U.S. patent application number 14/563862 was filed with the patent office on 2015-04-09 for methodology for design of a manufacturing facility for fabrication of solid state hybrid thin film energy storage and conversion devices.
The applicant listed for this patent is SAKTI3, INC.. Invention is credited to Yen-Hung CHEN, Marc LANGLOIS, Ann Marie SASTRY, Chia-Wei WANG, Xiangchun ZHANG.
Application Number | 20150100146 14/563862 |
Document ID | / |
Family ID | 46065072 |
Filed Date | 2015-04-09 |
United States Patent
Application |
20150100146 |
Kind Code |
A1 |
SASTRY; Ann Marie ; et
al. |
April 9, 2015 |
METHODOLOGY FOR DESIGN OF A MANUFACTURING FACILITY FOR FABRICATION
OF SOLID STATE HYBRID THIN FILM ENERGY STORAGE AND CONVERSION
DEVICES
Abstract
A method and system for designing a manufacturing facility for
solid state thin film battery devices. The method can include
providing a plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities. A plurality of variables can be assigned for the
plurality of processing tools. A target financial variable can be
defined to evaluate different manufacturing processing tool
configurations. The plurality of variables in the tensor
relationship can be processed to reduce a magnitude of the target
variable. An optimized set of the plurality of processing tools and
respective configuration with the plurality of tools associated
with the reduced magnitude of the target variable can be determined
through processing. The optimized set of the plurality of
processing tools in the respective configuration can be used in the
one or more manufacturing facilities for the manufacture of a solid
state thin film battery device.
Inventors: |
SASTRY; Ann Marie; (Ann
Arbor, MI) ; ZHANG; Xiangchun; (Ann Arbor, MI)
; WANG; Chia-Wei; (Ypsilanti, MI) ; CHEN;
Yen-Hung; (Ann Arbor, MI) ; LANGLOIS; Marc;
(Ann Arbor, MI) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
SAKTI3, INC. |
Ann Arbor |
MI |
US |
|
|
Family ID: |
46065072 |
Appl. No.: |
14/563862 |
Filed: |
December 8, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
13359374 |
Jan 26, 2012 |
8930008 |
|
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14563862 |
|
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Current U.S.
Class: |
700/99 |
Current CPC
Class: |
G05B 2219/31396
20130101; G05B 2219/31395 20130101; Y02P 90/02 20151101; G05B
19/418 20130101; G06F 30/13 20200101; G05B 19/41805 20130101 |
Class at
Publication: |
700/99 |
International
Class: |
G06F 17/50 20060101
G06F017/50; G05B 19/418 20060101 G05B019/418 |
Claims
1. A manufacturing facility designed from a method for forming a
manufacturing facility, comprising: one or more facilities; a
plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities; a plurality of variables assigned, respectively, for
the plurality of processing tools, the plurality of variables being
in a tensor format; wherein an optimized set of the plurality of
processing tools operable for the manufacture of a solid state thin
film battery device, the optimized set of the plurality of
processing tools configured by defining a target financial variable
to evaluate different manufacturing processing tool configurations,
the target financial variable including at least internal rate of
return (IRR), modified internal rate of return (MIRR), net present
value (NPV) and weighted average cost of capital (WACC); processing
the plurality of variables in the tensor relationship to reduce a
magnitude of the target variable; determining an optimized set of
the plurality of processing tools and respective configuration with
the plurality of processing tools associated with the reduced
magnitude of the target variable; and using the optimized set of
the plurality of processing tools in the respective configuration
in the one or more manufacturing facilities.
2. A method for forming a manufacturing facility comprising:
providing a plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities, wherein the plurality of processing tools comprises at
least two tools selected from a physical vapor deposition based
thin film coater, chemical vapor deposition based thin film coater,
atomic layer deposition thin film coater, transport robot, winder,
slitter, slitter using a laser process, packaging machine using a
technique of at least dip coating, and robotic arms for attaching
leads, wiring, moving, handling and electronic control component
assembling; assigning a plurality of variables, respectively, for
the plurality of processing tools; providing the plurality of
variables in a tensor format; defining a target financial variable
to evaluate different manufacturing processing tool configurations;
processing the plurality of variables in the tensor relationship to
reduce a magnitude of the target variable; determining a set of the
plurality of processing tools and respective configuration with the
plurality of tools associated with the reduced magnitude of the
target variable; using the set of the plurality of processing tools
in the respective configuration in the one or more manufacturing
facilities; and operating the set of tools for the manufacture of a
solid state thin film battery device.
3. A method for forming a manufacturing facility comprising:
providing a plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities; assigning a plurality of variables, respectively, for
the plurality of processing tools, wherein the plurality of
variables comprises capital cost of the tool, throughput of the
tool, downtime of the tool, yield of the tool, efficiency of the
tool, material load and unload time of the tool, preparation time
of the tool, work in process for the tool and operational cost of
the tool including labor cost, electricity cost, and other cost;
providing the plurality of variables in a tensor format; defining a
target financial variable to evaluate different manufacturing
processing tool configurations; processing the plurality of
variables in the tensor relationship to reduce a magnitude of the
target variable; determining an optimized set of the plurality of
processing tools and respective configuration with the plurality of
tools associated with the reduced magnitude of the target variable;
using the optimized set of the plurality of processing tools in the
respective configuration in the one or more manufacturing
facilities; and operating the optimized set of tools for the
manufacture of a solid state thin film battery device.
4. The method of claim 1 wherein the target financial variable is
calculated based on inputs comprising capital expenditure,
production rate, profit of one single product unit, operation
expenditure and discount rate.
5. The method of claim 2 wherein the physical vapor deposition
based thin film coater includes at least one of the processing
facilities comprising vacuum chamber, electron-beam evaporator,
thermal evaporator, pulsed laser deposition tool, flash evaporator
and ion-beam assisted deposition tool and ion-beam sputtering tool;
wherein the physical vapor deposition based thin film coater.
6. The method of claim 1 wherein the targeted financial variable is
simplified as a ratio of total capital expenditure over production
rate for a first-order analysis.
7. The method of claim 6 wherein the total capital expenditure is
provided by a sum of the capital expenditure of the plurality of
processing tools associated with processing facilities included
inside the tools.
8. The method of claim 6 wherein the production rate is provided by
a throughput rate of a rate-limiting processing tool.
9. A method for forming a manufacturing facility comprising:
providing a plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities; assigning a plurality of variables, respectively, for
the plurality of processing tools; providing the plurality of
variables in a tensor format; defining a target financial variable
to evaluate different manufacturing processing tool configurations;
processing the plurality of variables in the tensor relationship to
reduce a magnitude of the target variable; determining a set of the
plurality of processing tools and respective configuration with the
plurality of tools associated with the reduced magnitude of the
target variable; using the set of the plurality of processing tools
in the respective configuration in the one or more manufacturing
facilities; and operating the set of tools for the manufacture of a
solid state thin film battery device, wherein the manufacturing
facility is configured with a design comprising a continuously
moving web design, a carousel design, or a cluster design; wherein
the continuously moving web design uses a flexible substrate or a
rigid substrate including glass.
10. A system for designing a manufacturing plant, the system
comprising: a computer readable memory device, the computer
readable memory including: one or more codes directed to a
plurality of tool parameters corresponding respectively to a
plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities; at least one code directed to a plurality of variables,
respectively, for the plurality of processing tools; whereupon the
plurality of variables are arranged in a tensor format; one or more
codes directed to a processing tool configuration tensor; a tensor
operation module configured to process the plurality of variables
and the configuration tensor to obtain production rate, capital
expenditure, and operation expenditure; a financial modeling module
to reduce a magnitude of a target financial variable associated
with a set of the plurality of variables and the configuration
tensor; the target financial variable comprising at least internal
rate of return (IRR), modified internal rate of return (MIRR), net
present value (NPV) and weighted average cost of capital (WACC); an
optimization module configured to output an optimized configuration
tensor associated with the optimal target financial variable value;
and a post-processing module configured to convert the optimal
configuration tensor to output an optimized set of tools and
associated configuration for the optimized set of tools.
11. The system of claim 10 wherein the processing tool
configuration tensor is a n-order tensor with n dimensions to index
a plurality of specifications comprising at least the processing
step, allocated locations for tools inside the processing step,
processing tool type and the type of facility used inside a
processing tool.
12. The system of claim 10 wherein the processing tool
configuration tensor comprises elements which have binary values of
zero and one.
13. The system of claim 10 wherein the tensor operation module
comprises adding two tensors, multiplying two tensors, transposing
first-order and second-order tensors, contracting a tensor and
finding the maximum or minimum element of a tensor or a subset of
the tensor along with specified dimensions.
14. The system of claim 10 wherein the optimization module
comprises one or more codes directed to an integer programming
optimization process applying enumerative techniques,
branch-and-bound techniques, or cutting planes techniques; wherein
the optimization module comprises one or more codes directed to an
integer programming optimization process applying genetic algorithm
techniques.
15. The system of claim 10 wherein the post-processing module
comprises importing the optimal configuration tensor, identifying
the non-zero elements which have exactly values of one and
outputting the optimal configuration information with
specifications of which type of and how many processing tools are
used for each processing step associated with which type of and how
many processing facilities are used inside each processing
tool.
16. A method for forming a manufacturing facility comprising:
providing a plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities; assigning a plurality of variables, respectively, for
the plurality of processing tools; providing the plurality of
variables in a tensor format; defining a target financial variable
to evaluate different manufacturing processing tool configurations;
processing the plurality of variables in the tensor relationship to
reduce a magnitude of the target variable; determining a set of the
plurality of processing tools and respective configuration with the
plurality of tools associated with the reduced magnitude of the
target variable; using the set of the plurality of processing tools
in the respective configuration in the one or more manufacturing
facilities; and operating the set of tools for the manufacture of a
solid state, hybrid thin film energy storage and conversion device,
the solid state, hybrid thin film energy storage and conversion
device including at least one of a solar cell device/battery
device, an optical device/battery device, a capacitor
device/battery device, a fuel cell device/battery device, a first
battery device/second battery device or a micro-combustion engine
device/battery device.
17. A method for forming a manufacturing facility comprising:
providing a plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities; assigning a plurality of variables, respectively, for
the plurality of processing tools; providing the plurality of
variables in a tensor format; defining a target financial variable
to evaluate different manufacturing processing tool configurations,
wherein the target financial variable comprises at least internal
rate of return (IRR), modified internal rate of return (MIRR), net
present value (NPV) or weighted average cost of capital (WACC);
processing the plurality of variables in the tensor relationship to
reduce a magnitude of the target variable; determining a set of the
plurality of processing tools and respective configuration with the
plurality of tools associated with the reduced magnitude of the
target variable; using the set of the plurality of processing tools
in the respective configuration in the one or more manufacturing
facilities; and operating the set of tools for the manufacture of a
solid state, hybrid thin film energy storage and conversion device.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application claims priority to and is a
continuation of U.S. patent application Ser. No. 13/359,374, filed
on Jan. 26, 2012, which is incorporated herein by reference in its
entirety for all purposes.
BACKGROUND OF THE INVENTION
[0002] This present invention relates to manufacture of
electrochemical cells. More particularly, the present invention
provides a method and system for a manufacturing facility for
fabrication of thin film energy devices. Merely by way of example,
the invention has been provided for the manufacture of lithium
based cells, but it would be recognized that other materials such
as zinc, silver, copper and nickel could be designed in the same or
like fashion. Additionally, such batteries can be used for a
variety of applications such as portable electronics (cell phones,
personal digital assistants, music players, video cameras, and the
like), power tools, power supplies for military use
(communications, lighting, imaging and the like), power supplies
for aerospace applications (power for satellites), and power
supplies for vehicle applications (hybrid electric vehicles,
plug-in hybrid electric vehicles, and fully electric vehicles). The
design of such batteries is also applicable to cases in which the
battery is not the only power supply in the system, and additional
power is provided by a fuel cell, other battery, IC engine or other
combustion device, capacitor, solar cell, etc.
[0003] Common electro-chemical cells often use liquid electrolytes.
Such cells are typically used in many conventional applications.
Alternative techniques for manufacturing electro-chemical cells
include solid state cells. Such solid state cells are generally in
the experimental state, have been difficult to make, and have not
been successfully produced in large scale. Although promising,
solid state cells have not been achieved due to limitations in cell
structures and manufacturing techniques. These and other
limitations have been described throughout the present
specification and more particularly below.
[0004] Solid state batteries have been proven to have several
advantages over conventional batteries using liquid electrolyte in
lab settings. Safety is the foremost one. Solid state battery is
intrinsically more stable than liquid electrolyte cells since it
does not contain a liquid that causes undesirable reaction,
resulting thermal runaway, and an explosion in the worst case.
Solid state battery can store over 30% more energy for the same
volume or over 50% more for the same mass than conventional
batteries. Good cycle performance, more than 10,000 cycles, and a
good high temperature stability also has been reported.
[0005] Despite of these outstanding properties of solid state
batteries, there are challenges to address in the future to make
this type of batteries available in the market. To exploit the
compactness and high energy density, no metal housing or excessive
substrate should be used. To be used in variety of applications
such as consumer electronics or electric vehicle, large area and
fast film deposition techniques at low cost should be developed.
Also, a solid state, hybrid thin film energy storage and conversion
device, such as solid-a state battery, a solid oxide fuel cell, a
capacitor, a photovoltaic cell and a hybrid device of these,
consists of several components of thin film layers. These thin film
layers are made from different materials and of different
thicknesses. The deposition rate of laying down a material using a
physical vapor deposition technique to form the thin film layer
varies with the material and the processing technique used. Each
individual layer requires a different time to finish to make a thin
film device.
[0006] The production rate of solid state batteries, in terms the
number of device units made per unit time, depends on the slowest,
rate-limiting processing step for the layer with the largest
thickness to deposition rate ratio. Multiple deposition zones and
multiple deposition chambers are used to speed up the rate-limiting
processing step by distributing the deposition task in parallel to
the assigned multiple zones and chambers. However, the added
deposition zones and chambers increase the total capital and
operational expenditure for the manufacturing facility. It is
necessary to optimize the number of deposition zones and chambers
to balance the competition between cost and production rate. The
same optimization necessity exists for other solid state, hybrid
thin film energy storage and conversion device manufacturing
processing steps including chemical vapor deposition, atomic layer
deposition, winding, slitting, packaging using a technique of at
least but not limited to dip coating, and robotic arm operations
for attaching leads, wiring, moving, handling and electronic
control component assembling.
[0007] However, the existing manufacturing facilities for solid
state, hybrid thin film energy storage and conversion devices,
including solid-state batteries, solid oxide fuel cells,
capacitors, photovoltaic cells and hybrid devices of these, are
designed in an arbitrary and subjective intuition-based fashion
without conducting a systematical and mathematical analysis to
identify the optimal design.
[0008] From the above, it is seen that techniques for improving the
manufacture of solid state cells are highly desirable.
BRIEF SUMMARY OF THE INVENTION
[0009] This present invention relates to manufacture of
electrochemical cells. More particularly, the present invention
provides a method and system for a manufacturing facility for
fabrication of thin film energy devices. Merely by way of example,
the invention has been provided for the manufacture of lithium
based cells, but it would be recognized that other materials such
as zinc, silver, copper and nickel could be designed in the same or
like fashion. Additionally, such batteries can be used for a
variety of applications such as portable electronics (cell phones,
personal digital assistants, music players, video cameras, and the
like), power tools, power supplies for military use
(communications, lighting, imaging and the like), power supplies
for aerospace applications (power for satellites), and power
supplies for vehicle applications (hybrid electric vehicles,
plug-in hybrid electric vehicles, and fully electric vehicles). The
design of such batteries is also applicable to cases in which the
battery is not the only power supply in the system, and additional
power is provided by a fuel cell, other battery, IC engine or other
combustion device, capacitor, solar cell, etc.
[0010] In an embodiment, the present invention presents a system
for and a methodology to design a manufacturing facility for the
fabrication of solid state, hybrid thin film energy storage and
conversion devices using a systematical and mathematical approach
which applies a tensorial notation to represent processing tool
configuration and integer programming-based optimization to
identify the optimal manufacturing facility configuration to
maximize specified target financial variables including internal
rate of return (IRR), modified internal rate of return (MIRR), net
present value (NPV) and weighted average cost of capital
(WACC).
[0011] In an embodiment, the present invention provides a method
for forming a manufacturing facility. The method can include
providing a plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities. A plurality of variables can be assigned, respectively,
for the plurality of processing tools. These variables can be
provided in a tensor format. A target financial variable can be
defined to evaluate different manufacturing processing tool
configurations. The plurality of variables in the tensor
relationship can be processed to reduce a magnitude of the target
variable. Through the processing, an optimized set of the plurality
of processing tools and respective configuration with the plurality
of tools associated with the reduced magnitude of the target
variable can be determined. The optimized set of the plurality of
processing tools in the respective configuration can be used in the
one or more manufacturing facilities. Furthermore, the optimized
set of tools can be operated for the manufacture of a solid state
thin film battery device. Those skilled in the art will recognize
other variations, modifications, and alternatives.
[0012] In an embodiment, the present invention provides a system
for designing a manufacturing plant. This system can include a
computer readable memory device, one or more codes directed to a
plurality of variables, a tensor operation module, a financial
modeling module, an optimization module, and a post-processing
module. The computer readable memory device can include one or more
codes directed to a plurality of tool parameters corresponding
respectively to a plurality of processing tools for arrangement
within a predetermined spatial region of one or more manufacturing
facilities. The one or more codes directed to a plurality of
variables, respectively, can be for the plurality of processing
tools, whereupon the plurality of variables are arranged in a
tensor format, with the one or more codes directed to a processing
tool configuration tensor. The tensor operation module can be
configured to process the plurality of variables and the
configuration tensor to obtain the production rate, capital
expenditure, and operation expenditure. The financial modeling
module can be used to reduce a magnitude of a target financial
variable associated with a set of the plurality of variables and
the configuration tensor. The target financial variable can include
at least the internal rate of return (IRR), modified internal rate
of return (MIRR), the net present value (NPV), and the weighted
average cost of capital (WACC). The optimization module can be
configured to output an optimized configuration tensor associated
with the optimal target financial variable value. The
post-processing module can be configured to convert the optimal
configuration tensor to output the optimized set of tools and
associated configuration of the set of tools. Those skilled in the
art will recognize other variations, modifications, and
alternatives.
[0013] Benefits are achieved over conventional techniques.
Depending upon the specific embodiment, one or more of these
benefits may be achieved. In one or more embodiments, the present
invention provides a method for designing solid state thin film
energy devices that are optimized to minimize manufacturing time,
costs, and flaws, as well as a system implementing such a method.
Of course, there can be other variations, modifications, and
alternatives.
[0014] The present invention achieves these benefits and others in
the context of known process technology. However, a further
understanding of the nature and advantages of the present invention
may be realized by reference to the latter portions of the
specification and attached drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] The following diagrams are merely examples, which should not
unduly limit the scope of the claims herein. One of ordinary skill
in the art would recognize many other variations, modifications,
and alternatives. It is also understood that the examples and
embodiments described herein are for illustrative purposes only and
that various modifications or changes in light thereof will be
suggested to persons skilled in the art and are to be included
within the spirit and purview of this process and scope of the
appended claims.
[0016] FIG. 1 is a simplified diagram of a thin film battery
manufacturing plant layout according to an embodiment of the
present invention;
[0017] FIG. 2 is a simplified diagram of modules of the code
included in the manufacturing plant design system according to an
embodiment of the present invention;
[0018] FIG. 3 is a simplified comparison of an example plant design
configuration against the optimized design configuration;
[0019] FIG. 4 is a simplified illustration of the set up of
configuration tensor according to an embodiment of the present
invention;
[0020] FIG. 5 is a simplified illustration of the set up of a
fourth-order configuration tensor according to an embodiment of the
present invention;
[0021] FIG. 6 is a simplified illustration of a serially configured
continuously moving web design according to an embodiment of the
present invention;
[0022] FIG. 7 is a simplified illustration of a carousel design
configuration; and
[0023] FIG. 8 is a simplified illustration of a carousel design and
its optimal configuration that yields the best internal rate of
return.
DETAILED DESCRIPTION OF THE INVENTION
[0024] This present invention relates to manufacture of
electrochemical cells. More particularly, the present invention
provides a method and system for a manufacturing facility for
fabrication of thin film energy devices. Merely by way of example,
the invention has been provided for the manufacture of lithium
based cells, but it would be recognized that other materials such
as zinc, silver, copper and nickel could be designed in the same or
like fashion. Additionally, such batteries can be used for a
variety of applications such as portable electronics (cell phones,
personal digital assistants, music players, video cameras, and the
like), power tools, power supplies for military use
(communications, lighting, imaging and the like), power supplies
for aerospace applications (power for satellites), and power
supplies for vehicle applications (hybrid electric vehicles,
plug-in hybrid electric vehicles, and fully electric vehicles). The
design of such batteries is also applicable to cases in which the
battery is not the only power supply in the system, and additional
power is provided by a fuel cell, other battery, IC engine or other
combustion device, capacitor, solar cell, etc.
[0025] FIG. 1 is a simplified diagram of a thin film battery
manufacturing plant layout according to an embodiment of the
present invention. This diagram is merely an illustration and
should not unduly limit the scope of the claims herein. As shown,
the plant layout includes several rotating units that control a
moving surface, such as a conveyer belt or web. Batteries or other
sources of energy can be used to drive the rotating units. The
moving surface runs through several tools, each with a specified
function. In a specific embodiment, the PVD Coater tools can be
configured to for physical vapor deposition of one or more
materials to form thin film layers for a battery device. Also, the
slitter may be configured to remove excess portions of deposited
layers, and the winder may be configured to coil the thin film
layers. The packaging tool can encapsulate the electrochemically
active materials in a sealed unit. One of ordinary skill in the art
would recognize many variations, modifications, and alternatives to
such a lay out, such as adding or removing chambers and adding or
removing functions for individual chambers.
[0026] FIG. 2 is a simplified diagram of modules of the code
included in the manufacturing plant design system according to an
embodiment of the present invention. The system comprises codes of
data acquisition and pre-processing module, tensor operation
module, financial modeling module, integer programming optimization
module and post-processing module. Of course, those skilled in the
art will recognize other variations, modifications, and
alternatives for modules of code to be incorporated into the
manufacturing plant design system.
[0027] In an embodiment, the present invention provides a method
for forming a manufacturing facility. The method can include
providing a plurality of processing tools for arrangement within a
predetermined spatial region of one or more manufacturing
facilities. A plurality of variables can be assigned, respectively,
for the plurality of processing tools. These variables can be
provided in a tensor format. A target financial variable can be
defined to evaluate different manufacturing processing tool
configurations. The plurality of variables in the tensor
relationship can be processed to reduce a magnitude of the target
variable. Through the processing, an optimized set of the plurality
of processing tools and respective configuration with the plurality
of tools associated with the reduced magnitude of the target
variable can be determined. The optimized set of the plurality of
processing tools in the respective configuration can be used in the
one or more manufacturing facilities. Furthermore, the optimized
set of tools can be operated for the manufacture of a solid state
thin film battery device. Those skilled in the art will recognize
other variations, modifications, and alternatives.
[0028] In a specific embodiment, the plurality of processing tools
can include physical vapor deposition based thin film coaters,
chemical vapor depositions based thing film coaters, atomic layer
deposition thin film coaters, winders, slitters, packaging
machines, and the like. The packing machine can use techniques of
at least but not limited to dip coating and robotic arms for
attaching leads, wiring, moving, handling, and electronic control
component assembling. The physical vapor deposition based thin film
coaters can include at least one of the processing facilities,
which can include a vacuum chamber, an electron-beam evaporator, a
thermal evaporator, a pulsed laser deposition tool, a flash
evaporator, and an ion-beam assisted deposition tool and an
ion-beam sputtering tool. These tools can be implemented in a
plant, such as the one shown in FIG. 1. The tools mentioned herein
can be added to or removed from the sequence of tools configured in
the plant layout.
[0029] In a specific embodiment, the plurality of variables can
include the capital cost of the tool, throughput of the tool,
downtime of the tool, yield of the tool, efficiency of the tool,
material load and unload time of the tool, preparation time of the
tool, work in process for the tool and operational cost of the
tool, including labor and electricity cost. The target financial
variable can include at least the internal rate of return (IRR),
modified internal rate of return (MIRR), net present value (NPV),
and the weighted average cost of capital (WACC). In a specific
embodiment, the target financial variable can be calculated based
on inputs, which include expenditure, production rate, profit of
one single product unit, operation expenditure, and discount rate.
Also, the target financial variable is simplified as the ratio of
capital expenditure over production rate for a first-order
analysis. The total capital expenditure can be provided by a sum of
the capital expenditure of the plurality of processing tools
associated with processing facilities include inside the tools. The
production rate can be provided by a throughput rate of a
rate-limiting processing tool. Of course, there can be variations,
modifications, and alternatives.
[0030] In an embodiment, the manufacturing facility can be
configured with at least one of the designs including a
continuously moving web design and a carousel design. In the
continuously moving web design, a web continuously moves through
each processing tool during which period the materials are
deposited. The web is slit and wound and the cells are packaged. In
the carousel design, a drum stays in each processing tool for a
certain period until the processing task is finished and moves to
the next process tool. In the carousel design, the number of drums
is equal to the number of total processing tools and all the
processing tools are arranged along a circular line.
[0031] In a specific embodiment, the battery device can be a solid
state, hybrid thin film energy storage and conversion device. This
device can include at least a solar cell device/battery device, an
optical device/battery device, a capacitor device/battery device, a
fuel cell device/battery device, a first battery device/second
battery device, and a micro-combustion engine device/battery
device. Those skilled in the art will recognize other variations,
modifications, and alternatives.
[0032] In an embodiment, the present invention provides a system
for designing a manufacturing plant. This system can include a
computer readable memory device, one or more codes directed to a
plurality of variables, a tensor operation module, a financial
modeling module, an optimization module, and a post-processing
module. The computer readable memory device can include one or more
codes directed to a plurality of tool parameters corresponding
respectively to a plurality of processing tools for arrangement
within a predetermined spatial region of one or more manufacturing
facilities. The one or more codes directed to a plurality of
variables, respectively, can be for the plurality of processing
tools, whereupon the plurality of variables are arranged in a
tensor format, with the one or more codes directed to a processing
tool configuration tensor. The tensor operation module can be
configured to process the plurality of variables and the
configuration tensor to obtain the production rate, capital
expenditure, and operation expenditure. The financial modeling
module can be used to reduce a magnitude of a target financial
variable associated with a set of the plurality of variables and
the configuration tensor. The target financial variable can include
at least the internal rate of return (IRR), modified internal rate
of return (MIRR), the net present value (NPV), and the weighted
average cost of capital (WACC). The optimization module can be
configured to output an optimized configuration tensor associated
with the optimal target financial variable value. The
post-processing module can be configured to convert the optimal
configuration tensor to output the optimized set of tools and
associated configuration of the set of tools. Those skilled in the
art will recognize other variations, modifications, and
alternatives.
[0033] In a specific embodiment, the processing tool configuration
tensor is an n-order tensor with n dimensions to index a plurality
of specifications including at least the processing step, allocated
locations for tools inside the processing step, processing tool
type, and the type of facility used inside a processing tool. The
processing tool configuration tensor in also include elements which
have binary values of zero and one. An element has the value of one
if and only if the specified allocated location for the specified
processing step is occupied by the specified processing tool
including the specified processing facility. Otherwise, the tensor
element has the value of zero.
[0034] In a specific embodiment, the tensor operation modules
comprises adding two tensors, multiplying two tensors, transposing
first-order and second-order tensors, contracting a tensor and
finding the maximum or minimum element of a tensor or a subset of
the tensor along with specified dimensions. In a specific
embodiment, the optimization module includes one or more codes
directed to an integer programming optimization process applying
enumerative techniques, branch-and-bound techniques, or cutting
planes techniques.
[0035] In a specific embodiment, the post-processing module
includes importing the optimal configuration tensor, identifying
the non-zero elements which have exactly values of one and
outputting the optimal configuration information with
specifications of which type of and how many processing tools are
used for each processing step associated with which type and how
many processing facilities are used inside each processing
tool.
[0036] In a specific embodiment, the enumerative optimization
procedure comprises a parallelized implementation of the
enumeration of the feasible possibilities to speed up the
computation process on a shared memory and multi-processing unit
computing system. Of course, those skilled in the art will
recognize other variations, modifications, and alternatives.
[0037] FIG. 3 is a simplified comparison of an example plant design
configuration against the optimized design configuration. In this
example, there are five processing steps (i=1, 2, 3, 4, 5). There
are four different types of processing tools to choose from (k=1,
2, 3, 4). These four processing tools are represented by A, B, C,
D. Each of the processing tool has its own deposition rate for a
given processing step and the cost is also different for different
type of tools. It is also assumed that maximum of four locations
are allocated for each processing step (j=1, 2, 3, 4). An example
design is given in 301 in FIG. 3. In this example design, one tool
B is assigned to processing step 1; four tools of D are assigned to
processing step 2; three tools of D are assigned to processing step
3; two tools of D are assigned to processing step 4; one tool of B
is assigned to processing step 5. The obtained internal rate of
return from the financial modeling module is 0.112. The
corresponding production rate is 0.7599 million units per year, and
the corresponding capital expenditure is 54 million dollars. This
example design is chosen arbitrarily without conducting
optimization. If the internal rate of return is used as an
objective function to be maximized, one can conduct an optimization
process to identify the optimal configuration as shown in 302 in
FIG. 3. This optimal configuration assigns one tool of A for step
1, three tools of D for step 2, two tools of D for step of 3, one
tool of D for step 4 and one tool of B for step 5. This optimal
configuration yields an IRR of 0.139. The corresponding production
rate is 0.6079 million units per year and the capital expenditure
is 37.5 million dollars. The optimization technique used is
enumeration to go through all the possible combinations for the
configuration tensor. The computational time of the enumeration
based optimization for this case was reduced from 10.2 minutes to
1.38 minutes when a parallel computing was implemented to increase
the utilized process units from one to eight.
[0038] FIG. 4 is a simplified illustration of the set up of
configuration tensor according to an embodiment of the present
invention. In this case, the configuration tensor is a third-order
tensor. There are five processing steps to deposit current
collector, cathode, electrolyte, anode and barrier respectively.
These five process steps are specified by the index of i in the
tensor T.sub.kij.
[0039] Four different types of processing tools A, B, C and D are
used. Processing tool is specified by the index of k in the tensor
T.sub.kij. Assuming that maximum of 4 positions are assigned to
each processing step for the processing tools. The position is
specified by index j in the tensor T.sub.kij. If three type D
processing tools are used for step number 3 (electrolyte
deposition), the configuration tensor T has three non-zero
elements, T.sub.431, T.sub.432 and T.sub.433 associated with step
number 3 (i=3). The corresponding elements of T.sub.131, T.sub.231,
T.sub.331, T.sub.132, T.sub.232, T.sub.332, T.sub.133, T.sub.233,
T.sub.333, T.sub.134, T.sub.234, T.sub.334, T.sub.434 associated
with step number 3 (i=3) are all zero. To further illustrate how
the configuration tensor is set up, consider position 2 (j=2) of
processing step 3 for the electrolyte deposition. This position is
occupied with tool type D (k=4). Therefore, the tensor element of
T.sub.432=1. Position 4 of processing step 3 is not occupied by any
tool, so T.sub.k34=0 (where k=1, 2, 3, 4).
[0040] FIG. 5 is a simplified illustration of the set up of a
fourth-order configuration tensor according to an embodiment of the
present invention. In this example, there are three processing
steps, i=1, 2, and 3. In each processing step, there are three
pre-allocated positions, j=1, 2 and 3. There are three type of
process tools with k=1 being a thin film coater, k=2 being a winder
and k=3 being a slitter. There are four types of facility tools,
1=1, 2, 3, and 4. If facility type does not apply to a specific
processing tool, it is indicated by the element of 1=0. As
illustrated in FIG. 5, position 2 of processing step 2 is occupied
by a thin film coater with thermal evaporation and thickness
sensor, which dictates that T.sub.2214=1 and T.sub.2212=1. As also
illustrated in FIG. 5, position 1 of processing step 3 is occupied
by a winder, which dictates that T.sub.3120=1. As further
illustrated in FIG. 5, position 3 in processing step 1 is not
occupied by any tool, which dictates that T.sub.13k1=0 (where k=1,
2, 3 and 1=1, 2, 3, 4). In the set-up process of the configuration
tensor, all the elements are assigned to be zero initially. A
respective element T.sub.ijk1 is changed to the value of one when a
certain tool type (index k) with certain facility type (index 1) is
assigned to a certain position (index j) for a certain processing
step (index i).
[0041] FIG. 6 is a simplified illustration of a serially configured
continuously moving web design according to an embodiment of the
present invention. As shown in FIG. 6, a moving web configured with
two or more rotating units or rollers, which control the web's
movement, can be used as a platform for forming electrochemically
active materials. The separate materials overlying the moving web
can represent a battery device in various stages of processing as
described previously wherein each step "i" includes one or more
positions "j". Those skilled in the art will recognize other
variations, modifications, and alternatives.
[0042] FIG. 7 is a simplified illustration of a carousel design
configuration. In the carousel design, a drum stays in each
processing tool for a certain period until the processing task is
finished and moves to the next process tool. In this design, the
number of drums is equal to the number of total processing tools
and all the processing tools are arranged along a circular line.
There can be other variations, modifications, and alternatives.
[0043] FIG. 8 is a simplified illustration of a carousel design and
its optimal configuration that yields the best internal rate of
return. In this example, there are 8 processing steps which
includes the deposition of anode current collector, a first layer
of anode, a first layer of electrolyte, a first layer of cathode,
cathode current collector, a second layer of cathode, a second
layer of electrolyte and a second layer of anode. For the optimal
configuration, each of the electrolyte layers is finished in two
deposition zones with each zone depositing exactly half of the
desired electrolyte layer thickness; each of the cathode layers is
finished in five deposition zones with each zone depositing exactly
one fifth of the desired cathode layer thickness. The optimized
configuration yields a production rate of 0.458 million batteries
per year with a initial capital expenditure of 19.1 million
dollars. The optimized internal rate of return is 0.201 and the
capital expenditure divided by the production rate is 0.0240. The
tensor format discussed in the figure descriptions above is further
explained below.
[0044] The configuration tensor T is set up with binary values of
zero and one. Take a third-order tensor for example, a respective
element T.sub.ijk is one when a certain tool type (index k) is
assigned to a certain position (index j) for a certain processing
step (index i).
T ijk = { 1 when position j at step i is occupied by tool type k 0
otherwise ##EQU00001##
[0045] The advantage of this setup of configuration tensor is that
the parameters such as capital expenditure and throughput rate can
be easily obtained using tensor multiplication. For example, the
capital expenditure X.sub.ij.sup.c of the processing tool located
at position j at processing step i is obtained by:
X.sub.ij.sup.c=(x.sub.c).sub.kT.sub.ijk=x.sub.c.sup.TT(:,i,j)
where x.sub.c is a K by 1 vector defining the capital expenditure
of K types of processing tools and (x.sub.c).sub.k T.sub.ijk
defines a the multiplication along the dimension indexed by k.
Similarly, the throughput rate R.sub.ij at position j at processing
step i is obtained by:
R.sub.ij=(r).sub.ikT.sub.ijk=r(i,:)T(:,i,j)
where (r).sub.ik is a I by K matrix (2.sup.nd order tensor) and
(r).sub.ikT.sub.ijk defines a multiplication along the dimension
indexed by k.
[0046] To calculate the throughput of thin film deposition
processing tools (thin film coaters), first consider the time
required to deposit the component layer required for a whole
battery .tau.,
.tau. = LW .delta. rA 1 zm ##EQU00002##
where L is the length of the battery component layer, W is the
width of battery component layer, r is the rate, in angstrom per
second, for the component layer material to be deposited by the
specified processing tool with the specified processing facility, A
is the effective deposition area of the processing tool, and z is
the number of deposition zones inside one coater, .delta. is the
thickness of the battery component layer and m the number of
processing tools used for the battery component layer. The
throughput of the coater for this specific battery component layer
is then:
R = N .tau. = NA LW rzm .delta. ##EQU00003##
where N is the machine running time in a year.
[0047] The total expenditure of the all the processing tools used
is calculated by:
X total c = j = 1 J i = 1 I X ij c ##EQU00004##
The production rate of the whole line, in number of units made per
year, is determined by the rate-limiting step:
R total = min 1 .ltoreq. i .ltoreq. I { j = 1 J R ij }
##EQU00005##
The described configuration tensor is expandable to include a
fourth dimension to index the facility type.
T ijkl = { 1 when position j at step i is occupied by tool type k
with processing facility type 1 0 otherwise ##EQU00006##
The corresponding calculations for expenditure and rate are:
R ij = ( R ) i kl _ T ij kl _ = k l [ R ( : , i ) T ( : , i , j ) ]
kl ##EQU00007## X ij c = ( x c ) kl _ T ij kl _ = k l x c T ( : . i
. j ) ##EQU00007.2##
where R.sub.ikl.epsilon..quadrature..sup.I.times.K.times.L is the
production rate when processing tool k with facility 1 is used for
step I and (x.sub.c).sub.kl.epsilon..quadrature..sup.K.times.L is
tool capital expenditure for processing tool type k equipped with
processing facility 1.
[0048] To evaluate different manufacturing processing tool
configurations, at least one target financial variables are used.
The target financial variable comprises at least internal rate of
return (IRR), modified internal rate of return (MIRR), net present
value (NPV) and weighted average cost of capital (WACC). The net
present value (NPV) is calculated by:
NPV = - X total c + y = 1 n 1 ( 1 + r dis ) y [ p R total - X total
o ] ##EQU00008##
where r.sub.dis is discount rate, p is the profit for one unit of
the product, X.sub.total.sup.0 is the total operational cost per
year and n is the duration of the project in years. The internal
rate of return (IRR) is obtained by finding the exact discount rate
r.sub.dis which satisfies that the net present value (NPV) is
zero,
- X total c + y = 1 n 1 ( 1 + r dis ) y [ p R total - X total o ] =
0 ##EQU00009##
[0049] Due to the intrinsic drawbacks of the internal rate of
return, two other financial variables, modified internal rate of
return (MIRR) and weighted average cost of capital (WACC), are also
used to evaluate processing tool configurations and the
manufacturing facility design. Modified internal rate of return
(MIRR) is obtained by:
MIRR = ( FVCF IO ) 1 n - 1 ##EQU00010##
where FVCF is the total future value of the cash flows, IO is the
cost of investment, and n is the duration of the project in years.
The total future value of the cash flows is obtained by summing the
future values of the individual cash flows (CF).
FVCF = i = 1 n CF ( 1 + r ) n - i ##EQU00011##
The cost of investment is obtained by summing the present values of
the individual investment.
[0050] While the above is a full description of the specific
embodiments, various modifications, alternative constructions and
equivalents may be used. Therefore, the above description and
illustrations should not be taken as limiting the scope of the
present invention which is defined by the appended claims.
* * * * *