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

eee |

tjimkscKcKSddpp mt

s

jt

s

t

c

it

c

kit

c

it

c

kit

c

kb ,,,,,,|,,,,,,

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