  15. 15. 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.
  16. 16. RESOURCE UTILISATION LOW
  17. 17. 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
  18. 18. 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
  19. 19. InSearchOfLostTimebybogenfreundonFlickr But the biggest problem in transportation is time. There is not enough of it. Ever.
  20. 20. The transport industry does not like real-time decisions. At all. DSC_9073.jpg by James England on Flickr (CC-BY)
  21. 21. 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)
  22. 22. Image: Alain Delorme, alaindelorme.com The current model is focused on economy of scale and standardization
  23. 23. Image: Alain Delorme, alaindelorme.com The current model is focused on economy of scale and standardization
  24. 24. The current paradigm
  25. 25. So… What are we doing about all this?
  26. 26. 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!
  27. 27. Digitization fronts Goods Vehicle Business process Infra- structure
  28. 28. 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
  29. 29. 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
  30. 30. 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)
  31. 31. 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
  32. 32. http://www.gartner.com/newsroom/id/2575515 Source: Gartner August 2013 Gartners Hype Cycle for Emerging Technologies
  33. 33. http://www.gartner.com/newsroom/id/2575515 ? Source: Gartner August 2013 Gartners Hype Cycle for Emerging Technologies Transportation/ logistics?
  34. 34. Opportunities Digitization Increasinggoods volumes New technology Political interest Quad Aces by fitzsean on Flickr
  35. 35. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) 3 mountaintops to climb…
  36. 36. 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
  37. 37. 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
  38. 38. 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
  39. 39. 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
  40. 40. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY) Mountaintop #2 Processing of data in real-time
  41. 41. 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)
  42. 42. 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)
  43. 43. CASES
 (MANY)
  44. 44. CASES 
 (MANY MORE)
  45. 45. Challenges The Challenger by Martín Vinacur on Flickr (CC-BY)
  46. 46. The Challenger by Martín Vinacur on Flickr (CC-BY) Not all ideas age with grace
  47. 47. The Challenger by Martín Vinacur on Flickr (CC-BY) Someone must do the work
  48. 48. The Challenger by Martín Vinacur on Flickr (CC-BY) Not everyone will want to adopt new things…
  49. 49. 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)

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