International Business Machines Corporation et al.

Patent Trials and Appeals Board

Dec 30, 2020

2020002824 (P.T.A.B. Dec. 30, 2020)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
15/080,656 03/25/2016 Jeffrey S. Katz YOR920150227US2 6451
48915 7590 12/30/2020
CANTOR COLBURN LLP-IBM YORKTOWN
20 Church Street
22nd Floor
Hartford, CT 06103
EXAMINER
IQBAL, MUSTAFA
ART UNIT PAPER NUMBER
3683
NOTIFICATION DATE DELIVERY MODE
12/30/2020 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
usptopatentmail@cantorcolburn.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte JEFFREY S. KATZ, ALI KOC, GERARD LABUT,
RICHARD J. MUELLER, ASHISH SABHARWAL, and
AMITH SINGHEE
Appeal 2020-002824
Application 15/080,656
Technology Center 3600
Before EDWARD A. BROWN, BENJAMIN D. M. WOOD, and
MICHAEL J. FITZPATRICK, Administrative Patent Judges.
WOOD, Administrative Patent Judge.
DECISION ON APPEAL
STATEMENT OF THE CASE
Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from the
Examiner’s decision to reject claims 1, 5–9, 13–16, and 18–20. See Final
Act. 1. We have jurisdiction under 35 U.S.C. § 6(b).
We affirm.

1 “Appellant” refers to the applicant as defined in 37 C.F.R. § 1.42.
Appellant identifies the real parties in interest as International Business
Machines Corp. and DTE Electric Co. Appeal Br. 1.
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CLAIMED SUBJECT MATTER
The claims are directed to systems and methods for “resource
planning and management that include[] resizing and movement of resources
while considering business constraints and organizational structures.” Spec.
¶ 12. The systems and methods are particularly intended for “managers of
organizations that maintain distributed infrastructure and personnel”—e.g.,
an electric utility—having “service centers from which resources are
deployed for repair and maintenance of the infrastructure.” Id. Claim 1,
reproduced below, is illustrative of the claimed subject matter:
1. A computer-implemented method of performing
infrastructure management, the method comprising:
generating, using a processor, models of one or more work
shifts, one or more repair tasks, and one or more safety tasks
with each of the models including one or more variables,
wherein each work shift model includes a fixed duration and a
variable location, each repair task model includes a fixed
duration and a variable time interval, and each safety task
model includes a variable time interview2 and a variable
duration;
defining a constraint that affects at least one of the one of
[sic, or] more variables of at least one of the models;
generating a scenario based on the models and the
constraint; and
determining resource pre-positioning and task scheduling,
according to the scenario, by solving, using the processor, for
the one or more variables of each of the models of the scenario
in order to perform the infrastructure management, the solving
being based on achieving one or more objectives.

2 The Examiner objected to claim 1 because it incorrectly recites “variable
time interview” instead of “variable time interval.” Final Act. 5. Appellant
does not dispute that claim 1 should recite “interval” here instead of
“interview.”
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REFERENCES
Name Reference Date
Cocanougher US 2014/0278653 A1 Sep. 18, 2014
Brown US 2016/0171452 A1 Jun. 16, 2016
REJECTIONS
Claim(s) Rejected 35 U.S.C. § Reference(s)/Basis
1, 5–9, 13–16, 18–20 101 Eligibility
1, 5–9, 13–16, 18–203 103 Brown, Cocanougher
OPINION
Claims 1, 5–9, 13–16, and 18–20:
Rejected as Directed to Ineligible Subject Matter
Legal Principles
To determine whether a claim falls within a judicially recognized
exception to patent eligibility under 35 U.S.C. § 101, we apply the two-step
framework set forth in Mayo Collaborative Services v. Prometheus
Laboratories, Inc., 566 U.S. 66 (2012), and reaffirmed in Alice Corporation
Proprietary LTD. v. CLS Bank International, 573 U.S. 208 (2014). For the
first Alice step (Step 2A of the USPTO’s Patent Subject Matter Eligibility
guidance, MPEP § 2106), we determine whether the claims at issue are
directed to a patent-ineligible concept such as an abstract idea, law of nature,
or natural phenomenon. Alice, 573 U.S. at 217 (citing Mayo, 566 U.S. at
78–79). If so, we advance to the second Alice step (Step 2B of the USPTO’s
Patent Subject Matter Eligibility guidance) where “we consider the elements
of each claim both individually and ‘as an ordered combination’ to

3 Although the heading for this rejection lists only claims 1, 9, and 16, the
Examiner addresses all of the pending claims in the body of the rejection.
See Final Act. 9–21.
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determine whether the additional elements ‘transform the nature of the
claim’ into a patent-eligible application” of the otherwise patent-ineligible
concept. Id. (quoting Mayo, 566 U.S. at 78–79).
We also follow the USPTO’s additional guidance on applying Step
2A. See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed.
Reg. 50 (Jan. 7, 2019) (“Revised Guidance”).4 The Revised Guidance
establishes a “two-prong inquiry” for determining whether a claim is
directed to a judicial exception. Id. at 54. In prong one, we determine
whether the claim recites a judicial exception, such as a law of nature,
natural phenomenon, or abstract idea. Id. If so, we look to whether the
claim recites additional elements that integrate the judicial exception into a
practical application. Id. at 50. Thus, a claim is directed to a judicial
exception only if the claim recites a judicial exception and does not integrate
that exception into a practical application. Id.
If we determine that the judicial exception is not integrated into a
practical application, we proceed to Step 2B and determine whether the
claim adds a specific limitation beyond the judicial exception that is not
well-understood, routine, and conventional activity in the field, or,
alternatively, whether the claim simply appends well-understood, routine,
and conventional activities previously known to the industry, specified at a
high level of generality, to the judicial exception. Revised Guidance, 84
Fed. Reg. at 56.

4 Available at https://www.govinfo.gov/content/pkg/FR-2019-01-
07/pdf/2018-28282.pdf.
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Analysis
Appellant argues claims 1, 5–9, 13–16, and 18–20 as a group. Appeal
Br. 5–7. We select claim 1 as representative of the group, and decide the
appeal of this rejection on the basis of claim 1 alone. 37 C.F.R.
§ 41.37(c)(1)(iv).
Step 2A, Prong 1
We first consider whether claim 1 recites a judicial exception. The
Examiner finds that claim 1 is “directed to the abstract ideas of
storing/receiving data regarding work shifts, repair tasks, and safety tasks.”
Final Act. 6. Appellant asserts, however, that claim 1 “is directed to a
computer-implemented method of performing infrastructure management.”
Appeal Br. 6.
Claim 1 recites the step of “generating, using a processor, models of
one or more work shifts, one or more repair tasks, and one or more safety
tasks.” Appeal Br. 13 (Claims App.). While the Specification is not entirely
clear on this point, “generating . . . models” of one or more work shifts, one
or more repair tasks, and one or more safety tasks is another way of saying
“modeling” these items. See Spec. ¶ 13 (describing “modeling” work shifts,
repair tasks, and safety tasks). “Modeling,” in turn, appears to require the
exercise of judgment, or something that can be performed in a human mind,
in that it requires recognizing the specific circumstances confronting the
manager that is implementing the claimed method. For example, the
Specification describes modeling a work shift as “refer[ring] to the work
shift of a crew member” employed by an organization. Spec. ¶¶ 12–13.
According to the Specification,
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A shift is modeled as an unmovable interval but with an
associated movement variable. That is, a shift from 8 am to 5
pm has an interval (8 am to 5 pm) that may not be moved, but
the associated movement variable allows that shift to be
completed at different locations by the crew associated with
that work shift, as needed. Modeling the shift (at block 110)
may include considering different modes. For example, a crew
may be limited to working a single 8-hour shift during a regular
working day but may be permitted to work overtime up to 16
hours a day while in emergency mode.
Id. ¶ 13; see also id., Fig. 1. Thus, modeling the work shift requires
recognizing the interval assigned to work shifts in a particular organization;
“allowing” the shift to be worked at different locations “as needed”; and
“considering” different “modes” for the shift (e.g., “permit[ing]” overtime,
again, as needed “while in emergency mode”). Deciding when something is
“needed,” and then permitting crews to work overtime or in different
locations, are exercises of judgment, which managers make in the course of
managing work crews. As such, they constitute mental processes, which is
one of the three recognized groupings of abstract ideas. Revised Guidance,
84 Fed. Reg. at 52. Modeling repair tasks and safety tasks likewise amount
to acts of managerial judgment. See Spec. ¶ 13.
Claim 1 further recites “defining a constraint that affects at least one
[or] more variables of at least one of the models.” Appeal Br. 13 (Claims
App.). “[D]efining a constraint” may be as simple as entering information
that is “received through user inputs” or established as a matter of
organizational safety policy—e.g., “the condition that a public safety task
precedes certain repair tasks and must remain active until the start of the
repair task.” Id. at 14. It may also amount to exercising judgment regarding
“consideration of different crew types”—i.e., deciding whether a regular
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crew is “preferable from a cost or logistics standpoint”—or whether a
situation may require “contract crews or foreign crews.” Id. Deciding
whether something is “preferable” over something else is an exercise of
judgment. Thus, like the step of “generating . . . models,” “defining a
constraint” represents, at most, an exercise of judgment, which can be
performed in the human mind, and thus falls into the mental-process
grouping of abstract ideas.
Claim 1 additionally recites “generating a scenario based on the
models and the constraint.” Appeal Br. 13 (Claims App.). In light of the
description of “scenarios” in the Specification (see Spec. ¶¶ 14–17, Fig. 1),
as well as the fact that scenarios are “generat[ed] . . . based on the models
and the constraint,” which, as discussed above, result from exercises of
managerial and logistical judgment, we determine that the step of
“generating a scenario” likewise constitutes an exercise of judgment, and, as
such, recites an abstract idea.
Finally, claim 1 recites “determining resource pre-positioning and task
scheduling, according to the scenario, by solving, using the processor, for
the one or more variables of each of the models of the scenario in order to
perform the infrastructure management, the solving being based on
achieving one or more objectives.” “[D]etermining resource pre-positioning
and task scheduling . . . by solving . . . the one or more variables” means,
essentially, assigning a start/stop time to an open repair task (solving the
repair-task model’s “interval” variable) and deciding whether to move a
work crew to a different location (solving the work-shift model’s “location”
variable). Spec. ¶¶ 13, 15. Safety tasks are associated with repair tasks, so
deciding a repair task’s start time may determine the safety task’s stop time;
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specific circumstances, such as a downed power line for an electric, may
determine a safety task’s start time. Id. ¶¶ 13–14. The “objectives,” the
achieving of which these decisions are based, are “goals” or preferences that
are considered in making the decisions. Id. ¶ 15. For example, it may be an
objective of the deciding user to minimize the amount of time taken to
resolve tasks or the number of crew movements. Id. In sum, this step
recites another exercise of judgment, an abstract idea.
For the above reasons, we determine that claim 1 recites an abstract
idea, and proceed to Step 2A, Prong 2.
Step 2A, Prong 2
Having determined that claim 1 recites a judicial exception, we next
consider whether claim 1 recites additional elements that integrate the
judicial exception into a practical application. As the Examiner notes, the
additional elements of claim 1 are directed to computer implementation of
the claimed method. Appeal Br. 13 (Claims App.). For example, the claim
states that “generating . . . models” and “determining resource pre-
positioning and task scheduling” are performed “using a processor.” Id.
These limitations are recited at a high level of generality, and the
Specification makes clear that the method can be implemented using general
purpose computers and computer technology. See Spec. ¶ 28, Fig. 5. “The
Court in Alice made clear that a claim directed to an abstract idea does not
move into section 101 eligibility territory by ‘merely requir[ing] generic
computer implementation.’” buySAFE, Inc. v. Google, Inc., 765 F.3d 1350,
1354 (Fed. Cir. 2014) (quoting Alice, 573 U.S. at 220); see also Trading
Techs., 921 F.3d 1084, 1090 (Fed. Cir. 2019) (“This invention makes the
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trader faster and more efficient, not the computer. This is not a technical
solution to a technical problem.”).
We have considered Appellant’s arguments concerning whether claim
1 is directed to a judicial exception, but find that unpersuasive of Examiner
error. Appellant primarily relies on its assertion that the “determining” step
does not recite an abstract idea, and that this step “is inextricably linked with
the other element of the claim, because the models and the constraint must
correspond with the resources to be pre-positioned and the task to be
scheduled.” Appeal Br. 6–7. As discussed above, however, we conclude
that the determining step does recite an abstract idea. Further, Appellant
does not show error in the Examiner’s conclusion that the abstract ideas
recited in claim 1 are not integrated into a practical application.
Considering the above limitations as an ordered combination, we see
nothing that adds more than the limitations considered individually.
Accordingly, considering the additional limitations individually and as an
ordered combination, we agree with the Examiner that they do not integrate
the judicial exception into a practical application. In sum, having reviewed
the additional limitations individually and as an ordered combination, we
agree with the Examiner that claim 1 is directed to a judicial exception.
Step 2B
Having determined that claim 1 is directed to a judicial exception, we
next consider under Step 2B whether claim 1 includes additional elements or
a combination of elements that provide an “inventive concept,” i.e., whether
claim 1 includes specific limitations beyond the judicial exception that are
not “well-understood, routine, conventional” in the field. Revised Guidance,
84 Fed. Reg. at 56. In doing so, we recognize that “[t]he inventive concept
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inquiry requires more than recognizing that each claim element, by itself,
was known in the art,” because “an inventive concept can be found in the
non-conventional and non-generic arrangement of known, conventional
pieces.” BASCOM Glob. Internet Servs., Inc. v. AT&T Mobility LLC, 827
F.3d 1341, 1350 (Fed. Cir. 2016).
The Examiner determines that claim 1 does not include additional
elements sufficient to amount to significantly more than the judicial
exception, because the additional elements are directed to generic computer
implementation of the recited abstract ideas. Final Act. 7–8. Appellant does
not substantively address the Examiner’s Step 2B analysis, asserting that
claim 1 should be found eligible under Step 2A, Prong 2. See Appeal Br. 7
(stating that “the integration of alleged judicial exceptions into a practical
application of determining resource pre-positioning and task scheduling
precludes consideration of processor”). We agree with the Examiner’s
finding that the additional elements, considered individually and as an
ordered combination, recite generic computer implementation, and therefore
the additional elements do not provide an inventive concept for the abstract
idea.
For the above reasons, we agree with the Examiner that claim 1 is
directed to ineligible subject matter, and therefore sustain the Examiner’s
rejection of claims 1, 5–9, 13–16, and 18–20 under 35 U.S.C. § 101.
Claims 1, 5–9, 13–16, 18–20: Rejected as
Unpatentable over Brown and Cocanaugher
Appellant argues claims 1, 7–9, 13–16, and 18–20 as a first group, and
claims 5 and 6 as a second group. Appeal Br. 8–11. We select claim 1 as
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representative of the first group and claim 5 as representative of the second
group. 37 C.F.R. § 41.37(c)(1)(iv).
Claim 1
The Examiner finds that Brown teaches all of the elements of claim 1
except that “Brown doesn’t necessarily teach generating/storing the models
and doesn’t teach work shifts and safety tasks.” Final Act. 10, 12-15 (citing
Brown ¶¶ 1, 3, 22, 26, 28, 31–33, 38, 39, 46, Figs. 4, 5). The Examiner
therefore relies on Cocanougher for the missing limitations. Id. at 11 (citing
Cocanougher ¶ 24, Figs. 2A–4). The Examiner determines that it would
have been obvious to one of ordinary skill in the art “to have combined
Brown’s invention by incorporating the method of Cocanougher because
Brown would be able to use the algorithm seen in paragraph 0030 of
Cocanougher to determine the optimal schedule for the interviewers in
additional to using the interview scheduler.” Id.
We have considered Appellant’s argument’s in support of the
patentability of claim 1, but find them unpersuasive. Appellant argues, for
example, that Brown does not teach the three claimed “models,” and that the
Examiner errs in asserting that “the three types of models specified in claim
1 are mere labels despite the plain meaning conveyed by the model names.”
Appeal Br. 9. While Appellant is correct that the Examiner deems “work
shifts,” repair tasks,” and “safety tasks” to be “mere labels,” the Examiner
also alternatively relies on Cocanougher, in combination with Brown, to
teach the different models, thus giving patentable weight to these terms.
Final Act. 11-–12; Ans. 8–9. We consider this alternative finding in
evaluating the Examiner’s rejection, rather than the Examiner’s position that
these terms are “mere labels.”
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Appellant also argues that “even if Cocanougher did teach the details
of three different types of models as required by Claim 1, the Examiner does
not sufficiently address how or why Brown is properly modified by
Cocanougher or another reference that teaches three types of models.”
Appeal Br. 10. Appellant specifically asserts that “the algorithm at
paragraph [0030] of Cocanougher involves values (e.g., distance value, skill
value, preference value) that are not relevant in Brown and are certainly not
available in Brown.” Id. In response, the Examiner disputes that the
variables discussed in Cocanougher are not relevant to Brown or found in
Brown. Ans. 10. The Examiner asserts that “Cocanougher discusses certain
values in its algorithm (¶0030) such as distance value, availability value,
skill value, and preference value which are also seen in Brown.” Id. That is,
according to the Examiner, “Brown talks about parameters used when
scheduling such as location parameter (¶0028), availability data (¶0028),
order preference (¶0029), and required interviewer list based on their skills
traits (See ¶0042).” Appellant does not directly address these contentions
regarding the relevance of Cocanougher’s values to Brown’s system in the
Reply Brief, and therefore does not identify Examiner error in the
contentions.
Claim 5
Claim 5 depends from claim 1 and additionally recites
[W]herein the solving for the one or more variables of the
scenario includes generating a constrained optimization model,
the constrained optimization model being a constraint
programming model that ensures that a solution does not
require more resources than are available according to the
scenario, and the generating the constrained optimization model
is according to the one or more objectives.
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Appeal Br. 13 (Claims App.). The Examiner relies on Brown to teach these
additional limitations. Final Act. 15-16 (citing Brown ¶¶ 22, 31). Appellant
responds that “the combination of Brown and Cocanougher fails to teach the
claimed generating of a constrained optimization model.” Appeal Br. 11.
Appellant does not, however, address the Examiner’s explanation of how
paragraph 31 of Brown teaches this limitation, and therefore does not show
error in that explanation.
Because we are not persuaded that the Examiner erred in rejecting
claims 1, 5–9, 13–16, 18–20 as unpatentable over Brown and Cocanougher,
we sustain the rejection.
CONCLUSION
The Examiner’s rejections are affirmed.
DECISION SUMMARY
Claim(s)
Rejected
35 U.S.C. § Reference(s)/Basis Affirmed Reversed
1, 5–9, 13–
16, 18–20
101 Eligibility 1, 5–9, 13–16,
18–20

1, 5–9, 13–
16, 18–20
103 Brown,
Cocanougher
1, 5–9, 13–16,
18–20

Overall
Outcome
1, 5–9, 13–16,
18–20

TIME PERIOD FOR RESPONSE
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R.
§ 1.136(a)(1)(iv).

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AFFIRMED