Kick-Off Meeting - WP5

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


• 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


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


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


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


Iptim – UI examples (1)





Beyond state of the art


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


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.


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


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


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


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


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:


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

[email protected]

T.5.3. Online purchasing/invoicing of industrial timber and biomass


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.

http://www.puukauppa.fi/

http://www.balbic.eu/en/current/2012-2013/en_GB/simulator_intro/

Plugin module development


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


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


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


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

32

Risks

33

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)35

Results – Pareto Curve

Increasing profit

Kanzian et al. (2013)

36

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

Education

Kick-Off Meeting - WP5