Value Maximization and Decision Support (VMDS)

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December 3

rd

_{, 2014}

Jean Favreau, Research manager, Pointe-Claire

Presented by

Yu (Vivian) Li, Researcher, Vancouver

Value Maximization and Decision Support

(VMDS)

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© 2014 FPInnovations. All rights reserved. Copying and redistribution prohibited. ® FPInnovations, its marks and logos are tr ademarks of FPInnovations. © 2013 FPInnovations. Tous droits réservés. Reproduction et diffusion interdites. Les marques et les logos de FPInnovations sont des marques déposées de FPInnovations

Access to R&D knowledge from

400+ R&D Staff Covering the Full Forest Value Chain

2 Road &

Transportation

Fiber Supply

Inventory

Resource

Attributes

Harvesting

Systems

Wild Fire

Operations

EWP

Manufacturing

Secondary

Advanced

Building System

Paper, Packaging &

Consumer Products

Cellulosic

Biomaterials

Market Pulp

Wood

Biomaterials

Biorefinery &

Energy

Environment &

Sustainability

PIT

(3)

VMDS Program Objectives



Develop strong market pull industrial behavior



Direct the fiber at the right process facility at the right time in the

right form



Take advantage of the unique attribute of the fiber



Optimize the entire value chain from resource to market



Improve efficiency of the manufacturing sector

(4)

VMDS Main Research Themes

4 

Better fibre supply for the

industry



Improved value-based modules

in FPInnovations DSS tools



Innovative tools to improve

product flow efficiency



Agile and efficient

manufacturing



Integration of NSERC VCO

(5)

1. Better supply

5 

Strategies to apply “the right

fibre is sent to the right mill at

the right time at the right

cost”



Complex planning decisions

with better planning tools

(e.g. net value of forest

stands, wood allocation,

scheduling, better forest

inventory)

(6)

BC Bioeconomy - Fort St. James study



Objective: map distribution of

different categories of fibre

(sawlog, pulpwood, biomass)

over large areas



Green stands, no Lidar tree

heights



211 plots



Sampling intensity: 200 m

(direction of main change) * 400

m. Total area approx. 2,000 ha



Digital air photos to be available

in 2015

(7)

Total sawlog volume (pine l.,

spruce, and balsam) at each

plot (m

3 _/ha)

Digital Elevation

Model (TIN

representation) and

location of the 211

plots

(8)

Total sawlog volume

interpolated over the

study area (m

3 _/ha)

Map depicting the probability

that sawlog volume > 200

m

3 _/ha

(9)

2. Value tools

9 

Provide tools to help streamline supply

chains and maximize value from available

fibre



Develop practical, functional models for

the industry considering the entire value

chain



Provide tools to help companies evaluate

and leverage new bioproduct opportunities



Propose (“push”) new solutions to the

(10)

ForestPlan

Approach



Use ForestPlan to determine the

optimal harvest and log allocation

plan based on sawmill needs at

Tembec



Populate ForestPlan with forest,

road and sawmill data



Evaluate the impact of lumber

market fluctuations on log

allocation decisions to sawmills

Expected benefits



Potential benefits identified in a

case study on BC Coast are

approx. $1.5/m³

(11)

3. Products flow

11 

Solutions to provide efficient fibre flow



New tools to manage larger product mix

with shorter lead time and make

strategies to bring fibre from far or

remote areas



Better use of truck fleet and drivers to

supply mills and to overcome a lack of

manpower



Support implementation of efficient

multimodal transportation systems

(12)

Transportation Logistics

12 Transportation interacting with upstream and downstream activities

Forest

Forest operations

Inventory

Transport

Mill

Demand

Information

Market

Three main decisions

1. Allocation (Where)

2. Routing (How)

3. Scheduling (When)

Optimization

Simulation

(13)

FPInterface

TM

13 GIS-based simulation model to assess hauling

cost. A tool to analyze tactical and operational

plans.

(14)



Determining the backhaul potential

by sector



Calculating the savings by

company/product



Identifying the best routes



Evaluating the viability of solutions



Establishing transport rates for

complex situations

Implementing in Canfor and

Resolute Forest Products

to

identify backhaul opportunities and

reduce transportation cost

Optimizes transport by:

FPInterface

TM --

_MaxTour



Reduce 10-20 % of empty travel distances



Reduce 2-7 % of total transport cost

Mill A

Mill B

Mill C

_Loaded

Truck 1

(15)

Truck Scheduler (TS)

Forest

Forest operations

Roadside Inventory

Transport

Mill

Market

TSC:

Truck Scheduler for Company

TSD: Truck Scheduler for Drivers

Optimizes transport by:



Minimizing queuing time (waiting time) for log trucks



Determining

the back haul opportunities



Increasing driver satisfactory of working hours/shifts

(16)

Truck Scheduler:

Improve Log Truck Utilization

16

Forest to mill Mill to mill

D a sh b o a rd G a n tt C h a rt s C S V r e su lt s fi le s M a tr ix t ra v e l d ist a n ce C o n tr a ct o r a ssu m p ti o n s M o d e l p a ra m e te rs S u p p ly a n d d e m a n d Create CSV file Operational parameters Input

Driving time empty Driving time loaded

Contractor assumptions Contractor availability Mathematical parameters

Payload

Mill demand

Loader schedule

Supply sector Inventory

Dashboard

Truck Planning

Demand Plan

Import results

Inventory Plan Loader Plan (Mill)

Period KPIs Shifts Plan Shipment Plan Supply Loaders Transportation Plan Trucks KPIs Trucks Plan Optimize Mill Planning Site Planning Period : January

KPIs Dem. Satisf.

Fleet Utilization (Detailed)

Inventory

▲1 2 3 4 5 ▲1 2 3 4 5

0 Re07095 14190 21285 28280 0 Elko Saw millWh 1750200921501450 0 0 Wh0 156 503 5091865 0 Radium Saw millWh 2846229426502988 0 1 Re0 0113115622493 0 Radium Saw millRe 12226 12500 11550 11702 0 2 Re05762 11174 16986 22748 0 Canal Flats Saw millRe 11905 15826 11550 11350 0

Fleet Utilization Trend 3 Re0 171 242 413 534 0 Kootenay OperationPu 2850290028001950 0 4 Re0 126 2 128 254 0 Kootenay OperationRe 6261850800 250 0 5 Re0245047007400 10100 0 Elko PulpPu 2600280032501200 0 7 Re0324364869729 12972 0 0 0 0 0 0 0 12 Re0268653728058 10744 0 0 0 0 0 0 0 1030 Re0 187 474 511 748 0 0 0 0 0 0 0 ▼ ▼ 89% Logistics Dashboard Hours / Truck Mill Supply 62 h/Week Av. Trsp Cost 5,75 $/m³ Fleet Utilz. 25% Comments/Notes : 20 25 30 35 1 2 3 4 0 10000 20000 30000 40000 50000 60000 70000

Attained Vol Missed Vol 0 20000 40000 60000 80000 100000 120000

Attained Vol Missed Vol

0 50 100 150 200 K335K249K334K188 K T1 55K153K517 K T580 K1 07A K30 7AK333 K T1 15K439 K51 6AK147K513K504K102 K T1 18 K18 6A K43 3AK501 KT2 4K331 K T131 K1 49AK313K146K242K189K141 K T610K151K332K231 K T577 KT2 3 KT14 2A K43 2AK431 K50 6AKT21 K T130 KT0 2 32,5 40 12,75 12,75 0

DRIVING EMPTY (%) DRIVING LOADED (%) LOADING (%) UNLOADING (%) WAITING (%) 0% 10% 20% 30% 40% 50%

Loaders Utlization Ratio

Dashboard

Dock Scheduling

Truck Scheduling

Determine the

schedule of trucks

over a period of time

(e.g. one week) in

Weyerhaeuser to:



Minimize transportation

cost (loaded and empty

trips)



Minimize the cost

associated with waiting

time of trucks and

loaders at the mill and in

the forest.

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Thank you

Yu (Vivian) Li

Researcher Value Maximization/Decision support

604-222-5629