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Bulletin of the Transilvania University of Braşov
Series II: Forestry • Wood Industry • Agricultural Food Engineering • Vol. 6 (55) No.1 - 2013
IMPROVING THE PRIMARY FOREST
FUEL SUPPLY CHAIN
Peter RAUCH1
Abstract: The paper comprises various topics covering the primary forest
fuel supply chain, provides an overview of actual research and outlines
future research issues. Starting with estimating the potential supply volumes
of primary forest fuel, which proved to be a really crucial task for the whole
supply system, the supply network is then described. Further development of
forest fuel supply chain engineering is shown and proven to be a valuable
measure in improving supply chain performance. The paper concludes with
critical reflections on some shortcomings of developed forest fuel supply
models and ends by illustrating future research options.
Key words: primary forest fuel, bioenergy, transportation, logistics.
1 University of Natural Resources and Life Sciences, Vienna
1. Introduction
The paper comprises various topics
covering the primary forest fuel (PFF)
supply chain, provides an overview of
actual research and outlines future research
issues. Therefore, it does not intend to
present a comprehensive literature review
on each issue, since supply chain research
is a broad field, even if one focuses mainly
on the PFF supply chain.
A supply chain is defined as a system
consisting of material suppliers, production
facilities, distribution services and
customers, who are all linked together via
the downstream feed-forward of materials
(deliveries) and the upstream feedback of
information (orders) [1]. Accordingly, the
wood supply chain spans everything from
the forest to the forest-based industry,
including the bioenergy generation, as well
as the procurement of wood products for
further processing steps, e.g., deals for
solid structure timber production.
Measures for improving the supply chain
differ in terms of their time horizon and
aggregation of information and processes.
Strategic supply chain decisions have a
planning horizon of several years and are
thus long-term decisions, such as supply
chain design, which includes decisions on
transportation modes or facility location
decisions (e.g., power plant location or
terminal location). Additionally, wood
procurement planning decisions are often
interconnected, e.g. a decision for a
specific plant location can restrict
transportation modes, which can
furthermore restrict potential suppliers or
supply regions. Tactical supply chain
decisions take into consideration a
medium-term planning horizon of up to
several months. Typical tactical planning
tasks are transportation planning, including
harvest area and plant allocation or
capacity planning, production planning and
materials requirement planning.
Operational supply chain decisions are
Bulletin of the Transilvania University of Braşov • Series II • Vol. 6 (55) No. 1 - 2013
2
short-term decisions made from day to day
or a planning horizon of a few weeks.
Detailed schedules for machines and
harvest sites, or transportation decisions,
such as vehicle routing for forest fuel
transport, are typical operational tasks [2].
The level of planning detail increases from
the strategic to the operational level.
Contrary, research dealing with strategic
and tactical supply chain decisions
strongly relies on input data gathered in
operational studies (e.g., including
chipping operations in a model depends on
chipping costs for different chipping
devices obtained in field trails).
2. Estimating Potential Supply Volumes
In Europe, recent regulations have
stimulated sustainable and CO2-neutral
energy sources, since fossil fuels have been
recognized as an uncertain and climate-
threatening energy source. Biomass presents
enormous opportunities for global energy
production in the coming decades [3], and
various studies indicate that forests can
become a major source of bioenergy, even
without negative side effects, such as further
deforestation [4]. Accordingly, wood fueli is
seen as one of the most promising options
for the future among the other renewable
energy sources [5]. Therefore, the
ambitious national and EU bioenergy
targets (e.g., 20 20 20 by 2020 target)
i Woodfuels (or wood fuel): “All types of biofuel
originating directly or indirectly from woody
biomass.” [6]: p.42.
ii Primary forest fuel or forest fuels: “Wood fuel
produced where the raw material has not previously
had another use. Forest fuel is produced directly
from forest wood by a mechanical process.” [6]:
p.35. It comprises traditional fuel wood, sub-
standard industrial roundwood, and logging residues,
and is supplied either directly from the forest to the
energy plant or via terminals. Sometimes it is also
called primary forest fuel in order to separate it from
other wood fuels, such as the industrial by-products
saw chips or black liquor.
demand further increasing the proportion
of wood-based bioenergy systems.
Therefore, the demand for wood fuel and
particularly for PFFii, has skyrocketed [7].
Fuel supply planning has been based on
studies that evaluated the potential supply
volume (e.g. [8], [9], [10]) based on the
yearly increment and wood reserves
accumulated as a result of under-utilization
in the past and took technical and
economic limitations into consideration.
However, even though it was not explicitly
declared, the authors assumed that every
forest owner would be utilizing timber
within a couple of years, if it could be done
in a profitable way. In contrast, most of the
calculated potential comes from small-
scale forests, where an increasing number
of owners value their forests as a place to
spend their leisure time and, in fact, they
do not want to harvest timber at all
[11],[12]. Furthermore, small-scale forest
owners tend to set the harvest time
according to their own investment needs.
Ignoring these restrictions resulted in
excessively high supply potentials for
wood fuel [13]. Therefore, as a robust
basis for the design of a regional supply
chain, a stepwise heuristic approach was
introduced that integrates seasonality of
supply and demand based on calculation of
the available market potential [14]. In
subsequent applied projects for the
bioenergy industry, it could be proven that
the available forest fuel potential is a good
indicator for estimating whether planned
plants can be supplied with feedstock, as
well as making a first estimation of
expected average transport distance and
related transportation cost.
3. The Wood Supply Network
Terminals balance the seasonal
fluctuation of the plant's demand and the
respective variability of supply from the
forests [15] and serve as transshipment
Rauch, P.: Improving the Primary Forest Supply Chain 3
points, where chipping is carried out.
Therefore, terminals are used to ensure a
reliable supply, even under extraordinary
conditions (e.g., when wood fuel piles in
the forest cannot be accessed after a period
of rain or heavy snowfall; [16]).
Furthermore, terminals are sometimes
needed to store energy wood and chips
because of low storage capabilities at the
plant location. Allocating a terminal with
chipping operations needs to take vicinity
to settlements into account because of
noise and dust produced during chipping.
Setting up a terminal results in a tradeoff
between additional costs (e.g., investment
and material handling) and decreasing
chipping and transportation costs due to
scale effects [17]. Therefore, the cost-
cutting potential of a terminal depends on
the entire PFF supply chain [18].
Seasonality of both the fuel supply from
the forest and the fuel demand, leading to a
maximum volume of forest fuels stored at
a given time of the year, should determine
the storage capacity of the regional
terminal [14].
Terminals as large buffer storage areas
are also prerequisites for ship and rail
transport, because high volumes have to be
unloaded and stored within a short time
period [16]. Usually, a stationary chipper
at a plant operates more cost effectively
(economy of scale) than chipping at
roadside landings, for example [19].
Terminals may differ in terms of location,
storage capacity and chipping technology.
Industrial terminals are located at a
forest-based industrial plant, where a
stationary chipper is mainly used for
chipping wood for pulp or panel
production, but its capacity also allows
handling forest fuels [16]. Furthermore, an
industrial terminal using a stationary
chipper can be located directly at an
energy conversion plant. According to
forest fuel supply chain cost analyses,
terminals at energy conversion plants
required a large storage area, a high annual
processing volume and a stationary chipper
to be competitive [17]. Industrial terminals
mainly use existing infrastructures and
profit from scale effects in acceptance of
wood or chipping and thus provide low
costs [19]. Accordingly, for a national PFF
supply chain it was proved that industrial
terminals offer considerable saving
potentials [18]. Consequently, a forest-
based industrial partner as terminal
provider can offer important cost cuttings.
Simple terminals in or near the forest
only provide storage areas for several
thousand cubic meters of wood fuel, as
well as year-round access for trucks and
mobile chippers. Often entrepreneurs with
mobile chippers are engaged, since
chipped volumes are low. Compared with
the annual demand of a CHP, the storage
capacity of a regional terminal is relatively
low, and the same applies to scale effects
on chipping and transportation [18].
Agricultural infrastructures providing a
calibrated weighbridge and asphalted
storage surface, such as terminals built for
processing sugar beets, are also used as
forest fuels terminals [16]. The actual
implemented forest fuel supply chains in
Central Europe rely on the transportation
modes, such as truck, rail and inland
waterways, with the truck as the most
commonly used mode (Figure 1).
In supply chains, shortages are usually
buffered by means of stored material,
leading to so-called hidden inventory costs
due to material deterioration. Contrarily,
storing woody biomass properly for
several months increases the net calorific
value due to drying, however
biodegradation leads to dry matter losses.
Indeed, a higher net calorific value of
fuel reduces both the quantity of ashes
produced and the ash disposal costs [20].
Bulletin of the Transilvania University of Braşov • Series II • Vol. 6 (55) No. 1 - 2013
4
Fig.1. PFF supply network for Austrian energy conversion plants (CHP: combined
heating plant; HP: heating plant)
4. Forest fuel supply chain engineering
Innovation potential on an operational
level is nowadays small compared with
that on a tactical or strategic level.
Furthermore, with the expeditiously
growing forest fuel demand, the strategic
problem of how to design a cost-efficient
distribution network has evolved. Studies
addressing tactical or strategic decisions in
the forest fuel supply network focus on
terminal location, transportation mode, or
supply and demand allocation. The task is
to design a forest fuel supply network
where the procurement areas, different
terminal types and plants are all connected
in a cost effective manner via various
kinds of fuel supply chains.
A forest fuel supply network with several
supply regions, one central terminal as a
processing site, and a single energy plant
was described and solved for a multi-period
horizon with Linear Programming, by
which it was shown that the transportation
costs constituted the most essential part of
the total forest fuel supply cost [21]. A
geographic information system (GIS)-based
model was developed for estimating the
total purchase and transportation costs for
supplying woody fuel from the forest
directly to coal-fired power plants. The
results stressed the importance of a plant-
based approach for assessing both biomass
resources and procurement costs in order to
determine the profitability of co-firing
woody fuels [22].
A recently developed model combines
the GIS-based fuel potential and cost
estimates with a Linear Programming
model to allocate forest fuels from
regeneration cuttings to CHPs, but no
terminals are considered in the potential
supply chains [23]. A Mixed Integer
Linear Programming model supported
supply chain planning for heating plants
firing both forest and sawmill residues.
Decisions to be taken included the kind of
fuels (e.g., forest residues, sawmill
byproducts and decay-damaged wood),
harvest area and sawmills to be contracted,
Rauch, P.: Improving the Primary Forest Supply Chain 5
as well as transportation modes [15]. A
heuristic solution was developed in order
to more quickly solve the problem with a
planning horizon of one year, considering
monthly periods. At a regional level, a
Linear Programming Model located and
sized CHPs by considering the fuel harvest
and transportation costs, as well as
regulatory and social restrictions [24]. An
evaluation method of a forest fuels supply
network design that comprised inventory
management policies to buffer seasonal
fluctuations in fuel demand and supply
shows that the supply chain outperforming
all regional terminals located within a
radius of 100 km was using a central,
forest industry-based terminal [14]. In
addition, a more recently developed
operational forest fuel logistics model
includes daily variations in moisture
content of delivered woodchips, as well as
weather conditions that slow down the
logging operations [25].
The robustness of the forest fuel supply
network design was tested by means of
changes in the transportation cost and
domestic forest timber utilization rate. It
was possible to demonstrate that industrial
terminals offer considerable saving
potentials. Therefore, the cooperation of
CHP operators with a forest-based
industrial partner as a terminal provider is
one of main management implications of
the study results [18].
The concept of using scenario analyses
in order to test the sensitivity of a forest
fuel supply model was further
implemented for evaluating the impacts of
rising energy costs on procurement
sources, transport mix and procurement
costs on a national scale (Austria).
Furthermore, the influence of truck route
optimization on procurement costs and
modal split was evaluated. [16].
In conclusion, it can be said that various
optimization models have been developed
for a number of forest fuel supply
decisions. In addition, models became
more and more detailed and spatially
explicit, but examples for the estimation of
the surplus of optimized supply networks
compared to concrete actual supply
situation are still rare. An example for
cooperative wood procurement by two
Swedish pulp producers, who optimize the
allocation of sawmill chips to pulpmills in
order to minimize transportation cost is
provided by [26]. They state that this
cooperation reduces transportation cost,
but give no exact figures on the saving
potential.
One attempt to close aforementioned gap
has be made by [27], who simulated actual
forest fuel procurement costs for Austria
with heuristics and found that they are at
least 20% higher than procurement costs
based on a MILP model. Cooperation
between all Austrian CHP plants lowers
forest fuel transportation costs by 23% on
average and reduces average transportation
distances by 26%. This corresponds with
the results of [28], who noted a 20%
reduction in truck transport costs by inter-
enterprise cooperation in the roundwood
procurement of three large timber
industries.
Nevertheless, cooperation amongst all 91
CHPs throughout Austria would seem to
be rather unrealistic. Therefore the next
logical research step was to explore the
effects of concrete cooperation and
possible cost cutting. Accordingly, the
above-described methodology was adapted
to calculate the economic benefits of
cooperative fuel procurement as a result of
the fictional cooperation of seven of the
largest Austrian CHPs [29]. Savings
through cooperation were calculated as the
difference between the sum of total
transportation costs of all partners with or
without cooperation. Average savings span
from 14% to 24% of the transportation
costs, but differ amongst the cooperating
partners.
Bulletin of the Transilvania University of Braşov • Series II • Vol. 6 (55) No. 1 - 2013
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Establishing partnerships and working
alliances for forest fuel procurement thus
has important management implications
for achieving efficiency in forest fuel
supplies and strengthening the
competitiveness of wood fuel-based energy
production. Despite the benefits of
cooperation, several critical issues still
exist. One important issue is that
cooperation benefits may not be distributed
equally between cooperating partners.
Such is the case, if one partner receives a
larger share of cost-cutting effects than the
other(s). Accordingly, recent developments
consider cost-saving sharing as a key issue
of inter-enterprise cooperation in
transportation and are discussing new cost
allocation methods according to the
example of a forest-based industry [30].
5. Shortcomings of Developed Forest
Fuel Supply Models
Many of the developed optimization
models (which are mainly MILP models)
minimize specific costs under the implicit
assumption of perfect cooperation and
coordination among all involved business
entities. Due to competition, on the
contrary, calculated costs are certainly
lower than in reality, as was proven by [27],
who found that real costs were at least 20%
higher. To simulate a competitive situation,
they applied three different models to figure
out the practical behavior of managers
supplying a single CHP.
Further frequent shortcomings of many
of the presented network models are the
exclusion of the long-distance
transportation modes of rail and ship, the
assumption of too small procurement areas
disregarding the supply and demand of
adjacent regions, or competing material
uses (e.g., panel production), and
disregarding import options.
Furthermore, even though several
models support strategic decisions with a
long-term planning horizon, basic
economic assumptions are market stability,
in terms of supply and demand volumes,
prices or supply costs. Accordingly, like
most forest planning models, many forest
fuel supply models are also based on the
assumption that all information is
deterministic [31].
Additionally, most presented models are
not sensitive to stochastic supply delays
caused by natural hazards or technical
breakdowns. However, the resulting delays
of terminals or direct supplies have a
considerable impact on economic
performance of the supply chain and
should be considered in the supply network
design (e.g., whether additional terminals
are needed for fuel buffer stocks; [18],
[20]).
Similar to other supply decision-making
models, many of the presented approaches
focus on a single parameter and are
exposed to produce suboptimal solutions to
the sourcing problem [32], because
multiple criteria (e.g., supply security,
product quality, risk splitting) are usually
important in sourcing decisions.
6. Future Research Options
Optimization of supply chains, as well as
operational studies on new logging and
wood transportation techniques and
machines, will still offer a vast research
field and contribute to the further
development of wood supply chains.
Innovative technologies (e.g., torrifaction
and pelletization of wood chips) will
expand the scope of usable raw materials
from agricultural, forestry and industrial
residues, and provide new opportunities.
Furthermore, in addition to economic
sustainability, environmental, social and
cultural dimensions of sustainability of
wood procurement also have to been taken
into consideration and integrated in an
adaptive collaborative management [33].
Rauch, P.: Improving the Primary Forest Supply Chain 7
Including sustainability issues will further
enrich the complexity of wood supply
chain research, and it represents an
ongoing daunting challenge for innovative
scientists working in this field.
Acknowledgements
The author would like to thank the “South
East Europe Transnational Cooperation
Programme” an EU program for financially
supporting this research within the project
“FOROPA - Sustainable Networks for the
Energetic Use of Lignocellulosic Biomass in
South East Europe”.
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