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T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

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T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

  1. 1. WP5: Forest information system development Task 5.4 – Short-term optimization: operational, ongoing and contingency planning Kühmaier M, Stampfer K Institute of Forest Engineering, University of Natural Resources and Life Sciences, Vienna Kick‐off Meeting   8‐9/jan/2014 
  2. 2. Activities and partners (1)  Definition of requirements for short‐term  harvesting schedules MHG, BOKU  Stand and tree selection  Machine capacities and demand  Workforce  Implementing just‐in‐time approach ITENE, MHG  Delivering products when they are needed  Reducing storage and buffers  Avoiding to run out of stock
  3. 3. Activities and partners (2)  Definition of procedures for ongoing management  activities TRE  Standard operations  Modifications are possible  Contingency plans  BOKU, MHG  Definition of risks  Actions in case of emergency or system failures  Multicriteria approach CNR, BOKU  Considering biodiversity and forest integrity
  4. 4. Timeline and participants 2014 2015 2016 J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D Start: June 2015 End: March 2016 D5.04 Short‐term optimization module of the FIS BOKU  Duration: 10 months, workload: 14 months  Task leader: BOKU (2)  Participants: CNR (3), MHG (3), TRE (3), ITENE  (2), GRAPHITECH (1) 4
  5. 5. Dependencies between activities WP2 Forest information collection WP3 Harvesting systems T.3.3, T.3.5 T.2.4, T.2.5 T.5.4 T.5.5 Mid‐long term optimization WP6 System  Integration 5
  6. 6. Risks  Implementation of existing or development of new  model into FIS  Available information for the daily planning  Interactive determination of cable corridors is a  challenging task  Just‐in‐time approach is hard to realize in the  forestry supply chain 6
  7. 7. Optimization models Kanzian et al. (2013) 7
  8. 8. Supply network Biomass Supply Network Forest (P) Terminal (T) Shipping Station (S) Plant (H) Kanzian et al. (2013) 8
  9. 9. Results – Pareto Curve Increasing profit Kanzian et al. (2013) 9
  10. 10. Results – Road transport distance Volume weighted  transport distance  increases from 45.7 to 48.1 km Increasing profit Kanzian et al. (2013) 10
  11. 11. Terminals and shipping stations Locations with minimal CO2 emissions 261 Terminals with an average of 650 odt/a 27 Shipping stations with an average of 2000 odt/a Kanzian et al. (2013) 11
  12. 12. Sensitivity analysis with profit Behavior on changing profit of solid delivered fuel Kanzian et al. (2013) 12

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