Slope wp5 by MHG

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 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


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:

Technology

Slope wp5 by MHG