Project SLOPE
1
WP 5 – Forest information system
development

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 deliverables
August 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 x
X
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 x
x
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 x
x
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, RealTime Forest Intelligence)
Satcom, GPRS,GPS

RealTime 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
Sustainability
Mobile
Application
Buy/sell Estates/
Cutting areas
Subscriptions/Tra
nsactions
Taxation
Resource/Volume
/Quality Analysís
Pre-sales/
Auctions
Certification Etc.
Etc.

Initiative features and players 2
Kick-off Meeting
8-9/jan/2014
Data Layers
Geospatial Fields and Forests
WMS (Web Map Service)
Databases
Conversion Facilities
Timber&biomass Producers
Equipment and Service
Vendors
Partners
Insurance
Legal
Logistics
Laboratories
Sustainability
Phytosanitary
Demo area needed with real detail
data, producers and end-users!
To be agreeded in Trento (and/or
other?) region
Note! This is a huge Service
package entity - market-
oriented approach a must (due
to limited financial resources in
Slope)

WP5: Forest information system development
Kick‐offMeeting
8‐9/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

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)
3
1
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

Dependencies between activities
T.5.4
WP2 Forest
information
collection
T.2.4, T.2.5
WP6 System
Integration
WP3 Harvesting
systems
T.3.3, T.3.5
T.5.5 Mid‐long term
optimization
32

Risks
3
3
 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)
34

Supply network
Terminal (T)
Plant (H)
Biomass Supply Network
Forest
(P)
Shipping
Station (S)
Kanzian et al. (2013)
3
5

Results – ParetoCurve
Increasing profit
Kanzian et al. (2013)
36

Results – Road transport distance
Volume weighted
transport distance
increases from
45.7 to 48.1 km
Increasing profit
Kanzian et al. (2013) 10

Terminals and shipping stations
Locations with minimal CO2emissions
Kanzian et al. (2013)
3
8
261 Terminals with an average of 650 odt/a
27 Shipping stations with an average of 2000 odt/a

Sensitivity analysis with profit
Behavior on changing profit of solid delivered fuel
Kanzian et al. (2013)
3
9