Optimized Delivery and Logistics Planning in Forestry What's Possible?
Optimized Delivery and Logistics Planning in Forestry What’s Possible? Remsoft & Geocom
Doug Jones, VP Forestry May 2013
Introduction • • • • • • • •
Delivered wood cost is significant Approximately 40% to 60% of final product cost Transportation cost approx. 30% Tends to be most variable cost item Fuel costs are rising Environmental concerns – GHG emissions Too many empty miles Complex supply chains
Agenda • Introduction • Background – Geocom and Remsoft
• • • •
Problem definition Solution concept Benefits Questions
Company backgrounds Geocom • • • • • •
Founded in 1995 Headquartered in Munich / Bern Customers in 24 countries Focus on OR and infrastructure management Domain expertise: logistics, utility networks, industrial plants Esri Platinum Partner
Remsoft • • • • •
Founded in 1992 Headquartered in Fredericton, Canada Customers in 20 countries Focus on OR & forestry planning Domain expertise: optimization solutions for hierarchical forest planning
Business Use
Hierarchical Planning
Strategic
Tactical
Operational
Portfolio, Estate, Property
Portfolio, Estate, Property
Estate, Property
Wood Supply Analysis Financial Analysis Buy and Sell Policy Evaluation Risk Analysis Land Management Valuation Integrated Nursery Planning Capital Planning Biomass Certification Harvest Scheduling Hydrology Environmental Impacts Habitat Analysis Facility Location Woodbasket Analysis Multi-use Planning Carbon Silviculture Strategies Portfolio Analysis Investment Planning
Wood Supply Analysis Financial Analysis Establishment planning Road planning Integrated Nursery Planning Capital Planning Biomass Production Scheduling Capacity Planning Woodflow Planning Budget Planning Crew Planning Delivery Planning Sales Planning
Financial Analysis Production Scheduling Capacity Planning Woodflow Planning Budget Planning Crew Planning Delivery Planning Sales Planning Activity Sequencing
Delivery & Logistics Property
Delivery Scheduling Resource Allocation Route Planning Automatic Vehicle Location Delivery Tracking
Delivery Planning Production
Full-tree Crews
Delivery
Sales / Demand
Rail Sawmills
Cut-to-length Crews Trucking Fleet
Sorting yards
Biomass Plants
Cable Crews
Pulp & Paper mill
Barge Chipping Crews
Fixed Prodn
28 day schedule
Purchase Wood
GEONIS Street Network Manager Integrating available street data and forest roads
1: two data sets
2: matched and reconciled base data set
3: unmatched data set elements integrated 4: integrated conflated and reconciled data set 7
Logistics Scheduling: GIS-based optimization
OR and GIS combined Step 1: Allocation and Sequencing Optimization Step 2 Routing and Telematics Dynamic, real-time scheduling
8
Problem definition: Delivery planning
$25/m 3 $30/m 3 $35/m 3 $40/m 3 $45/m 3
Unit 001
Problem definition: Delivery planning Daily Delivered Volume 800 600
Pellet #1
400
SM #3
200 $25/m3
SM #2
0
SM #1
$30/m 3
$35/m 3 $40/m 3 $45/ m3
28 days x 40Unit units x 15 products x 2 modes x 5 purchase x 7 destinations = 001 # of Trucks 15 10 5 0
Pellet #1 SM #3 SM #2 SM #1
Complexity
Problem Definition: Truck routing & sequencing • Identifying the optimal routes – Between all units and destinations
• • • • • •
Regulation compliance - weight restrictions; time of day Terrain constraints Fleet capacity constraints Truck configuration and product match Shift limits Loading and unloading bottlenecks
Solution Concept 1. Network Data Prep
• SNM
2. Delivery Planning
3. Truck Sequencing
• Optimized delivery • Schedule…what, where, when • Frequency?
• Optimized truck routing and sequencing • Frequency?
Process
Benefits • • • • • • • •
Maximizing supply chain value Transportation capacity management Reduction in fuel costs and transportation costs Reduction in GHG emissions Increased payload Reduction in wait times Planning agility Increased plan transparency
www.remsoft.com
Doug Jones, VP Forestry May 2013
Introduction • • • • • • • •
Delivered wood cost is significant Approximately 40% to 60% of final product cost Transportation cost approx. 30% Tends to be most variable cost item Fuel costs are rising Environmental concerns – GHG emissions Too many empty miles Complex supply chains
Agenda • Introduction • Background – Geocom and Remsoft
• • • •
Problem definition Solution concept Benefits Questions
Company backgrounds Geocom • • • • • •
Founded in 1995 Headquartered in Munich / Bern Customers in 24 countries Focus on OR and infrastructure management Domain expertise: logistics, utility networks, industrial plants Esri Platinum Partner
Remsoft • • • • •
Founded in 1992 Headquartered in Fredericton, Canada Customers in 20 countries Focus on OR & forestry planning Domain expertise: optimization solutions for hierarchical forest planning
Business Use
Hierarchical Planning
Strategic
Tactical
Operational
Portfolio, Estate, Property
Portfolio, Estate, Property
Estate, Property
Wood Supply Analysis Financial Analysis Buy and Sell Policy Evaluation Risk Analysis Land Management Valuation Integrated Nursery Planning Capital Planning Biomass Certification Harvest Scheduling Hydrology Environmental Impacts Habitat Analysis Facility Location Woodbasket Analysis Multi-use Planning Carbon Silviculture Strategies Portfolio Analysis Investment Planning
Wood Supply Analysis Financial Analysis Establishment planning Road planning Integrated Nursery Planning Capital Planning Biomass Production Scheduling Capacity Planning Woodflow Planning Budget Planning Crew Planning Delivery Planning Sales Planning
Financial Analysis Production Scheduling Capacity Planning Woodflow Planning Budget Planning Crew Planning Delivery Planning Sales Planning Activity Sequencing
Delivery & Logistics Property
Delivery Scheduling Resource Allocation Route Planning Automatic Vehicle Location Delivery Tracking
Delivery Planning Production
Full-tree Crews
Delivery
Sales / Demand
Rail Sawmills
Cut-to-length Crews Trucking Fleet
Sorting yards
Biomass Plants
Cable Crews
Pulp & Paper mill
Barge Chipping Crews
Fixed Prodn
28 day schedule
Purchase Wood
GEONIS Street Network Manager Integrating available street data and forest roads
1: two data sets
2: matched and reconciled base data set
3: unmatched data set elements integrated 4: integrated conflated and reconciled data set 7
Logistics Scheduling: GIS-based optimization
OR and GIS combined Step 1: Allocation and Sequencing Optimization Step 2 Routing and Telematics Dynamic, real-time scheduling
8
Problem definition: Delivery planning
$25/m 3 $30/m 3 $35/m 3 $40/m 3 $45/m 3
Unit 001
Problem definition: Delivery planning Daily Delivered Volume 800 600
Pellet #1
400
SM #3
200 $25/m3
SM #2
0
SM #1
$30/m 3
$35/m 3 $40/m 3 $45/ m3
28 days x 40Unit units x 15 products x 2 modes x 5 purchase x 7 destinations = 001 # of Trucks 15 10 5 0
Pellet #1 SM #3 SM #2 SM #1
Complexity
Problem Definition: Truck routing & sequencing • Identifying the optimal routes – Between all units and destinations
• • • • • •
Regulation compliance - weight restrictions; time of day Terrain constraints Fleet capacity constraints Truck configuration and product match Shift limits Loading and unloading bottlenecks
Solution Concept 1. Network Data Prep
• SNM
2. Delivery Planning
3. Truck Sequencing
• Optimized delivery • Schedule…what, where, when • Frequency?
• Optimized truck routing and sequencing • Frequency?
Process
Benefits • • • • • • • •
Maximizing supply chain value Transportation capacity management Reduction in fuel costs and transportation costs Reduction in GHG emissions Increased payload Reduction in wait times Planning agility Increased plan transparency
www.remsoft.com
