UNITED STATES PATENT AND TRADEMARK OFFICE
`
`______________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`______________
`
`
`
`Ford Motor Company
`Petitioner,
`
`v.
`
`Versata Software, Inc.
`Patent Owner.
`
`______________
`
`
`
`U.S. Patent No. 7,739,080
`
`CBM Case No.: 2016-00101
`
`______________
`
`
`
`DECLARATION OF DEBORAH L. McGUINNESS, Ph.D.
`
`Page 1 of 36
`
`
`
` FORD 1006
`
`

`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`TABLE OF CONTENTS
`
`
`
`
`
`List of Exhibits ........................................................................................................... 3
`
`I.
`
`II.
`
`Introduction ...................................................................................................... 4
`
`Qualifications and Professional Experience .................................................... 5
`
`III. Relevant Legal Standards ................................................................................ 9
`
`IV. While the disclosure of a patent specification is determined from the
`perspective of a person having ordinary skill in the art, the disclosure
`for purposes of analyzing a means-plus-function claim cannot be
`supplemented through expert opinion. For example, undisclosed
`subject matter that an expert might consider “obvious” or “known to
`those of skill in the art” at the time of the invention is not a part of the
`written description unless that subject matter is disclosed in the
`specification. Qualifications of one of ordinary skill in the art .....................11
`
`V.
`
`Challenged claims of the ‘080 Patent and proposed claim
`constructions ..................................................................................................12
`
`VI. The ‘080 patent claims cover what humans can do .......................................12
`
`A.
`B.
`
`Independent claims 1, 3, 4, and 22 ......................................................16
`The dependent claims ..........................................................................24
`
`VII. Claims 2, 6, and 16 of the ‘080 patent do not covey their scope to a
`skilled artisan with reasonable certainty ........................................................29
`
`VIII. Claim 22 of the ‘080 Patent is indefinite because the claim recites a
`general purpose computer and the ‘080 patent does not disclose an
`algorithm ........................................................................................................34
`
`IX. Conclusion .....................................................................................................35
`
`
`
`
`
`Page 2 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`List of Exhibits
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`Description
`
`1004
`
`
`Exhibit
`No.
`1001 U.S. Patent No. 7,739,080
`1002 Versata Complaint in the Versata lawsuit
`1003 Versata Counterclaim in the Ford lawsuit
`A Guide to the Legislative History of the America
`Invents Act; Part II of II, 21 Fed. Cir. Bar J. No. 4
`(2002), pp. 539-653
`1005 U.S. Patent No. 7,200,582
`
`1006 Declaration of Deborah L. McGuinness
`
`1010
`
`1011
`
`1012
`
`1013
`
`1014
`
`Identifier
`
`‘080 patent
`
`
`
`AIA Legislative
`History Guide
`
`McDermott
`
`
`
`
`
`
`
`
`
`‘582 patent
`McGuinness
`Decl.
`‘080 file history
`File history of the ‘080 patent
`1007
`
`1008 McGuinness Curriculum Vitae
`1009
`Stefik, Introduction to Knowledge Systems (1995) Stefik
`McDermott, R1: an Expert in the Computer
`Systems Domain, Proceedings AAAI-80 (1980)
`McGuinness et al., An Industrial-Strength
`Description Logic-Based Configurator Platform,
`IEEE Intelligent Systems (1998)
`McGuinness et al., Description Logic in Practice:
`A CLASSIC: Application, Proceedings of the 14th
`International Joint Conference on Artificial
`Intelligence, Montreal, Canada, (August 1995)
`Versata’s identification of “means” structure for
`claim 22 of the ‘080 patent from the Ford lawsuit
`Versata’s Opening Claim Construction Brief in
`the Ford lawsuit
`
`
`
`Page 3 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`I, Deborah L. McGuinness, Ph.D., declare as follows:
`
`I.
`
`Introduction
`
`1.
`
`I am making this declaration at the request of Ford Motor Company in
`
`a Covered Business Method Review proceeding concerning U.S. Patent No.
`
`7,739,080 (“the ‘080 Patent”).
`
`2.
`
`I am being compensated for my work in this matter at my standard
`
`consulting rate of $500 per hour and, when working while traveling, $600. My
`
`compensation does not depend on the outcome of this proceeding.
`
`3.
`
`I have been asked to provide my opinions related to the patentability
`
`of claims 1-22 of the ‘080 patent.
`
`4.
`
`In preparation of this declaration, I have studied Exhibits 1001, 1005,
`
`and 1007-1014 as listed in the Exhibit List shown above in my report.
`
`5.
`
`In forming the opinions expressed below, I have considered:
`
`(a) The patents and file histories identified in the List of Exhibits;
`
`(b) The relevant legal standards as explained to me by Ford’s
`
`counsel, including the standard for patentability under 35 United States Code
`
`§§ 101 and 112, ¶ 2; and
`
`(c) My knowledge and experience based upon my work and study
`
`as described below, considering the patentability of the ‘080 patent from the
`
`Page 4 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`viewpoint of a person having ordinary skill in the relevant art as of the
`
`priority date of the ‘080 patent, which I am told is April 19, 2004.
`
`II. Qualifications and Professional Experience
`
`6.
`
`I have provided my full background in the curriculum vitae that is
`
`attached as Ex. 1008, which more fully details my 30-plus years of experience in
`
`computer science and electrical engineering. I am also an inventor on five patents,
`
`four of which directly relate to product configuration: U.S. Patent Nos. 5,720,008,
`
`5,974,405, 6,256,627, 6,385,600, and 6,457,002.
`
`7. My academic training includes completing the requirements for a
`
`Bachelor of Science in Computer Science and a Bachelor of Arts in Mathematics
`
`from Duke University in 1980. I completed a Master of Science degree from the
`
`Electrical Engineering and Computer Science Department of the University of
`
`California at Berkeley in 1981. I also completed a Ph.D. in Computer Science
`
`from Rutgers University in 1996.
`
`8.
`
`I began my professional career immediately after my Bachelor’s
`
`degree and began work for AT&T Bell Laboratories in 1980. I was immediately
`
`accepted into the Bell Laboratories “One Year on Campus” program which
`
`supported me to be a full time Master’s student at Berkeley. Upon completion of
`
`my M.S. in 1981, I returned to Bell Laboratories and began work at the Home of
`
`the Future at the Home Information Systems Laboratory. In 1984, I transferred to
`
`Page 5 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`the Computing Environments and Artificial Intelligence Department in New
`
`Jersey. While there, I was accepted into the Bell Laboratories Ph.D. program,
`
`which supported me while I pursued a Ph.D. I simultaneously was accepted into
`
`the Computer Science Ph.D. program at Rutgers. In 1985, I became the first
`
`employee in the Artificial Intelligence Research department of Bell Laboratories. It
`
`was during this time period that I first began to work on a type of artificial
`
`intelligence (AI) system called description logic-based systems. I did my
`
`dissertation in description logics and I spent approximately a decade heavily
`
`involved with description logic-based systems and their use to directly address
`
`large configuration problems. In 1989, I and some Bell Labs colleagues began
`
`publishing our work on description logics and in the early 90s, we began
`
`publishing our work on configuration problems. Our configuration systems have
`
`been used by AT&T and Lucent to configure over $6 billion worth of AT&T and
`
`Lucent products. I also continued to address configuration-style applications in
`
`after leaving AT&T, and for example, used the same style application to
`
`“configure” wine and food pairings and I have published papers on those
`
`applications into the 2000s and beyond.
`
`9.
`
`I have been involved in a number of academic configuration activities.
`
`I gave a keynote address at what has been cited as the first in a series of
`
`configuration workshops –
`
`the 1996 American Association for Artificial
`
`Page 6 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`Intelligence-sponsored workshop on configuration. I also provided the invited
`
`plenary talk on the entire meeting to the full artificial intelligence conference
`
`community. I later co-organized two international configuration workshops. I was
`
`a guest editor for a special journal issue on configuration in the Artificial
`
`Intelligence for Engineering Design, Analysis and Manufacturing Journal series. I
`
`authored the chapter on Description Logic for Configuration in the Handbook of
`
`Description Logics. I also have over 350 peer reviewed published papers,
`
`including a number on platforms for configuration, conceptual models for
`
`configuration, and configuration applications, including but not limited to:
`
`• Deborah L. McGuinness and Jon Wright. “An Industrial Strength
`
`Description Logic-based Configurator Platform'.” IEEE Intelligent
`
`Systems, Vol. 13, No. 4, July/August 1998, pp. 69-77. (Ex. 1011.)1
`
`• Deborah L. McGuinness and Jon Wright. “Conceptual Modeling for
`
`Configuration: A Description Logic-based Approach” in the Artificial
`
`
` Ex. 1011 is a true and accurate copy, with exhibit and page numbers added, of:
`
` 1
`
`Deborah L. McGuinness and Jon Wright. “An Industrial Strength Description
`
`Logic-based Configurator Platform.” IEEE Intelligent Systems, Vol. 13, No. 4,
`
`July/August 1998, pp. 69-77.
`
`Page 7 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`Intelligence for Engineering Design, Analysis, and Manufacturing
`
`Journal (AIEDAM) - special issue on Configuration, AI EDAM 12(4):
`
`333-344 (1998).
`
`• Deborah L. McGuinness, Peter F. Patel-Schneider, Lori Alperin
`
`Resnick, Charles Isbell, Matt Parker, and Chris Welty. “A Description
`
`Logic Based Configurator for the Web.” SIGART Bulletin, 9(2) pp
`
`20-22. Fall, 1998.
`
`• Deborah L. McGuinness, Lori Alperin Resnick, and Charles Isbell.
`
`“Description Logic in Practice: A CLASSIC: Application.” in
`
`Proceedings of the 14th International Joint Conference on Artificial
`
`Intelligence, Montreal, Canada, August, 1995. (Ex. 1012.)2
`
`10.
`
` While at Bell Labs and AT&T, I focused on frame-based
`
`representation foundations, explanation environments for knowledge systems, and
`
`
`
` Ex. 1012 is a true and accurate copy, with exhibit numbers added, of: Deborah L.
`
` 2
`
`McGuinness, Lori Alperin Resnick, and Charles Isbell. “Description Logic in
`
`Practice: A CLASSIC: Application” in Proceedings of the 14th International Joint
`
`Conference on Artificial Intelligence, Montreal, Canada, August, 1995.
`
`Page 8 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`application environments, including configuration application environments, for
`
`frame-based systems.
`
`11.
`
`In 1998, I left AT&T Labs research and moved to Stanford University
`
`where I started as Associate Director and Senior Research Scientist of the
`
`Knowledge Systems Laboratory, within the Computer Science Department. When
`
`I left the lab nine years later, I was acting director of the laboratory. While at
`
`Stanford, I focused on knowledge-based systems. The work included creating
`
`languages for representing information, designing frame representation and
`
`reasoning systems for deducing information, creating explanation environments,
`
`next generation web languages and environments, and building many AI-based
`
`applications, including some configuration applications.
`
`III. Relevant Legal Standards
`
`12.
`
`I have been asked to provide opinions that relate the patentability of
`
`the ‘080 Patent under 35 U.S.C. §§ 101 and 112.
`
`13.
`
`I understand that the Patent Statute requires that patent claims must be
`
`definite. 35 U.S.C. § 112, ¶ 2 (“The specification shall conclude with one or more
`
`claims particularly pointing out and distinctly claiming the subject matter which
`
`the applicant regards as his invention.”). I further understand that the U.S.
`
`Supreme Court recently said that patent claims are indefinite if they fail to inform,
`
`with reasonable certainty, those skilled in the art about the scope of the invention
`
`Page 9 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`when read in light of the patent specification and its history in the Patent and
`
`Trademark Office (the file history).
`
`14.
`
`I have been informed that 35 U.S.C. §112(6) states:
`
`“An element in a claim for a combination may be expressed as a
`
`means or step for performing a specified function without the recital
`
`of structure, material, or acts in support thereof, and such claim shall
`
`be construed to cover the corresponding structure, material, or acts
`
`described in the specification and equivalents thereof.”
`
`15.
`
`I understand that the corresponding structure, material, or acts
`
`described in the specification must be clearly linked to the claimed function, and
`
`that whether the specification discloses such corresponding structure, material or
`
`acts is to be determined from the perspective of a person having ordinary skill in
`
`the art at the time of the alleged invention.
`
`16.
`
`It is my understanding that in most cases when a computer-
`
`implemented means-plus-function claim is involved, special programming is
`
`required for a general-purpose computer to perform the corresponding claimed
`
`function, and that the patent must disclose the algorithm used to perform the
`
`claimed function.
`
`17. An algorithm is typically understood as a disclosed step-by-step
`
`procedure for accomplishing a given result; a full description of the steps to be
`
`executed. An algorithm is essentially how the specialized programming performs
`
`Page 10 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`the claimed function, and is not simply repeating or describing such claimed
`
`function.
`
`18. The specification can disclose the algorithm in any understandable
`
`terms including as a mathematical formula, in prose, or as a flow chart, or in any
`
`other manner that provides sufficient structure.
`
`19. To provide adequate structure, the patent must disclose the structure
`
`necessary for a person having ordinary skill in the field to provide an operative
`
`software program for the claimed function and reasonably apprise a person having
`
`ordinary skill in the field of the invention of the scope of the subject matter that is
`
`patented.
`
`IV. While the disclosure of a patent specification is determined from
`the perspective of a person having ordinary skill in the art, the
`disclosure for purposes of analyzing a means-plus-function claim
`cannot be supplemented through expert opinion. For example,
`undisclosed subject matter that an expert might consider
`“obvious” or “known to those of skill in the art” at the time of the
`invention is not a part of the written description unless that
`subject matter is disclosed in the specification. Qualifications of
`one of ordinary skill in the art
`
`20.
`
`I have reviewed the ‘080 Patent and its file history. The relevant field
`
`of art is product configuration software. Based on my review and my knowledge
`
`in the area of configuration software, it is my opinion that a person having ordinary
`
`skill in the art would have: (1) a bachelor’s degree in computer science, electrical
`
`engineering, computer engineering, or similar technical field, and some familiarity
`
`Page 11 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`with configuration systems, or (2) equivalent experience in the design or
`
`implementation of configuration systems. In my declaration, this person is
`
`sometimes referred to as “a skilled artisan” or “a person skilled in the art.”
`
`V. Challenged claims of the ‘080 Patent and proposed claim
`constructions
`
`21.
`
`I have been asked to review claims 1-22.
`
`VI. The ‘080 patent claims cover what humans can do
`
`22. By the mid-1990’s computer-based “knowledge” systems were well-
`
`known, published, and in use. (Ex. 1009, Stefik at 180-207 for numerous
`
`examples; Ex. 1010, McDermott at 1-2.3) Numerous knowledge-based systems
`
`were in commercial use as well in this time period and companies also were in
`
`existence, such as Teknowledge and Intellicorp, that sold expert system building
`
`tools and provided consulting services to build expert systems. It was also
`
`understood that “knowledge systems” were sometimes also called “expert” system
`
`
`
` For Ex. 1009, page number “180” refers to “Page 180 of 224” in the bottom left
`
` 3
`
`corner of the page. For Ex. 1010, page number “1” refers to “Page 1 of 3” in the
`
`bottom left corner of the page.
`
`Page 12 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`because a computer program would be updated with the knowledge of an expert in
`
`a given field.
`
`Ex. 1009, Stefik at 160
`
`
`
`23.
`
` “Configuration” systems were also well-known by the 1990’s as
`
`being a specialized type of knowledge-based system. (Ex. 1009, Stefik at 163-165;
`
`Ex. 1010, McDermott at 1-2.) Configuration systems likewise would take an
`
`expert’s knowledge and employ it in a computer program that could be used by the
`
`companies buying or selling products that need to be configured or directly used by
`
`the public.
`
`24. Configuration systems are typically used by companies such that a
`
`person is able to “configure” a product that can actually be assembled and built.
`
`For instance, one of the oldest and well published configuration systems was
`
`published in 1980 along with many later publications and was used by Digital
`
`Equipment Corporation to configure their VAX computer systems – initially
`
`configuring the VAX-11/780 systems. (Ex. 1010, McDermott at 1.) This was
`
`aimed at technicians configuring the computer. The 1980 paper about the R1
`
`system says “R1 has proven itself to be a highly competent configurer of VAX-
`
`Page 13 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`11/780 systems. The configurations that it produces are consistently adequate, and
`
`the information that it makes available to the technicians who physically assemble
`
`the systems is far more detailed than that produced by the humans who do the
`
`task.” (Ex. 1010, McDermott at 3, Concluding Remarks.)
`
`25. Knowledge-based configuration has a long history that includes both
`
`consumer-facing as well as internal facing applications. The Wikipedia page on
`
`Knowledge-based configuration at https://en.wikipedia.org/wiki/Knowledge-
`
`based_configuration has a list of 27 references (as of July 24, 2016), many of
`
`which are published in the 80s and 90s, including one configurator family that I co-
`
`authored for AT&T. The paper referenced in the Wikipedia article was published
`
`in 1998 and the configurator family was used by AT&T and Lucent in the late 80s
`
`and 90s. (Ex. 1011, D. McGuinness and J. Wright, An Industrial Strength
`
`Description Logics-Based Configurator Platform, IEEE Intelligent Systems, vol.
`
`13, no. 4, pp. 69–77, 1998.) That paper presents background on how we at AT&T
`
`used knowledge based systems (built on a description logic system) to configure
`
`transmission equipment such as DACS cross-connect systems. The paper shows
`
`that companies such as AT&T and Lucent were doing configuration in the 90s
`
`using systems that included rule-based models along with attribute (called roles in
`
`the AT&T system) models. “Our DACS IV-2000 application has a knowledge
`
`base that includes a concept taxonomy and instance descriptions. … Concepts are
`
`Page 14 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`structured descriptions and can have many encoded restrictions…” The paper goes
`
`on to describe the concepts in terms of roles (analogous to attributes in the patent)
`
`and those roles may have number restrictions restricting the number of role fillers
`
`and a value restriction – restricting the type of role fillers. (Ex. 1011, p. 3). We
`
`also published other papers showing how to do configuration using the same style
`
`of combining rules and an attribute or object model in other domains – such as
`
`building a home theater system. (Ex. 1012, Deborah L. McGuinness, Lori Alperin
`
`Resnick, and Charles Isbell. Description Logic in Practice: A CLASSIC:
`
`Application in Proceedings of the 14th International Joint Conference on Artificial
`
`Intelligence, Montreal, Canada, August, 1995.) That paper describes our home
`
`theater configuration example and states (Ex. 1012, p. 1) that the system can
`
`“encode rich class and object descriptions” and “provide active inference (such as
`
`automatic classification of classes and objects into a generalization hierarchy, rule
`
`firing and maintenance, inheritance, propagation, etc.).” The use of the AT&T
`
`Description Logic platform for configuring transmission equipment and for
`
`configuring home theater systems provides additional evidence that people were
`
`building configuration systems that utilized combined rule and attribute models.
`
`26. The claims of the ’080 patent simply add conventional computer
`
`components to well-known configuration practices. Specifically, the ‘080 patent
`
`attempts to automate the consolidation of product configuration models.
`
`Page 15 of 36
`
`
`
` FORD 1006
`
`

`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`27. The ‘080 patent admits that consolidating product configuration
`
`
`
`models was old, and that the “new” automation process described in the ‘080
`
`patent may work, or may have remaining challenges. (See, Ex. 1001, ‘080 patent,
`
`“prior art” Figures 1-6 and accompanying text, 4:1-7, 7:14-16.) For example, the
`
`process may suggest configurations that are not buildable, i.e., “not defined in any
`
`of the source models.” (Ex. 1001, ‘080 patent at 4:1-7.) Further conflicts may be
`
`determined that require a human to resolve. (Id. at 7:14-16.)
`
`A.
`
`Independent claims 1, 3, 4, and 22
`
`28. Claim 1 is representative of the independent claims of the ‘080 patent:
`
`1. A method of using a computer system to consolidate multiple
`
`configuration models of a product, the method comprising:
`
`performing with the computer system:
`
`[1] identifying a conflict between at least two of the configuration
`
`models, wherein the configuration models are organized in
`
`accordance with respective directed acyclic graphs, each
`
`configuration model includes at least one ancestor configuration
`
`model family space and a child configuration model family
`
`space below the ancestor configuration model family space, a
`
`first of the conflicting configuration models comprises an
`
`ancestor configuration model family space that is different than
`
`an ancestor configuration model family space of a second of the
`
`conflicting configuration model, and each child configuration
`
`model family space constrains the ancestor configuration model
`
`Page 16 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`family space above the child in accordance with configuration
`
`rules of the configuration model to which the child belongs;
`
`[2] extending at least one of the ancestor configuration model
`
`family spaces of the conflicting configuration models so that the
`
`ancestor configuration model family spaces of the first and
`
`second conflicting configuration models represent the same
`
`ancestor configuration model family space;
`
`[3] removing from the child configuration model family space any
`
`configuration space extended in the ancestor of the child
`
`configuration family space; and
`
`[4] combining the first and second configuration models into a
`
`single, consolidated model that maintains a non-cyclic chain of
`
`dependencies among families and features of families for use in
`
`answering configuration questions related to the product.
`
`
`29. The claim recites the idea of consolidating two product configuration
`
`models using a computer by [1] identifying a conflict between configuration
`
`models, [2] extending the configuration space in the “parent family,” [3] removing
`
`the same configuration space in the “child family,” and [4] combining the models.
`
`30. All steps of the independent claims can be done by a human using pen
`
`and paper. Using Figure 8, the patent explains that steps [1], [2], and [3] can be
`
`drawn graphically. Figure 8 is reproduced below with annotations added showing
`
`claim steps [1] and [2]:
`
`Page 17 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`Ex. 1001, ‘080 patent, Figure 8
`
`
`
`31. Figure 8 shows two Configuration Models (602 and 612) for an
`
`automobile. The first three columns represent three families: “MKT,” “ENG,” and
`
`“SER,” respectively. As diagrammed, the MKT family is the parent of the ENG
`
`family, which is the parent of the SER family.
`
`32. The ‘080 patent says that shaded portions indicate buildable
`
`configurations (6:17-18) and the also patent uses the terminology of “release” and
`
`states that the shaded box of MKT1.ENG2 is released in Model 602 and not in
`
`Model 612 where there is an empty box. (Ex. 1001, ‘080 patent at 9:9-10.) As can
`
`Page 18 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`see seen by a visual review of the two Configuration Models in Figure 8, the
`
`shading/release status for “MKT1.ENG2” in the ENG Family of Configuration
`
`Model 602 differs from the shading/release status for “MKT1.ENG2” in the ENG
`
`Family of Configuration Model 612. (Id.) Thus a conflict exists between the two
`
`models (Ex. 1001, ‘080 patent at 9:9-10: “There is a conflict between the two
`
`models on ENG: MKT1.ENG2 is released in Model 602 but not in Model 612.”)
`
`The models cannot be combined without some adjustment to one of the models.
`
`(Id. at 9-24.)
`
`33. As the drawing of Figure 8 states, the conflict can be resolved “by
`
`adding space [MKT1:ENG2 (832)] to the ENG family and removing space
`
`[MKT1:ENG2:SER2 (834)] from [the] SER [family]” to create an “adjusted”
`
`Configuration Model 822. (Ex. 1001, ‘080 patent, Figure 8.) The patent
`
`specification confirms this step: “extend the ENG family in Model 612 to be
`
`compatible with the release of the ENG family in Model 602.” (Ex. 1001, ‘080
`
`patent at 9:14-16.) Also, the patent continues to discuss the adjustment: “the result
`
`is that the restriction on the SER family interacts with the extension of the ENG
`
`family in a way that the consolidated model 822 does not include unspecified
`
`buildable configurations . . . .” (Id. at 9:20-23.) Figure 8 shows that a human can
`
`draw the configuration models and perform claim step [2] using pen and paper.
`
`Page 19 of 36
`
`
`
` FORD 1006
`
`

`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`34. Step [3] (removing space from the child family space) is also drawn in
`
`
`
`Figure 8 as shown below (annotations added):
`
`Ex. 1001, Figure 8
`
`
`
`35. This step [3] removes from the SER (“child”) Family the space added
`
`to
`
`the ENG (“ancestor”) Family
`
`in step [2].
`
` The release status of
`
`MKT1.ENG2.SER2 changes from released to unreleased. As the ‘080 patent
`
`explains, “Referring to block 834, the extension is compensated for by restricting
`
`the SER family so that it is no longer released in the space we extended the ENG
`
`family (MKT1.ENG2.*).” (Ex. 1001, ‘080 patent at 9:16-19.) As illustrated in
`
`Page 20 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`Figure 8, a human can show this change using pen and paper by changing the
`
`shading of MKT1.ENG2.SER2 from shaded in Configuration Model 612 to
`
`unshaded in Adjusted Configuration Model 612. Extending space in the ENG
`
`family and removing the extended space from the SER family leaves the
`
`“Complete Model” 830 unchanged, as Figure 8, above, shows. Thus, the drawing
`
`of Figure 8 shows how a person with pen and paper could perform steps [2] and [3]
`
`by extending space in the ENG Family and then removing that extended space
`
`from the SER Family to create an Adjusted Configuration Model 822.
`
`36. Likewise, step [4] of the claims – combining the first model (602) and
`
`the adjusted second model (822) – can be done by a human using pen and paper.
`
`Figure 9A, reproduced below, is a drawing that shows the “combining” process
`
`(blue and orange highlighting added):
`
`Page 21 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`Ex. 1001, ‘080 patent, Figure 9A
`
`
`
`37. As shown in Figure 9A and described at 9:37-47, Configuration
`
`Model 602 and Configuration Model 612 (Adjusted) (reference numeral 822) are
`
`combined by first performing a logical “union” (highlighted in blue on Figure 9A)
`
`between each family in the two Configuration Models 602 and 822 (reading the
`
`drawing from top to bottom). “Blocks 924, 926, and 928 respectively represent the
`
`union of the MKT families, ENG families, and SER families from configuration
`
`models 602 and 612.” (Ex. 1001, ‘080 patent at 9:39-41.) The logical union
`
`Page 22 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`operation merges the release status in each family of the two Configuration Models
`
`such that, if an item is released in either family, the item is recorded as released in
`
`corresponding family (924, 926, 928) in the bottom row of Figure 9A. A person
`
`with a pen and paper can draw this union operation, as Figure 9A confirms.
`
`38. Next, a Consolidated Model (930) is created by intersecting
`
`(highlighted in orange in Figure 9A, above) the combined families 924, 926, and
`
`928. The intersection operation merges the release status of items in the three
`
`families (from left to right in Figure 9A) by recording an item as released in the
`
`Consolidated Model 930 only if it is released in every family. The result is the
`
`Consolidated Model 930 shown at the bottom right of the drawing: “Consolidated
`
`model 930 represents the accurate consolidation of models 602 and 612 having
`
`only specified configuration buildables.” (Ex. 1001, ‘080 patent at 9:41-43.) At
`
`this point, the Consolidated Model 930 can be used to answer configuration
`
`question about the product. Again, a person with a pen and paper can draw this
`
`intersect operation and create Consolidated Model 930, as Figure 9A confirms.
`
`39. The “combining” step [4] of the claims also states that the
`
`consolidated model “maintains a non-cyclic chain of dependencies among families
`
`and features of families.” The ‘080 patent shows this prior art concept
`
`diagrammatically in Figures 3 and 4, reproduced below:
`
`Page 23 of 36
`
`
`
` FORD 1006
`
`

`
`Atty. Dkt. No.: FPGP0131CBMR1
`
`Case No.: CBM2016-00101
`Patent No.: 7,739,080
`
`
`
`Ex. 1001, ‘080 patent, Figure 3 Ex. 1001, ‘080 patent, Figure 4
`
`40. Figure 3 shows a directed acyclic graph (“DAG”), which is “a non-
`
`
`
`cyclic chain of dependencies among families and features of families.” (Ex. 1001,
`
`‘080 patent at 8:26-27). In contrast, Figure 4 shows “a DAG with a cycle.” (Id. at
`
`7:53-55.) A human using pen and paper can maintain a non-cyclic chain of
`
`dependencies among families and features of families in the consolidated model.
`
`41. This same analysis applies to the other three independent claims,
`
`which are identical in substance to claim 1, merely adding trivial computer
`
`components that do not affect the analysis. T