Transcript
Project SLOPE1
WP 5 – Forest information systemdevelopment
WP5. Forest information system development
Kick-off Meeting 8-9/jan/2014
•Task 5.1 Database to support novel inventory data content – MHG• Partners: GRAPHITECH, CNR, COAST, FLY, TRE, ITENE• MHG Portal Platform with MHG Biomass Manager and Iptim integration as a basis• M08-M17
• Task 5.2 Platform for near real time control of operations–TRE• Partners: GRAPHITECH, CNR, MHG, TRE, ITENE• M11-M22
Task’s objective is to develop a system (MHG) for near real time control of operations that integrates the information about the timber material origin, quality and quantities being processed along the supply chain in order to optimize procedures and avoid delay times in operations (i.e. manage transport fleet in order to avoid saturation of storage areas at the cable crane landing).This will be achieved by the implementation of a series of different interfaces to access the FIS and allow a number of different operations• Note! Utilization of features and scalability of current services like the Forest Warehouse, MHG Biomass Manager, MHG Mobile and Iptim
WP5. Forest information system development
Kick-off Meeting 8-9/jan/2014
• Task 5.3 Online purchasing/invoicing of industrial timber and biomass – MHG• Partners: GRAPHITECH, CNR, TRE, ITENE• M19-M28• Huge field for development!
• Task 5.4 Short-term optimization–BOKU• Partners: CNR, MHG, TRE, ITENE• M18-M27• Note! Utilization of Iptim´s features and scalability
• Task 5.5 Mid-long term optimization; strategic and tactical planning - MHG• Partners: GRAPHITECH, FLY, TRE, ITENE• M18-M27• Note! Utilization of Iptim´s features and scalability
T.5.5 – Mid-long term optimization; strategic and tactical planning
Kick-off Meeting 8-9/jan/2014
MHG Systems• Our state of the art
• Simulation and optimisation framework• Simple user interface for the complex problem
• Beyond state of the art• Simulations: growth models• Simulations: management regimes• Optimisation
Our state of the art: computation
Kick-off Meeting 8-9/jan/2014
Long term planning using the SIMO framework for predicting alternative future states of forest stands using simulation, and using mathematical optimisation to select the best alternatives based on the objective and constraints for forest management.
The framework has been validated in Finland where the framework is in operational use on close to all of the 26 million ha of forest land.
Key features of the framework:• Adaptable: no fixed data model, type of silviculture or growth models, any of
these can be configured• Extensible: it has been used from tree plantations in Africa to boreal forest in
Finland
Our state of the art: UI
Kick-off Meeting 8-9/jan/2014
Iptim:• Long term planning Decision Support System built on top of the SIMO
framework• Design goal: “Excel like user experience for forest planning without sacrificing
the power of describing the complex phenomenon”
The design goal expressed by putting the user in control of:• The data model for forest inventory data• The baseline definition of how forests are managed; the management regime• The growth models on which the simulation is based;
• possibility to create user’s own growth models in situations where there’s scarce research literature found
• Adopt specific models from research, calibrate with your own data if necessary
Kick-off Meeting 8-9/jan/2014
Iptim – UI examples (1)
Kick-off Meeting 8-9/jan/2014
Iptim – UI examples (2)
Kick-off Meeting 8-9/jan/2014
Iptim – UI examples (3)
Beyond state of the art
Kick-off Meeting 8-9/jan/2014
Growth models: • Integrate state of the art growth models from research literature for the
demonstration areas (from Task ?.? / ?)
Management regimes:• Integrate baseline forest management regime for mountain forests (from Task
5.4 / BOKU)
Optimisation:• Bridging the gap between strategic (long term) and tactical (mid term)
planning• From tactical to operational• Risk management
Kick-off Meeting 8-9/jan/2014
Typical strategic plan
Long term plans are typically “shot gun” solutions; i.e. there is no spatial aspect in the solution, the stands to harvest are “all over the place”.This is especially true for plans for areas bigger than couple of hundred/thousand hectares.
Kick-off Meeting 8-9/jan/2014
A feasible tactical plan
That kind of plan is not ready for operation as such, yearly replanning needed to have something realistic to execute for that year. Currently lack of tools at this level.Let’s introduce the spatial constraints already at the strategic phase=> guarantee that our long term plan really is feasible=> shorten the planning cycle & gain visibility for resource and infrastructure demand
Kick-off Meeting 8-9/jan/2014
From tactical to operational
“Gain visibility for resource and infrastructure demand” taken one step further: introduce infrastructure, machine and workforce capacity as parameters in the planning problem• Identify production bottlenecks prior to running into them in operations• Plan harvesting, infrastructure investments and capacity investments
concurrently
Same framework spans from strategic to operational planning; possibility to use subsets of the functionality for optimising operational plans (workforce and machine capacity utilisation including logistics)
A note about contingency planning
Kick-off Meeting 8-9/jan/2014
Introducing uncertainty analysis and risk management already at the planning level.• Monte Carlo simulation for introducing the effects of uncertainty of different
components in the plan at the simulation stage• Robust optimisation for introducing the uncertainties at the optimisation
stage=> Tools for the planner to take their position on risk already at the long term planning stage
Kick-off Meeting 8-9/jan/2014
Timeline and deliverablesAugust 2014 January 2015 January 2016
WP5. Forest information system development M08 M09 M10 M11 M12 M13 M14 M15 M16 M17 M18 M19 M20 M21 M22 M23 M24 M25 M26 M27 M28
T.5.1. Database to support novel inventory data content x x x x x x x x xX
D5.01 Inventory module for the FIS: MHG
T.5.2. Database to support novel inventory data content x x x x x x x x x xx
x
D5.02 Real-time supply chain control module of the FIS: TRE
T.5.3. Online purchasing/invoicing of timber and biomass x x x x x x xx
x x
D5.03 Platform for purchasing/invoicing: MHG
T.5.4. Short-term optimization: operational planning x x x x x x x x x x
D5.04 Short-term optimization module of the FIS: BOKU
T.5.5.Mid-long-term optimization: strategic and tactical x x x x x x x x x x
D5.05 Mid-long-term optimization module of the FIS: MHG
Annual meeting
Project meeting
Skype
Kick-off Meeting 8-9/jan/2014
Communication and risk control
• Timeframe months: M08-M28• Strict schedule, real-time information sharing needed
• Communication• Skype in 2-3 weeks & physical meetings every two months• Communication platform • Immediate access to current services for key persons in
order to innovate; MHG Biomass Manager, MHG Mobile Iptim, Forest Warehouse etc.
• Person in charge• ITENE:• GRAPHITECH• CNR:• COAST:• BOKU:• FLY:• TRE:
Kick-off Meeting 8-9/jan/2014
Communication and risk control
• Timeframe months: M08-M28• Strict schedule, real-time information sharing needed
• Communication• Skype in 2-3 weeks & physical meetings every two months• Communication platform • Immediate access to current services for key persons in
order to innovate; MHG Biomass Manager, MHG Mobile Iptim, Forest Warehouse etc.
• Person in charge• ITENE:• GRAPHITECH• CNR:• COAST:• BOKU:• FLY:• TRE:
WP 5.2: Platform for near real time control of operations
• Harvest Planning System
• Harvest Management System (RTFI)
Our Offering
Harvest Machine Control (RTFI, Real Time Forest Intelligence)Satcom, GPRS, GPS
Real Time Forest Intelligence
Dynamic harvest control
Cooperative machining Multiple machines working as a team Combinatorial problem Managing the trade-off’s
Million's of harvested trees are stored for real time analysis
Treemetrics
www.treemetrics.com
ekeane@treemetrics.com
T.5.3. Online purchasing/invoicing of industrial timber and biomass
Kick-off Meeting 8-9/jan/2014
Partners: GRAPHITECH, CNR, TRE, ITENE
MHG Systems• Current project
• Simulation and optimisation framework (EEP Indonesia)• Strategy to move on
• Benchmarking of partners´ solutions and services and trading/feedstock platforms and services globaly like:• Finland; www.puukauppa.fi• http://www.balbic.eu/en/current/2012-
2013/en_GB/simulator_intro/• Alberta (feedstock information platform), St. Petersburg (waste
platform), USA (Commerce Platform) etc.
Plugin module development
Kick-off Meeting 8-9/jan/2014
Using the MHG Portal Platform on top the online purchase/sell platform is developed as a plugin module and select the best technologies/attractive features based on the bench-marking results and consortium´s decision taking account instant market demand and potential
Close linkage with the Forest Warehouse data and analysis (TRE)
Key features of the service:• Easy-to-use • Scalable: new features easily integrated/developed • Extensible: should be working anywhere with any kind of timber/feedstock
Initiative features and players 1
Kick-off Meeting 8-9/jan/2014
Group sell
Contractors/Service providers
Buy Timber &Feedstock
Sell Timber& Feedstock
Equipment
Profile matching
Price Info
Climatic DataSocial
Networking
Phytosanitary
Commerce Platform Information hub
SustainabilityMobile
Application
Buy/sell Estates/ Cutting areas
Subscriptions/Transactions
Taxation
Resource/Volume/Quality Analysís
Pre-sales/Auctions
Certification Etc.
Etc.
Initiative features and players 2
Kick-off Meeting 8-9/jan/2014
Data LayersGeospatial Fields and Forests WMS (Web Map Service)
DatabasesConversion FacilitiesTimber&biomass ProducersEquipment and Service Vendors
PartnersInsuranceLegalLogisticsLaboratoriesSustainabilityPhytosanitary
Demo area needed with real detaildata, producers and end-users!To be agreeded in Trento (and/orother?) region
Note! This is a huge Service package entity - market-oriented approach a must (dueto limited financial resources in Slope)
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
Activities and partners (1)
Avoiding to run out of stock
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
Activities and partners (2)
Considering biodiversity and forest integrity
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
Timeline and participants
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)
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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
Dependencies between activities
T.5.4
WP2 ForestinformationcollectionT.2.4, T.2.5
WP6 System Integration
WP3 Harvesting systemsT.3.3, T.3.5
T.5.5 Mid-long term optimization
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Risks
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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
Optimization models
Kanzian et al. (2013)
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Supply network
Terminal (T)
Plant (H)
Biomass Supply Network
Forest (P)
Shipping Station (S)
Kanzian et al. (2013)35
Results – Pareto Curve
Increasing profit
Kanzian et al. (2013)
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Results – Road transport distance
Volume weighted transport distance
increases from45.7 to 48.1 km
Increasing profitKanzian et al. (2013) 10
Terminals and shipping stationsLocations with minimal CO2emissions
Kanzian et al. (2013) 38
261 Terminals with an average of 650 odt/a
27 Shipping stations with an average of 2000 odt/a
Sensitivity analysis with profitBehavior on changing profit of solid delivered fuel
Kanzian et al. (2013) 39
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