t.5.4 – short-term optimization: operational, ongoing and contingency planning (by boku)

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WP5: Forest information system development Kickoff Meeting 89/jan/2014 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

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Page 1: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

WP5: Forest information system development

Kick‐off Meeting  8‐9/jan/2014 

Task 5.4 – Short-term optimization: operational, ongoing and contingency planning

Kühmaier M, Stampfer KInstitute of Forest Engineering, University of Natural Resources and Life Sciences, Vienna

Page 2: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

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

Page 3: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

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

Page 4: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

Timeline and participants

Duration: 10 months, workload: 14 months

Task leader: BOKU (2)

Participants: CNR (3), MHG (3), TRE (3), ITENE (2), GRAPHITECH (1)

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2014 2015 2016J 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 optimizationmodule of the FIS BOKU

Page 5: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

Dependencies between activities

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T.5.4

WP2 ForestinformationcollectionT.2.4, T.2.5

WP6 System Integration

WP3 Harvestingsystems

T.3.3, T.3.5

T.5.5 Mid‐long termoptimization

Page 6: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

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

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Page 7: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

Optimization models

7Kanzian et al. (2013)

Page 8: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

Supply network

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Biomass Supply Network

Terminal (T)

Plant (H)

Forest (P)

ShippingStation (S)

Kanzian et al. (2013)

Page 9: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

Results – Pareto Curve

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Increasing profit

Kanzian et al. (2013)

Page 10: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

Results – Road transport distance

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Volume weighted transport distance increases from45.7 to 48.1 km

Increasing profitKanzian et al. (2013)

Page 11: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

Terminals and shipping stations

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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)

Page 12: T.5.4 – Short-term optimization: operational, ongoing and contingency planning (by BOKU)

Sensitivity analysis with profit

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Behavior on changing profit of solid delivered fuel

Kanzian et al. (2013)