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Planning Forest Value Chain under Uncertainties Sophie D’Amours Scientific director, VCO NSERC Strategic Network Director, FORAC Research Consortium Canada Research Chair on Planning Sustainable Forest Networks Université Laval, Québec, QC, Canada
Agenda
• Value Chain Concepts
• Planning Value Chains
• Planning under uncertainties
• Concluding remarks
2
FORAC Research Consortium
3
Domtar Windsor
4
5
6
FOREST (e.g. suppliers, entrepreneurs)
PRODUCTION&DISTRIBUTION (e.g. mills, carriers, warehouses)
MARKET (e.g.customers, builders, printers)
Coordination mechanisms
Coordination mechanisms
Approaches to couple the value chains
• Market
• Auction
• Legislation/standardization
• Tenure, NLGA, PapiNet
• Design
• Integrator, broker, value added merchandizing yards
• Contract
• Volume-based, Buy-back, logistics
• Plan, mutual adjustment and collaboration
• Information exchange, joint planning and/or execution, joint venture
Alternative Divergent Processes • Trees are cut to produce a set of logs
• Logs are cut to produce a set of lumber
• Chips are mixed to produce different grades of pulp and paper
• Rolls are cut to produce a set of rolls or sheets
Recipe/cutting pattern Recipe/cutting pattern
Recipe/cutting pattern
Productivity not always linear
Sequence dependent set-ups
Attribute based
products/ecoservices
Attribute based
products/ecoservices
Forest, Industry, Energy and Environment Policies
Integrative Planning
Operative Planning
Forest, Assets and Value Proposition Management
Forest and industry policies
Spatially located assets, long term
forest management decisions,
value propositions
Resources allocation, rules and
operative policies
Aggregated information
on resources (capacity, efficiency),
demand (markets, customers, behaviors),
Supply (availability)
Forest and industry status
Macro socio-economic
models of the forest, demand
and resources on a global
scale
Execution updates Schedules and
commitments
Forest
operations
Inbound
logistics
Mills
logistics
Outbound
logistics
Sales
operations
Governments &
Communities
Companies
The wood supply chain network
Forests
Sawmills
Kilns
Furniture mills
Wood Supply chain
Public forest
Private forest
Warehouses
Retailers Customers
External
sawmillExternal
kiln
Source
(Buyer)
Source
(Buyer)
Source
(Buyer)Dry wood
supplier
The customer demand configuration did not fit with the sawing policies used and the hardwood logs procured by suppliers.
The sawing and drying capacities were sufficient, no need to outsource
Inventory went down while capturing the seasonality of customer demand and supplier capacity.
• Some specific products should be bought from the wood market
Manual
solution
Heuristic
solution
Variation
(Manual vs
heuristic)
Raw material
cost
48.1% 30.92%
Sawing cost 30.79% 23.04%
Drying cost 3.88% 3.33%
Inventory cost 3.29% 1.42%
Transportation
cost
6.36% 4.79%
Outsourcing
cost
2.01% 0.00%
Wood market 5.54% 36.51%
Total 100% 100% 22%
Uncertainties
14
FORAC Research Consortium The design of robust value-creating supply chain networks: A critical review
Klibi, Martel and Guitouni
VC Drivers when dealing with uncertainties
• Responsiveness
• capability of a VC to respond positively to variations to environmental uncertainties
• Robustness
• the quality of a VC to remain effective for all plausible futures
• Resilience
• the capability of a VC to respond positively to avoid disruptions or quickly recover from failures
15
FORAC Research Consortium
16
Scenario planning Structured brainstorming, Experts interview,
Qualitative forecasting methods (eg. Delphi), etc..
Designing under uncertainties Collaborative and anticipative planning,
Stochastic programming, Robust
optimization, Queuing theory,
Simulation, Design methods, etc…
Proactive and real-time planning Scheduling, Dispatching,
Agent-based planning, etc…
Hedging, Adaptive and Resilience
based Design Solutions and short term key drivers
Policy for value maximization
(Long term strategic issues)
Using plausible futures, model of social
expectations, stochastic and behavioral
models, benchmarking and decision support
Optimal design for value creation
(Long and mid term strategic issues)
Using strategic key drivers, stochastic
and behavioral models, benchmarking
and decision support
Optimal operations for value capture
(Short term operational issues)
Using short term key drivers,
stochastic and behavioral models,
benchmarking and decision support
Policies, plausible futures and
strategic key drivers for VCO
Executable plans
17
FORAC Research Consortium
Energy 2050
Integrated Bio-energy and Forest Products
Supply Chain Framework
18
Forestry
Logs
Lumber OSB
Plywood Pulp &
paper MDF,
particleboard
Process residues
Process
residues
Consumers
Sawmill
OSB mill
Plywood
mill
Pulp &
paper mill
MDF, PB
mills
Logs
Logs
Logs
Logs
Urban wood
wastes
Pellet plant
Power plant
Consumers
Consumers Chemical plant
Forest biomass
Forest
residues
Forest residues
Pellets
Pellets
Ethanol,
bio-diesel,
chemicals
Electricity,
heat
Residues
Energy
Forest products
Bio-energy and bio-fuel
Chemical plant
Power plant
Pellet plant
Power supplies
(electricity, gas, coal)
19
G2
G1
Market2
Pulp mill
Results and Discussions
Wood_sup3
Market1
Pulp: 250,000 ton
Boiler: 11 MW
CHP: 42 MW
Pellet: 40,000 ton
Chipper: 400,000 ton
Pulp logs
CHP: 34 MW
Sawmill2
Wood_sup1
Wood_sup2
CHP: 34 MW
Pellet: 100,000 ton
Heat
Heat, pulp liquor
Power supplies
(electricity, gas, oil, coal)
20
FORAC Research Consortium
The design of robust value-creating supply chain networks: A critical review
Klibi, Martel and Guitouni
Scandinavia
Russia
Finland
Scandinavia
Austria
Germany
Industrial context
Material flow
OSB plants
Information flow
)(RDelivery
s
Ltm,rm, srm
)(X Purchasing s
tm,rm,
)(d Demand c
it
)(XShipment s
irvt
(Contract, non-contract)
(Contract, non-contract)
Design contracts offer to the customers and suppliers
• The problem is to optimize the best set of contracts to offer to the customers and the suppliers
• Maximizing revenue in a context of varying economic conditions and business scenarios
• Balancing supply, production and distribution capacity
Flow modeling
Scenario building
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tjimkscKcKSddpp mt
s
jt
s
t
c
it
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be
Scenario Based Stochastic Programming Model First stage program
27
FORAC Research Consortium
Second stage program
• Maximize expected profits under a scenario ω
• Subject to:
• Constraints concerning sales
• Constraints concerning production and distribution
• Constraints concerning procurement
• Valid cuts (aggregate flow balance over manufacturing sites)
28
FORAC Research Consortium
Results
Experimental platform: Project
• Objective:
• To develop a multi-agent planning platform, specialised for divergent processes, based on a service oriented architecture (SOA) and controlled by events.
• Usages:
• To model value chains in the lumber industry
• To test different control and planning methods
FORAC Research Consortium
Sawing Drying Finishing
Distributor Typical sawmill Customer
Experimental platform
Forest
Experimental platform: Agents
• Specific control methods adapted to the business unit
• Synchronization realized through interaction with other agents in the network
• Distributed planning concept using multi-agent systems
33
FORAC Research Consortium
Different problems, different solving approaches
Simu
lation
Mo
nito
ring
Imp
ort / Exp
ort
Business logic
Object Model
Flow Manager
Event Manager
Task Manager
Conversation Manager
User interaction
User
Web Controls
Data and Communication
Factory Incoming Queue
Outgoing Queue
Databases Messaging Services
Agent Architecture
Sawing Agent
One-to-many processes
planning and scheduling
Mixed Integer Program
OR Component
Drying Agent
Many-to-many batch processes
planning and scheduling
Constraint programming
OR Component
Finishing Agent
One-to-many processes
planning and scheduling
Heuristic / Constraint
programming
OR Component
Deliver Agent
Transport Management
Mixed Integer Program
OR Component
Drying Agent Supply agent
Offer
Offer Accepted
Offer Refused
Need
Conversation
Offer
Offer Accepted
Offer Refused
Need
Conversation
Offer
Offer Accepted
Offer Refused
Need
Conversation
Workflow
Engins en approvisionnement infini
Allocations
Engins en approvisionnement fini
Allocations
Workflow
Engins en approvisionnement infini
Allocations
Engins en approvisionnement fini
Allocations
Workflow
Engins en approvisionnement infini
Allocations
Engins en approvisionnement fini
Allocations
Planning
Event
New Customer
Demand
Event
New Supplier
Demand
Event
New Supplier
Supply
Event
New Customer
Supply
© FOR@C – experimental platform
Revenu en fonction de la segmentation de la clientèle
$2.00
$2.10
$2.20
$2.30
$2.40
$2.50
$2.60
$2.70
$2.80
$2.90
$3.00
0% 20% 40% 65%
Millio
ns
Pourcentage de clients contratractuels
Re
ve
nu
me
ns
ue
l
Revenue as a function of % of contracted volume
under a ATP strategy
% of contracted volume
Mo
nth
ly r
even
ue
Concluding remarks
• Planning the value chain is a challenged without uncertainties…
• Major efforts are required to understand the expected value of perfect information (EVPI) and its usage within the decision making process
• Major efforts are required to process a framework to value chain optimization within the forest sectors in order to meet the social, economic and environment expectations
• The emerging field of collaborative and anticipative planning might be of help in dealing with the “chain of uncertainties”
39