Container supply chain for forest biomass

2. Container supply chain for forest biomass
Kalle Karttunen, Project Manager M.Sc (Agr. & For.)
LUT Savo Sustainable Technologies
FORMEC 2013 Techniques for sustainable management
46th International Symposium on Forestry Mechanisation, 30 Sept - 2 Oct 2013, Stralsund Germany

3. Content
› Introduction
› Intermodal composite container
› Study scenarios
› Material and methods
› Containers
› Simulation
› Availability analysis
› Results
› Unit cost
› Time usage
› Total cost saving potential
› Conclusion
› Container or not?
› Future research

4. Introduction
- Intermodal composite container
Aim of the study was to determine the profitability of an innovative
intermodal composite container solution compared to traditional supply
chains of forest chips from long-distances
“Composite Container Logistics 2011 – 2013” and
“Container Logistical Innovations, 2013 – 2014”
Karttunen, K., Lättilä, L., Korpinen, O-J. and Ranta, T. Cost-efficiency of intermodal
container supply chain for forest chips. Silva Fennica (manuscript).
The main idea of composite container was to maximize road transport
dimensions and minimize weight of container for intermodal transportation
Container is made of plastic channel composite1 material
Container is called Supercont® and it is produced by a Finnish company,
Fibrocom
6058 mm
2550 mm
3050 mm
(+ 200 mm
current
dimension)
1 pat pend

5. 1. Structural benefits:
Light weight of container (1500 kg) -> More payload
Temperature isolated -> Non-freezing
Composite material -> RFID-free
Channel structure, “one-shot”-moulding -> Durable
2. Supply chain benefits:
Suitable for standard equipments -> Flexibility
Suitable for truck-train/vessel-truck -> Intermodality
Flexibility in roadside chippings -> Easy handling
Productivity of unloading -> Fast handling
1 pat pend
Introduction
- Intermodal composite container

6. Introduction
- Study scenarios
Sub-scenarios
Traditional
Past dimensions 1.1.1 2.1.1 3.1.1
Current dimensions 1.1.2 2.1.2 3.1.2
a.Sensitivity analyses 1.1.3 2.1.3 3.1.3
b.Sensitivity analyses 3.1.4
Container
Past dimensions 1.2.1 2.2.1 3.2.1
Current dimensions 1.2.2 2.2.2 3.2.2
a.Sensitivity analyses 1.2.3 2.2.3 3.2.3
b.Sensitivity analyses 3.2.4
Main scenario
Sce. 1 Sce. 2 Sce. 3
Baseline (Sce 1): truck transportation for forest chips
(logging residues and small-diameter trees) around the
user site for current target demand (540 GWh)
• the case power plant at central Finland, city of
Jyväskylä
Comparison (Sce 2 and 3): additional target demand of
the case power plant (+200 GWh) from long-distances
by trucks (Sce 2) and railway (Sce 3).
• Sce 3: the case satellite railway terminal at
Kontiomäki
Sub-scenarios:
• Traditional vs. container supply chains
• Past dimensions (60 t) vs. current dimensions (64 t)
• Extra scenarios as sensitivity analyses:
Several number of trucks and wagons

7. Introduction
- Study scenarios
Main differences between
container and traditional supply
chain:
Trucks
Container vs. Solid-frame
Unloading: Stationary vs.
Back dumping
Satellite terminal loading
Containers (forklift loader)
vs. Loose chips (front
loader)
Railway transportation
Metal containers vs.
Composite containers
7

8. Traditional = Solid-frame-truckNew innovation = Container truck
- Full-trailer solid frame trucks (usage in Finland
89%)
-Unloading: Back dumping with a carried chain
(usage in Finland 65%)
- Metal container trucks (usage in Finland 8%)
- Normally unloading method is back dumping,
through open doors.
-Unloading: Stationary machine in this study
- On average 25 t tare weight of truck and
trailer (7 axle truck -> 64 t) max. 39 t
payload
- 127 m3 (137 m3 current increase) frame
volume
- (8 axle truck -> 68 t)
- (9 axle truck -> 76 t)
- 20-24 t tare weight of truck, trailer and three
containers (7 axle truck -> 64 t) max. 44 t
payload
-124 m3 (133 m3 current increase) frame volume
(three containers)
Past: Total weight limit in Finland, 60 t
Current (1.10.2013->): 64 – 76 t & 20 cm height more
Material and methods
- Containers
Payload is dependent not only on the truck weight and dimensions and moisture
content of biomass but also road weight limit legislation!

9. Material and methods
- Containers (railway)
Intermodal Container Other options = Interchangeable Containers
-Same composite containers for truck
and train (Fibrocom, Supercont)
Fig. VR Transpoint
•Container wagons (Sg-t)
•Maximum payload 61 t for wagon
•Weight limit is not a problem in railway
transportation of wood chips. Container frame-
volume is a restrictive factor!
- Interchangeable concepts, but only for railway
-Metal container (Innofreight) in this study

10. Material and methods
- Containers (unloading)
-If containers have no doors, a special
unloading system should be used.
-Containers can also be unloaded directly
from trucks to the stationary system
-Heavy forklift or wheel loader is anyway
needed in terminal actions (maximum
weight capacity for composite container 20 t)
-Weighting, moisture sampling and RFID
(Radio Frequency Identification) could be
included into the operations
Stationary unloading system
(used in this study):

11. 11
Material and methods
- Containers (terminal operations)
Front wheeled loader or heavy material handling machines for
bulky material, forklift loader for containers
In Sweden are used Austrian interchangeable container
solution (Innofreight), where heavy forklift truck are used
for unloading using rotating devise, also tests in Finland
Intermodal transportation option with containers could allow
combination of truck and railway logistics either on the
upstream or downstream part of supply chain
Innofreight containers are too wide for Finnish roads (2.9 m) and
metal containers are not suitable in winter time (freezing problem)

12. Material and methods
-Simulation (background)
The simulation was conducted with AnyLogic 6 software,
which is suitable for discrete-event and process-centric
modelling
The trucks “agents” have five distinct states: out of
service, waiting, moving, being loaded, and unloaded
The aim of the study method:
Combine simulation method with forest biomass site-
dependent availability analysis
1. Simulation web page to analyse alternative options (older
version with past road dimensions):
http://personal.lut.fi/users/lauri.lattila/MikkeliUpdated/MikkeliNe
tti.html
2. The model runs in the virtual reality for one year and
calculates the total costs supply chain for forest chips
yearly fixed costs
variable costs
the production amount of forest chips -> Unit cost
(€/MWh)
3. Statistics sheet: Time usage of trucks and driving distances
etc.
12
Simulation expertise: Lättilä 2012, LUT
1.
2.
3.

13. Material and methods
-Simulation (input)
13
Productivity of all operations from roadside to powerplant were taken into account (follow-up
studies, pre tests, early studies, estimates)
Cost structures of all vehicles and machines from roadside to powerplant were analysed with fixed
and variable costs
Costs of forest operations (logging residues and small-diameter energy wood) were included in
supply chain costs (9.3 – 9.8 €/MWh)
Several number of trucks (6 – 18) and wagons (15 or 20) were used in simulation scenarios
Parameter Values (“red color” in this study)
Amount of trucks 0…N (6 – 18)
Type of trucks Container or traditional
Type of rotator Mobile or fixed
Compression used Yes or no
Satellite terminal Yes or no
Amount of wagons 15 or 20
Type of railway containers Composite (41 – 54 m3) or metal (46-52 m3)
Target demand of plant 540 or 740 GWh

14. Material and methods
-Availability analysis
14
Site-dependent forest biomass resource
data was included in the simulation model
(additional excel)
The source data consisted of municipal
estimates of forest fuel availability and land-use
data (Korpinen et al. 2012)
The datasets were imported to a geographical
information system (GIS) environment that was
processed by ArcGIS software
The points of origin for forest-fuel supply were
generated via a 4 × 4 km grid
The competitive demand for forest fuels was
taken into account as market share analyses

15. Result
-Unit cost
15
Past dimension (60 t)
Baseline
Sce. 1 Sce. 2 Sce. 3
Current dimension (64 t)
Baseline
Sce. 1 Sce. 2 Sce. 3
First: Traditional supply chain
Second: Container supply chain
Container supply chains were the most cost-efficient alternatives
for both past and current maximum truck dimensions in all
scenarios!
Traditional supply chains were 7-19 % (past) or 3-11 %
(current) more expansive than container supply chains
The most cost-efficient way
to increase procurement of forest
chips was the container truck
transportation!
Railway transportation was
cost-competitive (17.6€/MWh) especially
for traditional options compared to
truck transportation!
But the whole costs of intermodal
supply chain was still cheaper (17.1€/MWh)!

16. Results
-Unit cost
The fixed and variable costs from roadside to powerplant:
The biggest costs of the transportation chain were the fixed costs of the
trucks, which varied between 2.1 and 4.7 €/MWh depending on the scenario
The second biggest part was the fixed costs of chipping, which varied between
1.8 and 3.5 €/MWh
16

17. Result
-Time usage
Simulated time usage of the truck logistics showed that the trucks stayed
unused (“Trucks at base”) most (62 – 66 %) of their annual time
It is notable that the traditional trucks spend 14.8 % of their time waiting to
be emptied
Large number of trucks are in unloading station of power plant at the same
time, which is clearly a bottleneck in traditional operations.
17

18. Result
- Total cost
Target demand (Sce. 1: 540 GWh. Sce 2 and 3: 740 GWh): ”Truck driving
kilometres can be decreased with satellite terminal and railway supply chain”
Simulated supply deliveries (482-857 GWh): ”The total costs can be reduced with
intermodal container supply chain”
18
Kilometre distance, km Sce. 1 Sce. 2 Sce. 3
Logging residues 61 (92) 69 (103) 59 (88)
Small-diameter energy wood 81 (121) 96 (144) 71 (106)
Average 71 (107) 83 (124) 65 (98)

19. Result
- Total cost saving potential
As an example, if deliveries of forest chips is doubled from 500 GWh to 1000 GWh:
Traditional supply chain: 15.9 €/MWh -> 20.5 €/MWh (increase: 4.6 €/MWh, 29%)
Container supply chain: 15.6 €/MWh -> 18.1 €/MWh (increase: 2.5 €/MWh, 16%)
Container cost saving potential: 0.4 €/MWh to 2.4 €/MWh ->
annual cost saving potential from 0.4 to 3.1 million euros!
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20. Conclusion
- Container or not?
Intermodal composite container supply chains were lower costs than traditional
options in all scenarios
Traditional systems were 7 – 19 % more expensive than the intermodal container
scenarios for past maximum road vehicle dimensions
Current dimension regulations decrease the total costs of forest chips in 0.4 – 1.9
€/MWh (on average 6 %)
Traditional options were still 3 – 11 % more expensive for current road vehicle
dimensions than container supply chain
How to expand the procurement area for forest chips?
Start using intermodal container trucks
Start using satellite terminals and train transportation with interchangeable or
intermodal containers instead of truck logistics from long-distances
Intermodal composite container logistics and railway transportation could be
developed as an attractive option for a large-scale supply chain for forest chips
20

21. Conclusion
- Future research
Study method:
Simulation study combined with geographical site-dependent information will lead to
results of greater relevance to practical decision making when considering the use of
innovations
The study method leads to cost evaluations very close to the actual prices of forest
chips (average price for forest chips 2008-2011: 17.4 €/MWh)
The simulation model can be used elsewhere if site-dependent availability studies
can be included
Supply chain:
Intermodal containers for biomass transportation and terminal operations
Usability of heavy volume traditional trucks with more axles and more frame-volume
Composite material can be used for the wall of traditional trucks
Usability of intermodal and removable containers for forest roads
This study presented the costs of traditional or container supply chain but combined
methods might achieve optimal solutions for the large-scale supply chain of forest
biomass in practice
21

22. Thank you for your attention !
Further information:
kalle.karttunen@lut.fi (project manager) or tapio.ranta@lut.fi (prof.)
http://www.lut.fi/lut-savo-sustainable-technologies
http://www.fibrocom.com/