DOI: 10.1002/fuce.201700012
R. Scataglini1, M. Wei1*, A. Mayyas1, S. H. Chan2, T. Lipman3, M. Santarelli4
1
2
3
4
Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Mailstop 90R-2002, Berkeley, CA, 94720, USA
Department of Mechanical Engineering, University of California, Berkeley, Etcheverry Hall, Hearst Ave #6141, Berkeley, CA 94720,
USA
Transportation Sustainability Research Center, University of California, Berkeley, University of California Richmond Field Station 1301 S.
46th Street, Building 190, Richmond, CA, 94804-3580, USA
Department of Energy, Polytechnic University of Turin, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy
Received May 01, 2017; accepted October 23, 2017; published online November 21, 2017
Abstract
This work details efforts to estimate the direct manufacturing
cost of solid oxide fuel cell (SOFC) stack components for combined heat and power applications. The main research goals
are to identify the major contributors to fuel cell stack manufacturing costs, examine the influence of both production
volume and stack size on cost, and compare the results of the
cost trajectories with the U.S. Department of Energy SOFC
stack manufacturing cost target of $238 kWe–1 (in 2015) and
industry reported cost projections and to identify critical
areas for manufacturing research and development. Stack
component direct manufacturing costs are modeled for net
electricity capacity of 1, 10, 50, 100 and 250 kWe across
1 Introduction
Fuel cell systems are an emerging technology for supplying
efficient, clean power for a wide range of settings, including
stationary combined heat and power (CHP) applications, forklifts, emergency backup systems, and automotive and bus/
truck applications. Fuel cells offer a promising role in addressing energy security and carbon emissions, due to their efficient
energy conversion processes and clean emission profiles in
comparison with fossil fuel combustion based-systems [1]. In
particular, CHP fuel cell systems are attractive applications
from both an economic and environment standpoint, due to
their ability to produce both power and useful heat onsite,
thus augmenting any additional heat needed to meet heating
demands [2]. Solid oxide fuel cells (SOFC) are ceramic-based
electrolyte fuel cells which operate between 600–1,000 C. They
are of particular interest in the CHP applications, due to their
point-of-use power generation ability on both small and large
FUEL CELLS 17, 2017, No. 6, 825–842
annual production volumes of 10, 1,000, 10,000 and 50,000
systems per year. Overall stack manufacturing costs range
from $5,387 kWe–1 to a minimum of about $166 kWe–1 for a
250 kWe system at 50,000 systems per year. To meet the manufacturing cost target of $238 kWe–1, a minimum annual production of 100–250 MWe per year would be required. Reduction opportunities for stack cost are expected to be available,
mainly with the adoption of thinner cells and stack components, higher levels of factory automation, and more sensitive
in-line defect diagnostics.
Keywords: Combined Heat and Power, Electrode–electrolyte
Assembly, Interconnects, Sealing, Solid Oxide Fuel Cell System
scale, high fuel-to-power conversion efficiency, and the high
quality waste heat produced [3].
Despite the numerous advantages over conventional and
alternative power generation sources, fuel cells are not yet
manufactured in high volumes. In addition to the absence of a
mature hydrogen supply infrastructure (but note that SOFC
operates directly with other types of fuels, such as natural gas
and bio/syn-gas), one main adoption barrier is the high capital costs of fuel cells [4]. Numerous studies and cost projections have been done for automotive fuel cells systems [5], but
fewer studies have been done for CHP applications. Additionally, current literature addressing fuel cells stack manufacturing costs are: (i) either too narrow in scope in terms of fuel cell
components, featuring only fuel cell stack parts but not bal-
–
[*] Corresponding author, mwei@lbl.gov
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A Direct Manufacturing Cost Model for
Solid-Oxide Fuel Cell Stacks
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Scataglini et al.: A Direct Manufacturing Cost Model for Solid-Oxide Fuel Cell Stacks
ance of plant components or vice versa [6, 7]; (ii) not detailed
enough and omitting detailed system characterization [8]; (iii)
lacking assessment or modeling of costs [9]; or 4) a combination of the above. This can result in an analysis with limited
applicability outside the fixed system requirements.
This work addresses these gaps by extending our analysis
to provide a fuller treatment to the design and manufacturing
of a solid oxide fuel cell stack. The overarching approach is to
utilize ‘‘Design for Manufacturing and Assembly’’ (DFMA)
techniques to optimize system design, materials and manufacturing flow for lowest manufacturing costs (reference: DFMA).
The model considers fuel cell systems ranging from 1–250 kWe
of net electrical power across various annual production rates
to estimate the direct manufacturing costs for key fuel cell
stack components. Sensitivity analysis is then performed to
gain insight into the effects of manufacturing operation
parameters on stack costs. This work will help identify dominant cost drivers in a fuel cell stack, determine cost effective
fuel cell components manufacturing options, and identify
cost-reduction opportunities to accelerate adoption of fuel cellbased systems.
2 Manufacturing Cost Modeling
2.1 Cost Analysis Methodology
The starting point of the cost analysis methodology is the
definition of the system boundaries and identification of stack
components. Based upon a search of relevant fuel cell literature and patents, industry system specifications sheets as well
as industry and academic advisor inputs, operational and performance requirements are identified and system design and
the functional specifications of the fuel cell were determined.
Process modeling or optimization of the stack design from a
detailed thermodynamic and thermo-chemical point of view is
not described in this paper. However, a ‘‘medium fidelity’’
design, based on feedback from industry advisors, is used to
be representative of actual fuel cell systems.
The second step is to determine which components are
expected to be purchased and which are manufactured inhouse. This model assumes a business scenario of vertical integration where the fuel cell manufacturer is presumed to manufacture all stack components. This assumption is geared
towards the case of higher volume production, since at lower
production volume it may be more cost-effective to purchase
finished or partially finished stack components. This is
because at very low volumes the investment costs for vertical
integration are high and equipment utilization is low for some
elements of the manufacturing chain.
The third step is to design a base manufacturing process
flow for each stack component by combining a literature
search with industry and vendor inputs. The outputs of the
cost model are the direct manufacturing costs. These include
capital costs, operation and management costs (O&M), labor
costs, materials costs, scrap costs and factory building costs,
subjected to global assumptions such as discount rate, infla-
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tion rate and tool lifetimes. This methodology follows that of
other similar cost studies [10].
The annualized manufacturing cost of each component is
quoted as the sum of all these direct manufacturing costs normalized to the annual equivalent production volume in kWe,
units or meter squared of cell surface area per year. A detailed
bottom up costing is done for all major stack components
(e.g., electrode-electrolyte assembly functional cell, frame, cellto-frame seals, interconnect and nickel mesh) and for the final
stack assembly and conditioning process. The stack manufacturing cost is then the sum of costs of all stack components
analyzed. Sensitivity analysis is performed at the component
level and at stack level in order to identify key cost drivers,
cost reduction opportunities and manufacturing R&D areas.
Stack direct manufacturing costs are mainly modeled for
net electricity capacities of 1 kWe, 10 kWe, 50 kWe, 100 kWe
and 250 kWe across annual production volumes of 100, 1,000,
10,000 and 50,000 units per year. Stack design does not change
with production rate, but material costs, manufacturing processes and equipment size often vary. For some components
(interconnects, frames and cell-to-frame seals), multiple
designs and manufacturing approaches are analyzed.
An annualized cost of tool approach is adopted from
Haberl [11]. The annualized cost equation can be expressed in
constant currency as follows:
Cy ¼ Cc þ Cr þ Coc þ Cp þ Cbr þ Ci þ Cm Cs Cint Cdep
(1)
where Cy is the total annualized cost, Cc is the capital/system
cost (with interest), Cr is the replacements or disposal cost, Coc
is the operating costs (e.g., electricity cost) excluding labor, Cp
is the property tax cost, Cbr is the building or floor space cost,
Ci is the tool insurance cost, Cm is the maintenance cost, Cs is
the end-of-life salvage value, Cint is the deduction from income
tax and Cdep is the deduction due to tool depreciation. The
interest tax deduction is not included in the calculations since
it is assumed no net income for fuel cell manufacturers [1].
Direct material costs are determined from the exact type
and mass of material employed in the component. Material
scrap costs include cost of waste material (e.g. due to cutting
or punching processes) and direct manufacturing cost of
defective parts. Labor costs are estimated based upon the
number of people required to operate each machine. A labor
rate of $30 hour–1 is assumed for all process labor, a daily
working time of 16 h (2 shifts), and 240 operating days per
year. Building costs are amortized with building depreciation
for a building life of 31 years. Building area is quoted as the
sum of each specific process module footprint multiplied by a
2.8 space correction factor [12]. Capital costs for each manufacturing machine are estimated based on quotes from manufacturers. In case the vendor does not provide information about
installation and maintenance costs, it is assumed that cost to
install the equipment is equal to 20% of the machine capital
cost and an annual maintenance factor is equal to 10% of
installed equipment cost. Equipment costs are based on a
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Scataglini et al.: A Direct Manufacturing Cost Model for Solid-Oxide Fuel Cell Stacks
2.2 Stack Design and Functional Specifications
System designs and functional specifications for SOFC
CHP applications were developed across the range of system
power levels mentioned above. The general structure of a
SOFC stack is shown in Figure 1. A typical SOFC stack is
made up of two electrodes (anode and cathode), an electrolyte,
seals, interconnect plates, and a frame. The electrodes and
electrolyte form the electrolyte electrode assembly (EEA) and
is the core component of the fuel cell where the electrochemical reactions take place. An anode supporting layer and cathode supporting layer is often added to the EEA, which are
designed to support the cathode and anode layers as shown in
Figure 2. This work is primarily based on FCE/VersaPower’s
anode-supported cell architecture and reported process steps
and stack materials. In an anode-supported cell, the anode
layer provides the structural support for the electrically-active
components.
Table 1 Manufacturing cost shared parameters.
Parameter
Symbol
Value
Units
Comments
Operating hours
ths
varies
Hours
8 h base shift; (2–3 shifts per day)
Annual operating days
tdy
240
Days
52 wks*5 days/wk – 10 vacation days –10 holidays
Avg. inflation rate
j
0.023
US average for past 10 years [13]
Avg. mortgage rate
jm
0.051
Trading Economics [14]
Discount rate
jd
0.10
Energy inflation rate
je
0.056
US average for last 3 years [13]
Income tax
ii
0
No net income
Property tax
ip
0.01035
US average [15]
Assessed value
iav
0.4
Salvage tax
is
0.5
EOL salvage value
keol
0.02
Tool lifetime
Tt
15
Energy tax credits
ITC
0
Dollars
Energy cost
ce
0.10
$ kWhe–1
Assume 2% of end-of-life value
Years
Typical value in practice
Typical U.S. value
–2
Floor space cost
cfs
1,291
Building depreciation
jbr
0.031
Building recovery
Tbr
31
Years
U.S. Department of Commerce [17]
Hourly labor cost
clabor
30
$ hr–1
Hourly wage per worker
$m
US average for factory [16]
U.S. Department of Commerce [17]
Table 2 General assumptions for scaling manufacturing process from low volume to high volume.
Manufacturing Area
Low Volume Manufacturing
High Volume Manufacturing
Labor and automation of manufacturing processes
Mostly manual work with some automation
High degree of automation with low direct labor
requirements
Quality inspection and defect metrology
Mostly manual inspection
Shift to more automated inspection systems
Materials purchasing
Low volume purchases and few suppliers
High volume of purchases with more suppliers
Throughput
Low throughput and low tool utilization
High throughput with high tool utilization
Process rework and material scrappage
Higher rates of process rework and material
scrappage
Low rates process rework rates and material
scrappage
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15 year lifetime [1]. An electricity rate of $0.10 kWh–1 is
assumed and an electricity cost corresponding to the energy
requirements for each piece of equipment. General manufacturing cost parameters are summarized in Table 1.
General assumptions for scaling manufacturing process
from low volume to high volume are shown in Table 2. At low
volumes, manufacturing processes have a greater degree of
manual labor, e.g., quality inspections and defect metrology
have a high degree of manual intervention. Manufacturing
lines generally have low tool utilization and relatively high
rates of process rework and material scrappage, and supply
chains are not well developed with low-volume of purchases
and few suppliers. At high volume, manufacturing process
flows and quality inspection steps are assumed to be more
automated with higher tool utilization and low rates of process rework and material scrappage. Supply chains are
assumed to be more developed with multiple suppliers.
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Scataglini et al.: A Direct Manufacturing Cost Model for Solid-Oxide Fuel Cell Stacks
Fig. 2 Electrolyte-electrode assembly (EEA) schematic.
Fig. 1 Typical SOFC stack configuration [18].
For an SOFC stack, the electrolyte is typically made up of a
ceramic material, such as yttria-stabilized zirconia (YSZ), due
to its good ionic conductivity and robust mechanical proper-
ties under high-temperature operation. The anode is made up
of a porous cermet material composed of nickel oxide mixed
with YSZ to allow the fuel to be diffused to the reaction sites
close to the electrolyte layer, for the oxygen ions to oxidize the
fuel, and for the delivered electrons to be conducted to the
next cell or to the external load. The anode is formed by mixing NiO and 8YSZ powder in the common volume ratio of
70:30 [19]. The composition and manufacturing process for the
EEA is summarized in Table 3 and an overall process flow diagram in Figure 3.
The interconnections provide both electrical contacts and
gas channels between individual cells. Metallic interconnects
Table 3 EEA composition and manufacturing process.
Component
Materials
Thickness / mm
Process
Anode
Ni/YSZ
700
Tape casting
Anode electrolyte interlayer
50% YSZ
50% NiO
10
Screen printing
Electrolyte
YSZ (Yttria-Stabilized Zirconia)
10
Screen printing
Electrolyte/cathode Interlayer
50% YSZ
50% LSM
10
Screen printing
Cathode
LSM (lanthanum strontium manganite )
50
Screen printing
Fig. 3 Process flow-diagram for EEA.
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Table 4 Functional specifications.
Parameter
10kWe CHP system reformate fuel
50kWe CHP system with reformate fuel
Units
Gross system power
11.0
54.9
kW DC
Net system power
10
50
kW AC
Electrical output
220 V AC
480 V AC
Volts AC or DC
DC/AC inverter efficiency
95
95
%
Operating temperature
700–800
700–800
Temp. C
Waste heat grade
220
220
Temp. C
Fuel utilization % (overall)
N/A
N/A
%
Net electrical efficiency
59
59
% LHV
Thermal efficiency
24
24
% LHV
Total efficiency
84
84
Elect.+thermal / %
Stack power
11.0
54.9
kW
Total plate area
540
540
cm2
Actively catalyzed area
329
329
cm2
Single cell active area
299
299
cm2
Gross cell inactive area
45
45
%
Cell amps
105
105
A
Current density
0.35
0.35
A cm–2
Reference voltage
0.8
0.8
V
Power density
0.28
0.28
W cm–2
Single cell power
84
84
W
Cells per stack
130
130
cells
Stacks per system
1
5
stacks
Parasitic loss
0.5
2.5
kW AC
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tional specifications were developed based on a variety of
industry sources and literature and include calculated parameters for stack and system efficiencies for an ‘‘internally consistent’’ set of reference values. The determination of gross
system power reflects about 10% overall parasitic power at
10 kWe and 50 kWe, including losses through the inverter. DC
to AC inverter efficiency is assumed to be 95% and constant
across the system power ranges. Additional parasitic losses
are from compressors, blowers and other parasitic loads and
are assumed to be direct DC power losses from the fuel cell
stack output power.
The waste heat grade from the coolant system is taken to be
220 C for all system sizes although a range of other temperatures are possible, mostly over the range of 50–70 C. The heat
exchanger configuration can also depend on the demand temperatures for the heating streams, and the exact cooling and
heating loops will be location and system specific. Additional
waste heat streams from the anode and cathode exhaust can
be routed to the fuel processor reactor burner.
At the reference cell voltage of 0.8 V, the net electrical efficiency is 59% (lower heating value, or LHV) for the reformate
systems. These overall electrical efficiency levels are similar to
those reported in literature [10]. The total overall CHP system
efficiency of 84% is viewed as a benchmark value for the case
where a large reservoir of heat demand exists and represents
are preferred for intermediate temperature SOFCs which
usually operate at £800 C and typically have lower manufacturing costs than ceramic-based interconnects. Glass seals
between the EEA and interconnects prevent the mixing of fuel
and oxidant within the stack, leaking of fuel and oxidant from
the stack, and also provide mechanical bonding for the components [20]. Barium-calcium-aluminosilicate (BCAS), an alkaline earth aluminosilicate glass, is most commonly used for
SOFC seals due to its high electrical resistivity, high thermal
expansion, and rapid crystallization kinetics [21] and was
modeled in this study.
The EEA, seals, and interconnects together form the ‘‘stack
repeating unit’’ (SRU) of the cell. These repeating units are
connected together to provide a wide range of power output,
forming a ‘‘stack’’. Finally, a support structure, such as endplates with tie-rods, hold the fuel cell stack together to provide
structural support. In this study, two different stack designs
are considered, a base design with SS441 interconnect and
frame and an alternative design with Crofer 22 APU interconnect and frame. The Crofer interconnect has a thickness of
315 mm and a mass of 123 grams, whereas SS441 Interconnect
has a thickness of 630 mm and a mass of 247 grams [22].
Functional specifications for the 10 kWe and 50 kWe CHP
systems with reformate fuel are shown in Table 4 below and a
system schematic diagram is show in Figure 4. These func-
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Scataglini et al.: A Direct Manufacturing Cost Model for Solid-Oxide Fuel Cell Stacks
Fig. 4 SOFC CHP system design schematics for 50kW CHP system.
the maximal total efficiency of the system. Actual waste heat
utilization and total efficiency will be highly dependent on the
site and heating demands. For example, smaller overall heat
efficiency can result, if waste heat utilization is confined to
building water heating and the building has a relatively low
demand for hot water.
Total fuel cell plate area is taken to be 540 cm2. Active catalyzed area is about 61% of this area, due to plate border
regions and manifold openings. Single cell active area has an
additional 10% area loss, due to the frame sealing process. The
10kWe system consists of 130 cells in a single stack, while the
50kW system has 5 stacks of 130 cells each.
2.3 Stack Manufacturing Process Flow
Three different process parameters have been taken into
account in the cost model: (i) ‘‘Availability,’’ or the percentage
of time that equipment is available to run during the total possible planned production up-time; (ii) ‘‘Performance,’’ a measure of how well the equipment runs within its time of operation; and (iii) ‘‘Process Yield or Quality,’’ a measure of the
number of parts that meet specification compared to how
many were produced.
A major challenge for fuel cell manufacturing cost modeling is that these parameters are not available since data collected by fuel cell manufacturers are not accessible, and each
fuel cell manufacturer uses different toolsets, different manufacturing techniques and produces no more than 100 MW per
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year. As in other costing studies [23–25], the model assumes
that losses decrease with increasing manufacturing volumes
and level of automation, due to: (i) improvement of inline
inspection with greater inspection sensitivity and more accurate response to defects an inline signals; (ii) development of
models that relate inline metrics and measurements to output
responses and performance [26]; and (iii) utilization of greater
feedback systems in manufacturing processing for real time
adjustment of process parameters.
Since vendors and industry advisors do not provide exact
information about these parameters, the approach is to
assume a range for each parameter as described below and
then estimate intermediate values through exponential interpolation depending on annual production volume. The advantage of introducing these parameters in the model is because
using sensitivity analysis it is possible to estimate the impact
of these parameters on manufacturing costs.
2.3.1 Electrode–electrolyte Assembly Functional Cell (EEA)
Based on a literature search and discussions with industry
experts, the steps required for the fabrication of the EEA functional cell are:
(i)
Preparing the anode slurry using a two steps ball milling
process;
(ii) Sieving and de-airing of the anode slurry;
(iii) Tape casting and infrared drying of the anode tape;
(iv) Rolling in a take-up roll of the green tape;
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Cutting and blanking into sheets of the green tape;
Screen printing and infrared drying of subsequent layers
(anode-electrolyte interlayer, electrolyte, cathode-electrolyte interlayer and cathode layer) above the anode sheet;
(vii) First quality check (infrared imaging and ultrasonic
spectroscopy);
(viii) Bonding together the mini-stack of five layers by placing
it in a furnace at elevated temperature (~1,300–1,400 C)
for 24 h [27, 28];
(ix) Laser cutting of the EEA cell to the proper dimensions;
(x) Final quality check (infrared imaging, ultrasonic spectroscopy and vacuum leak test).
In this investigation, slurries are prepared by a two steps
ball milling process. In the first step, solid powders are ball
milled for 12 h in solvent. In the second step, binder and
plasticizer are added and then ball milled for another 12 h
[29]. Quantities of slurry to mill per day are estimated based
on number of cells casted per day and slurry weight of each
layer. Slurry drying time is estimated using the average
evaporation rate value of aqueous slurry described by
Mistler, et al. [30] as suggested in a Battelle report [31].
Assuming that the ratio of the freshly deposited layer thickness to the dried tape thickness is two [32] and multiplying
this freshly deposited layer thickness by its corresponding
liquid density it was possible to obtain the quantity of liquid
removed per unit area. The corresponding slurry drying
time is estimated dividing the quantity of liquid removed
per unit area by an average evaporation rate of the solvent
equal to 2.22 · 10–5 g cm–2 s–1 at room temperature for an air
flow rate of 75 L min–1 [30]. Estimated slurry drying times
are: 24.7 min for the anode slurry, 0.48 min for the electrolyte slurry, 2.2 min for the cathode slurry and 0.44 min for
interlayer slurries. In reality, evaporation rates may be
expected to be faster than the ones considered in this study
since water evaporates more slowly than most organic solvents as n-butyl acetate or 2-butoxyethanol [33].
In the last few years, many studies have been conducted to
evaluate and compare co-fired cells performance and costs to
cells made by multiple firing steps. During co-firing (or co-sintering), all the layers are subjected to the same thermal treatment. A good choice of the sintering temperature is the most
important requirement to consider since it allows to minimize
chemical interaction between various layers and the distortion
of the structure due to mismatch in thermomechanical and
physical properties of the various layers [34]. This means that
the common temperature must be necessarily a compromise
between the highest and the lowest sintering temperature of
the different layers but the residence time in furnace must be
long enough to allow the sintering of the most refractory
layers [28].
The anode is the least refractory layer and must be highly
porous (30–40% porosity). If it is sintered for a longer time
than necessary, the porosity could decrease dramatically and
an over-densification could occur. For this reason, during slurry
formulation, usually pore formers are added in order to control
the porosity of the anode layer. On the contrary, the electrolyte
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has the highest sintering temperature and has a dense structure
with low porosity. Typical co-firing temperature for anode supported cell fabrication with Ni/YSZ anode, YSZ electrolyte and
LSM cathode varying from 1,250 to 1,400 C and co-firing process lasts about 16–24 h [27, 28, 34]. Deformation during sintering is related to different factors as elastic deformation, thermal
deformation, visco-plastic deformation and shrinkage due to
densification. The shrinkage is the factor which most affects the
overall deformation and references [28] and [34] report the linear shrinkage decreases with increasing total volume percentage of dispersant, binder and plasticizer.
Equipment size, cycle times and level of automation vary
with annual production rates. Tape casting machines are sized
depending on production volume, slurry drying time and
casting speed. Tape casting speed varies with annual production volume and machine size from 0.25 m min–1 to 1 m min–1.
Subsequent process modules included in the production line
are sized based on the estimated production capacity and
cycle time of the tape casting machine.
Line availability is assumed to be 80% and process yield to
be 85% at low volumes (<100,000 EEA cells year–1, 10 MWe).
At the highest volumes (>10,000,000 EEA cells year–1,
500 MWe year–1), line availability and process yield are
assumed equal to 95%. For volumes between 100,000 and
10,000,000 EEA cells year–1, the process parameters are found
through exponential interpolation. Line performance is considered equal to 89% for manual configuration and 95% for
semi-automatic and automatic configurations. As a comparison, Fuel Cell Energy Inc. has reported a fabrication yield of
95% at a production volume of 500 kWe year–1 [22].
2.3.2 Interconnect and Frame
The interconnect manufacturing process flow consists of
the following modules: (i) stamping of a sheet roll of Stainless
Steel 441 or Crofer 22 APU by means of a dual die stamper;
(ii) post-stamp cleaning and drying of the metal plate; (iii)
cathodic arc plasma vapor deposition (Arc-PVD) of a manganese cobalt oxide (MCO) spinel coating; and (iv) final inspection. The MCO layer is only applied to one side of the interconnects to protect the cells from chromium poisoning and to
improve cell performance and durability [35]. The dual die
stamper uses two strokes to punch out the manifolds, create
the perimeter of the plate and form the flow fields. Three different manufacturing lines (manual, semi-automatic and fully
automatic) are designed depending on the annual production
volume. The physical vapor deposition step represents the
bottleneck process. Other process modules included in the
production line are sized based on the estimated production
capacity and cycle time of the physical vapor deposition process. Assuming a 1 cm margin on each side of the interconnect [31] and that manifold areas are punched out during
stamping process, a material scrap of 20% is estimated. The
model also assumes that interconnect material waste is
recyclable and sold at a price equal to 40% of the raw material purchase price.
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(v)
(vi)
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Scataglini et al.: A Direct Manufacturing Cost Model for Solid-Oxide Fuel Cell Stacks
Line performance is assumed to be 89% for manual configuration and 95% for semi-automatic and automatic configurations. At low volumes (< 100,000 interconnects year–1,
10 MWe year–1) line availability is assumed to be 80% and process yield to be 85%. At high volumes (>10,000,000 interconnects year–1, 500 MWe year–1), line availability is estimated to
be 95% and process yield to be 99%. For volumes between
100,000 and 10,000,000 interconnects year–1, the process
parameters are found through exponential interpolation.
Frames are manufactured the same way using the same
machines and materials. In case of high tool utilization, additional lines are needed for manufacturing of the frame and a
similar line is considered. If this is the case, a single die stamper
can replace the dual die stamper since no bending is required
for the frame. Assuming a 1 cm margin on each side of the frame
and that cell size slot and manifolds slots are punched out during stamping process, a material scrap of 72% is estimated.
2.3.3 Cell-to-frame Seal
The method of creating a glass seal considered in this study
is adopted from a PNNL study [33]: (i) ball milling of the glass
paste; (ii) dispensing of the paste on EEA cell perimeter by
means of a dispensing robot; (iii) placing of the cell onto the
frame; (iv) placing of a weighted plate onto the cell; (v) loading of the piece in the annealing furnace; and (vi) annealing in
furnace under a static load (450 to 2,200 N). The annealing
process includes four steps: (i) heating up to 600 C with a
heating rate of 3 C min–1; (ii) heating up to 750 C with a heating rate of 5 C min–1; (iii) holding at 750 C for 60 min; and
(iv) cooling to 50 C with a cooling rate of 15 C min–1.
Manual and automatic configurations are included in the
analysis depending on production volume. The manual line
requires three workers whereas the automatic line requires
one worker in the dispensing line and another worker every
four furnaces (1.25 worker line–1). Due to the long thermal
cycle, the annealing process is the process bottleneck here.
Capital costs vary from $600,000 to $1,350,000, based on furnace cost information from Abbot Furnace. Estimated cycle
time ranges from 370 seconds to 62 seconds depending on the
production capacity of each furnace.
2.3.4 Assembly and Conditioning
The assembly and conditioning process is composed of 10
steps:
(i)
Feeding of the anode plate into the system;
(ii) Adding the nickel mesh;
(iii) Dispensing glass sealing paste along the edge of the anode plate and the perimeter of gas manifolds;
(iv) Adding the EEA functional cell;
(v) Dispensing glass sealing paste along the edge of the
cathode plate;
(vi) Adding the cathode plate;
(vii) Pressing the whole stack and adding of end plates and
compression springs etc.;
(viii) Adding power electronics, hosing, and sensors;
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ª 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
(ix) Adding stack housing;
(x) Conditioning and testing of the stack.
Note that steps 1 through 6 form a repeated unit and may
be executed multiple times. The number of repeated units
included in the fuel cell stack depends on the electrical and
thermal characteristic curves and electrical power output of
the fuel cell stack, which determines the fuel cell system size.
Manual assembly of stack repeating units is assumed at
low volume manufacturing (£ 5 MWe year–1), semi-automatic
at production volume £ 50 MWe year–1 and automatic at all
higher production rates. The difference between semi-automatic and automatic configuration is based on the number of
Staubli 6-axis RX160 robots used. Non-repeating stack components are assembled manually at all rates in about 10 min.
Cycle times range from 90 min in case of manual assembly
of the 1 kWe stack block to approximately 20 min in case of
automated assembly of the 10 kWe stack block. Three different
Fuelcon vendor sintering and testing stations are considered
(4-fold, 8-fold and 16-fold) depending on annual production
volume. Sintering and testing process lasts about 24 h including load and unload time. Fuel utilization is 0.8 SLPM for the
1 kWe stack block and 0.91 SLPM for the 10 kWe stack block.
For sealing paste preparation, the same ball mills used for
manufacturing of EEA cells are considered and machines are
sized depending on quantity of paste to mill per day. Line performance is assumed 89% for manual configuration, 95% for
semi-automatic assembly line and 98% for automatic assembly
line. Line availability is assumed to be 80% at low volumes
(10 MWe) and 95% at high volumes (500 MWe). For volumes
between 100,000 and 10,000,000 interconnects year–1, it is
found through exponential interpolation. Process yield is
assumed to be 99.5% at all rates since the vendor is assumed
to take extra precautions and rework to ensure that no material is scrapped. The process yield is varied in the sensitivity
analysis below in order to estimate the impact of this parameter to the assembly and conditioning costs.
2.4 Material Cost
Material costs were obtained from multiple vendors from
Japan, USA, and China. These countries are the primary suppliers for SOFC materials worldwide. Material prices were priced
based on delivery to the geographical center of the USA. Material quality and prices from Chinese suppliers were also evaluated versus US distributors to determine their competiveness.
Material prices for the EEA used in this study are shown in
Table 5. For the EEA, material cost of each layer was calculated
using the weight of the slurry constituents multiplied by the
corresponding material cost ($ kg–1). For the anode supported
cell design, the anode materials contribute to about 75–82% of
the EEA material cost due to the thickness of the anode layer.
Table 6 shows the material prices for the binders, plasticizers,
pore formers, and solvents at different order quantities. As
shown in the tables, material costs are highly dependent on
annual production volume, especially for ceramic materials
used in the fabrication of the EEA cells.
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Table 5 Anode-supported cell material prices.
Function
Material
Vendor (Country)
Order quantity / kg
Price ($ kg–1)
Comments
Anode / Anode-Electrolyte interlayer
NiO powder
AIICHI JITSUGYO (Japan)
1
68.5
CIF USA by sea
Anode / Electrolyte / Interlayers
Anode / Electrolyte / Interlayers
Anode / Electrolyte / Interlayers
8YSZ powder
(8 mol% YSZ)
AIICHI JITSUGYO (Japan)
8YSZ powder
(8 mol% YSZ)
Daiichi (Japan)
8YSZ powder
(8 mol% YSZ)
Inframat Advanced Materials
(USA)
Cathode / Electrolyte-Cathode interlayer LSM powder
Cathode / Electrolyte-Cathode interlayer LSM powder
Inframat Advanced Materials
(USA)
Qingdao Terio Corporation
(China)
5
42.5
CIF USA by sea
10
37
CIF USA by sea
20
34
CIF USA by sea
100
78
CIF USA by sea
1
68
CIF USA by sea
5
63
CIF USA by sea
10
97
CIF USA by sea
100
95
CIF USA by air
1
83
CIF USA by sea
1
139.2
by rail or truck
5
115.8
by rail or truck
10
94.5
by rail or truck
50
71.6
by rail or truck
100
49.7
by rail or truck
1
35.2
by rail or truck
10
29.8
by rail or truck
100
170
by rail or truck
1
95
by rail or truck
10
70
by rail or truck
10
250
CIF USA by air
100
150
CIF USA by air
200
125
CIF USA by air
500
105
CIF USA by air
1
80
CIF USA by air
2
75
CIF USA by air
5
60
CIF USA by air
CIF = price including cost, insurance and freight
A summary for the interconnect materials is summarized in
Table 7 with Stainless Steel 441 as the base case for this study.
Table 8 shows specifications for the MCO powder. Note that a
rough order of magnitude (ROM) estimate for the sealing
prices were obtained from 3M’s Advanced Materials Division
for this analysis and are not shown here, due to confidentiality
restrictions from the supplier.
At high volumes, material cost is one of the dominant cost
drivers in a SOFC stack. In most cases, material prices from
Chinese suppliers are competitive with US-based suppliers,
while prices from Japanese suppliers were the highest among
all vendors.
3 Results and Discussion
Table 9 shows the cost model results for all system sizes
and production rates. The choice of a more expensive material
as Crofer 22 APU instead of SS441 increases the stack manu-
FUEL CELLS 17, 2017, No. 6, 825–842
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facturing cost by 1–14%. If multi-firing is implemented instead
of co-firing, the EEA cost is estimated to increase by about 40–
50% and the stack costs by 20–25%.
Considering the base design, stack cost per unit of electric
power ($ kWe–1) decreases both with increasing system size
and increasing annual production rate (Figures 5 and 6). When
comparing the two key cost drivers, cost seems to be somewhat more sensitive to system size than to production rate,
and the impact of system size diminishes at higher production
volumes.
At the same annual power production rate, stack costs
decrease with larger SOFC system size (Figure 7). This cost
reduction is only related to stack assembly and conditioning
cost. It is more cost-effective to assemble and test fewer large
stacks compared to a larger number of lower-power stacks.
Figure 8 below shows stack manufacturing costs broken
out by component for 10 kWe systems. The largest contributor
to the stack manufacturing cost is the EEA, which constitutes
about 50% of total cost in all cases analyzed. Interconnect and
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Scataglini et al.: A Direct Manufacturing Cost Model for Solid-Oxide Fuel Cell Stacks
Table 6 Binders, plasticizers, pore formers, and solvent prices.
Function
Material
Vendor (Country)
Order quantity / kg
Price / $ kg–1
Comments
Solvent (Anode / Electrolyte)
N-butyl acetate 99,5%
Jiangsu Xiangcanghongrun
Trade Co., Ltd. (China)
100
4.34
CIF USA by sea
1
1,516
CIF USA by sea
10
1.29
CIF USA by sea
Binder (Cathode / Interlayers)
Methocel A4M
ChemPoint Inc. (USA)
1–45,400
18.5–29.6
CIF price
Binder (Anode / Electrolyte)
Butvar B-76
Dowd & Guild, Inc. (CA)
63.5
23.37
by rail or truck
200
21.42
by rail or truck
500
19.47
by rail or truck
1
18.36
by rail or truck
2
17.14
by rail or truck
5.000
16.07
by rail or truck
Plasticizer (Anode/Electrolyte)
Santicizer 160
Univar USA
Confidential information from vendor
Pore former (Anode)
Thermax N990 Thermal
Carbon Black
Cancarb Limited (USA)
Confidential information from vendor
Solvent (Cathode / Interlayers)
2-Butoxyethanol
Jinan Shijitongda Chemical Co.,
Ltd. (China)
1
3.07
CIF USA
10
3.07
CIF USA
100
2.53
CIF USA
1,000,000
2.32
CIF USA
10,000,000
2.29
CIF USA
CIF = price including cost, insurance and freight.
Table 7 Interconnect material costs.
Table 9 Direct manufacturing cost results for SOFC stack.
Component
Material
Cost / $ kg–1
Sheet metal
SS 441 (Tianjin Brilliant Import &
Export Co.,Ltd.)
2.3–1.5
Sheet metal
Crofer 22 APU (Elcogen)
25–10.0
Coating powder
MCO (Qingdao Terio Corporation)
300–250
Table 8 Manganese cobalt oxide powder specifications.
Grade and Specifications
Grades
MCO
2
Specific surface area / m g
–1
5.0–10.0
Particle size (D50 / mm)
0.4–0.6
Feature
Spinel phase black powder
Source: Qingdao Terio Corporation.
cell-to-frame seal each constitute 11–15 % of the stack cost and
decrease with production volume. Stack assembly and conditioning process remains constant at about 9% of the stack cost.
The relative contribution of frame manufacturing cost to overall stack cost increases with production volume, since at low
volumes is assumed that interconnect manufacturing lines are
used and there is no capital cost and building cost associated
with the frames.
At low volumes, process capital and labor costs are the
categories that most affect the stack cost whereas at high vol-
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System
power / kWe
Systems
year–1
Stack cost
Base design /
$ kWe–1
Stack cost
Cost increase
Alternative
/%
–1
design / $ kWe
1
100
5,387
5,463
1.4%
1
1,000
1,196
1,252
4.7%
1
10,000
451
485
7.4%
1
50,000
322
347
7.7%
10
100
1,039
1,096
5.4%
10
1,000
342
376
9.7%
10
10,000
197
221
12.3%
10
50,000
178
202
13.1%
50
100
478
514
7.7%
50
1,000
215
240
11.5%
50
10,000
176
200
13.2%
50
50,000
170
193
13.5%
100
100
339
372
9.8%
100
1,000
194
219
12.4%
100
10,000
171
194
13.5%
100
50,000
168
191
13.7%
250
100
249
274
10.0%
250
1,000
181
204
13.0%
250
10,000
167
190
13.7%
250
50,000
166
189
13.9%
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FUEL CELLS 17, 2017, No. 6, 825–842
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4 Sensitivity Analysis for Stack
Manufacturing Cost
Fig. 5 Stack manufacturing cost variation with system size.
Fig. 6 Stack manufacturing cost variation with annual production rate.
Sensitivity analysis at the component level is
done for 50 kWe systems at all annual production
rates. Sensitivity analysis at the stack level is then
obtained summing the effects of sensitivity analysis
performed at the component level. Global sensitivity
parameters are power density, process yield, manufacturing line performance, manufacturing line
availability, capital cost, discount rate, building cost,
operational cost and hourly labor rate. The impact to
the stack manufacturing cost in $ kWe–1 is calculated
for a +20% change in the sensitivity parameter
being varied.
Figures 10 and 11 show results for production
volumes of 100 and 50,000 systems year–1, respectively. Power density and process yield are the
parameters having the greatest impact on stack
manufacturing cost. In addition, the sensitivity of
these parameters increases with the annual production volume. Line performance also deeply affects
the stack manufacturing cost, since equipment
speed losses cause an increase of annual operating
hours and therefore labor and operational costs.
Availability has negligible impact at the low volume of 100 systems per year, since in that case, its
variation causes only an increase of manufacturing
line utilization rate but not an increase of machines
needed to guarantee the required annual production. Labor rate is less important with higher
production volume because of higher levels of
automation. Operating and building costs are factors which have less impact on stack manufacturing cost in all cases.
5 Comparison to Cost Targets and Other
Industry Cost Estimates
Fig. 7 Stack manufacturing costs at the same global produced capacity of
10 MWe.
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A comparison of these results with U.S. Department of Energy (DOE) cost targets and industry
reported costs is shown in Figure 12. A DOE NETL
(National Energy Technology Laboratory) report
[36] states a target of $225 kWe–1 (in 2011 or about
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ORIGINAL RESEARCH PAPER
ume material cost dominates followed by process
capital cost. Figure 9 demonstrates that with
increasing production volume process/operational
costs increase and labor cost decreases at greater
level of automation. Capital and building costs
decrease due to the higher equipment utilization,
and scrap cost decreases since the cost model
assumes lower defective rate at higher production
volumes.
ORIGINAL RESEARCH PAPER
Scataglini et al.: A Direct Manufacturing Cost Model for Solid-Oxide Fuel Cell Stacks
meet the DOE target above an annual production
volume of about 350 MWe.
Across the range of capacities from 250 MWe to
1,000 MWe shown in Figure 12 the modeled results
(Model (Base Case)) are within 17–20% of FCE’s estimated costs and below the DOE target across this
range of power levels. The lower modeled cost is
perhaps not surprising given that the cost model
may not capture all process steps including defect
inspections and metrology steps, may underestimate
process losses and product rework operations and
frequency, and may overestimate product cycle
times and process equipment performance levels,
among other factors. Indeed, other cost models in
the literature add a 10–20% ‘‘cost margin’’ or cost
contingency to their manufacturing cost estimates to
account for this additional manufacturing cost, e.g.,
Fig. 8 Disaggregation of stack cost by relative percentage of stack components cost
for minor pieces of equipment or part replacements
to overall stack cost for 50 kWe systems.
that are not explicitly costed [10, 36]. Factoring a cost
margin of 20% into our model, in order to reach the
DOE target it would be necessary to produce (see
Figure 13) at least an annual equivalent power of
100 MWe (10,000 units of 10 kWe power or 1,000
units of 100 kWe power) or 250MWe for 5kWe systems at 50,000 units year–1. In contrast, adding a cost
margin higher than 20%, a production of 100 MWe
would not be sufficient to meet the DOE target.
Figure 14 shows the modeled stack costs at much
lower annual manufacturing volumes (2.5–50 MWe).
Here even with a 30% cost margin, modeled costs
are 34–47% lower than recently reported results
from SOLIDpower [37]. SOLIDpower results correspond to a 2.5 kWe system at volumes of 1000, 5000,
and 20,000 units per year. If we assume a 30% lower
process yield for the various stack modules and
apply a 30% cost margin, modeled costs are still
Fig. 9 Disaggregation of stack cost by relative percentage of cost components to
10–20% lower than SOLIDpowers estimates. There
overall stack cost for 50 kWe systems.
are three primary factors for why modeled stack
costs are much lower for this case of low power,
lower annual volume production:
(i)
This work is primarily based on FCE/VersaPower’s
$238 kWe–1 in 2015) for mass manufacturing but without speciSOFC stack architecture and reported process steps and
fying a manufacturing level.1) We assume this is for a level of
stack materials. The base FCE/VersaPower power
100 MWe per year and above. Also shown are manufacturing
system is also a larger system (10–50 kWe and higher)
cost projections reported by FuelCell Energy (FCE) [22]. Note
versus the micro-CHP system sized of SOLIDpower
that the FCE model assumes a slightly higher power density
(2.5 kWe). Thus, differences could arise both in material
at 0.299 W cm–2 than the 0.282 W cm–2 assumed in this work.
compositions and differences in process assumptions.
In the past years, FuelCell Energy Inc. has performed stack
For example, the EES stack is known to be a key cost
cost modeling for net electricity capacity of 5 kWe, 10 kWe and
driver for processing and materials, and the implemen20 kWe and a production volume of 50,000 units per year.
tation of single step co-firing versus multi-step firing is a
Figure 12 shows that the FCE estimates for manufacturing cost
critical contributor to reducing capital and overall manufacturing costs.
(ii) Lower volume may include more purchased compo–
nents. As described above, our analysis is focused on
1) From NETL [34]: ‘‘The stack cost target for the Nth of a kind
costs that can be achieved at scaled up, high process volunit assuming mass-manufacturing related cost advantages
umes and a vertically integrated factory is assumed. At
along with learning from repetition and increased capacity.’’
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Fig. 10 Global sensitivity analysis for 50 kWe system at the production volume of
100 systems year–1.
6 Conclusions
Fig. 11 Global sensitivity analysis for 50 kWe system at the production volume of
50000 systems year–1.
Fig. 12 Stack manufacturing costs for annual manufacturing volumes of
250-1000 MW. The base case result is within 17-20% of FCE’s reported cost estimates.
FUEL CELLS 17, 2017, No. 6, 825–842
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Presented here are the results of a detailed manufacturing cost model for SOFC fuel cell stacks, and
comparisons of those results to stack manufacturing
costs made by two SOFC stack manufacturers.
Under the assumptions made here, manufacturing
costs are within 17–20% of industry-estimated costs.
Factoring in a 20% cost margin into our modeled
results implies that the DOE target of $238 kWe–1 can
be achieved at an annual manufacturing volume of
100–250 MWe depending on system size and annual
production rate. Key assumptions include vertically
integrated manufacturing and high speed, relatively
high yield stack deposition processes for the EEA,
and cost reductions in material costs with higher
volume purchases from material suppliers. Implicit
in these assumptions is the assumption of continuous ‘‘learning-by-doing’’ as manufacturing volumes
increase to improve process yields, and accumulation of knowledge regarding best manufacturing
processes and defect mode characterization and
understanding.
We found that the EEA makes up about 50% of
the stack cost at all annual production volumes, followed by the cell sealing process at 10–18% and
interconnects at 10–18% of the stack manufacturing
cost. Single step co-firing of the EEA vs. multi-step
co-firing, process yield and power density are the
most sensitive parameters for the stack cost at both
low and high annual production volumes. At low
production volumes (5 MWe per year), line perfor-
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ORIGINAL RESEARCH PAPER
(iii)
lower volumes, there may be more purchased
parts than have been assumed here and these
could drive up costs since any purchased stack
component would incur an additional markup. For example, the base cost shown in
Figure 14 would be about 10% higher if interconnects were purchased from a third party
vendor which has the same cost structure assumed here and assuming a 100% markup.
At low manufacturing volumes, process yields
are expected to be lower and process costs
higher than at high manufacturing volumes.
The range or errors in modeled costs can thus
be expected be higher than at higher process
volumes when high process yields are assumed at high volumes. For example, costs
can be higher at lower volumes due to higher
labor costs (more engineering labor vs. factory
workers, more tool set up time, more reworked processes, more manual inspection,
lower tool availability and tool performance,
lower process yield, etc.).
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ORIGINAL RESEARCH PAPER
scope of this work. Additional future work includes
further detailed study of lower power (1–5 kWe) fuel
cell stack design and manufacturing, and expanding
the scope of the analysis to include balance of plant
costs and overall fuel cell system total costs of ownership.
Acknowledgements
Fig. 13 DOE cost target vs. modeled stack manufacturing costs with a 20% cost
margin.
This work was supported by the U.S. Department
of Energy, Office of Energy Efficiency and Renewable Energy (EERE) Fuel Cells Technologies Office
(FCTO) under Lawrence Berkeley National Laboratory Contract No. DE-AC02- 05CH11231. The
authors would also like to acknowledge inputs from
contributions of Brian Borglum (FuelCell Energy),
Nguyen Minh (University of California San Diego),
and Prof. Jack Brouwer (University of California,
Irvine).
Fig. 14 Stack manufacturing costs for annual manufacturing volumes of 2.5–
50 MW. Even with a 30% margin, modeled costs are 34–47% lower than SOLIDpower cost estimates (both estimates are in 2015).
mance and labor rate are the next most sensitive parameters,
while at high production volume (2500 MWe per year), material costs and tool availability also become important cost sensitivities.
Key uncertainties in this type of modeling are the exact
‘‘state of the art’’ design details for SOFC stacks, the actual
process yields of stack process modules, and the details of
stack composition and materials. Reverse engineering of a
commercial fuel cell through stack performance characterization and cross sectional analysis of an actual fuel cell stack
would provide valuable information but this was beyond the
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ORIGINAL RESEARCH PAPER
Appendix
Table A.1 Process parameters for tape casting machines.
Tape casting machines (HED International Inc.)
1
Model
TC-251
TC-501
TC-502
TC-1002
TC-1004
Cost ($)
Contact vendor1
Contact vendor1
Contact vendor1
Contact vendor1
Contact vendor1
Estimated capacity / MWe year–1
£5
10–25
50–100
250–500
‡1,000
# of machines
1
1
1
2–3
‡6
# of workers/machine
2
2
2
2
2
Casting Length / m
7.7
15.4
15.4
30.8
30.8
Casting Width / mm
300
300
600
600
1,200
Casting Speed / m min–1
0.25
0.5
0.5
1.00
1.00
Drying time / min
10.0
10.0
10.0
10.0
10.0
Required tunnel length / m
6.17
12.35
12.35
24.7
24.7
No of cells casted in a row
1
1
3
3
6
Cell dimensions including margin / mm
0.1915
0.1915
0.1915
0.1915
0.1915
Mylar roll length / m
1,000
1,000
1,000
1,000
1,000
Cycle time / part–1
53.02
25.57
8.52
4.49
2.25
Vendor shared equipment costs with authors for this study, but asked not to disclose them.
Table A.2 Process parameters for screen printing lines
Screen printing lines (Manncorp)
Manual Line (£ 5 MWe)
Cost / $
Length / m
Width / m
Consumption / kW
Cycle time / s
Parts cycle–1
# of workers
Screen printer (PB-2300)
20,000
0.745
0.96
3.00
35
1
1
Cycle time / s
Parts cycle–1
# of workers
12
1
1
Cycle time / s
Parts cycle–1
# of workers
12
3
1
Cycle time / s
Parts cycle–1
# of workers
12
3
1
Reflow oven (CR-3000)
10,000
1.8
0.855
10.00
PCB conveyor (BC-100X-W1)
3,595
1.2
0.8
0.1
Automatic Line #1 (5-25 MWe)
Cost / $
Length / m
Width / m
Consumption / kW
PCB Loader (BL-460W-ST)
10,695
1.75
0.96
0.3
Screen Printer (AP430)
60,000
1.45
1.12
3
PCB conveyor (BC-100X-W1)
3,595
1.2
0.8
0.1
Reflow oven (CR-4000)
25,000
2
1.2
15
Automatic Line #2 (50-100 MWe)
Cost / $
Length / m
Width / m
Consumption / kW
PCB Loader (BL-460W-ST)
10,695
1.75
0.96
0.3
Screen Printer (AP660)
80,200
1.13
0.89
3
PCB conveyor (BC-100X-W1)
3,595
1.2
0.8
0.1
Reflow oven (CR-5000)
35,000
3
1.51
22
Automatic Line #3 (‡ 250 MWe)
Cost / $
Length / m
Width / m
Consumption / kW
PCB Loader (BL-460W-ST)
10,695
1.75
0.96
0.3
Screen Printer (AP660)
80,200
1.13
0.89
3
PCB conveyor (BC-100X-W1)
3,595
1.2
0.8
0.1
Reflow oven (CR- 8000)
50,000
4.8
1.51
40
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Table A.3 Process parameters for co-firing kilns.
Co-firing kilns (Keith Company)
Model
Low volume (envelope)
Mid volume (envelope)
High volume (robotic)
Type of load
manual
manual
robotic
Kiln capacity / parts cycle–1
256
2,000
4,960
Kiln capacity / MWe year–1
0.1
1–5
>5
Furniture cost / $
30000
146,000
200,000
Cost + installation / $
150,000
730,000
2,000,000
Furnace total cost / $
180,000
876,000
2,200,000
Load/unload time / h cycle
–1
2.2
16.7
6
# of workers
2
2
0
Sintering time / h
24
24
24
Total cycle time / h
26.2
40.7
30
Average consumption / kW
50
240
320
Table A.4 Process parameters for interconnect manufacturing lines.
Interconnect manufacturing lines
Equipment
Manual Line
Semi-Automatic Line
Automatic Line
Cost / $
Average Consumption / kW
Cost / $
Average Consumption / kW
Cost / $
Average Consumption / kW
50,000
7.5
480,000
17
480,000
17
165,000
2
165,000
2
200,000
5
500,000
10
750,000
10
165,000
2
165,000
2
500,000
140
1,920,000
504
2,875,000
756
Pick & Place Robot
165,000
2
Inspection
250,000
10
Dual Die Stamper
Pick & Place Robot
Cleaner/Dryer
Pick & Place Robot
PVD
Cycle Time / s part
–1
# of workers line–1
28
10
7
1
1
0
Table A.5 Process parameters for annealing furnaces.
Annealing Furnaces (Abbott Furnace Company)
Model
Type A
Type B
Type C
Type D
Type of load
Manual
Robotic
Robotic
Robotic
Furnace capacity / MWe year–1
£1
=5
= 10
>10
Conveyor speed / m min–1
0.05
0.09
0.09
0.09
Furnace width / m
0.32
0.32
0.64
0.92
Furnace length / m
15
30
30
30
Drying time / min
330
330
330
330
Piece width / m
0.28
0.28
0.28
0.28
Piece length / m
0.28
0.28
0.28
0.28
Cycle time per row / s
369.6
184.8
184.8
184.8
Pieces per row
1
1
2
3
Cycle time per piece / s
369.60
184.80
92.40
61.60
# of workers
2
0
0
0
Average consumption / kW
35
35
67
100
Furnace Cost / $
600,000
1,100,000
1,200,000
1,350,000
840
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FUEL CELLS 17, 2017, No. 6, 825–842
Scataglini et al.: A Direct Manufacturing Cost Model for Solid-Oxide Fuel Cell Stacks
ORIGINAL RESEARCH PAPER
Table A.6 Process parameters for assembly and testing.
Stack assembly lines
Model
–1
Manual
Semi-automatic
Automatic
<100 k
100 k–600 k
>600 k
Cost / $
20,000
400,000
850,000
# of workers / line–1
2
2
1
Cycle time / s stack–1
120
28
20
4-fold station with 1 cart
8-fold station with 2 carts
16-fold station with 4 carts
No. of EEA cells / year
Stack sintering and testing stations (FuelCon)
Model
Stacks tested / cycle
–1
4
8
16
Cost / $ unit–1
400,000
700,000
1,300,000
# of workers station–1
1
1
1
Loading time / min
20
40
60
Cycle time / h
16–24
16–24
16–24
Average consumption / kW
15
30
60
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FUEL CELLS 17, 2017, No. 6, 825–842