United Parcel Service of America, Inc.

Patent Trials and Appeals Board

Nov 25, 2020

2020004260 (P.T.A.B. Nov. 25, 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.
14/182,066 02/17/2014 Carrie Parris IPP201326804 1029
143177 7590 11/25/2020
Shook, Hardy & Bacon L.L.P.
(United Parcel Service, Inc.)
2555 Grand Blvd.
Kansas City, MO 64108-2613
EXAMINER
DIVELBISS, MATTHEW H
ART UNIT PAPER NUMBER
3624
NOTIFICATION DATE DELIVERY MODE
11/25/2020 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):
shbdocketing@shb.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
____________________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________________

Ex parte CARRIE PARRIS,
ALAN AMLING, and SCOTT HERTEL
__________________

Appeal 2020-004260
Application 14/182,066
Technology Center 3600
____________________

Before JOSEPH A. FISCHETTI, JAMES P. CALVE, and
CYNTHIA L. MURPHY, Administrative Patent Judges.

CALVE, Administrative Patent Judge.

DECISION ON APPEAL

STATEMENT OF THE CASE
Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from the decision
of the Examiner to reject claims 1–12, 14–17, 20, 21, and 24.2 Appeal Br. 1.
We have jurisdiction under 35 U.S.C. § 6(b).
We AFFIRM.

1 “Appellant” refers to “applicant” as defined in 37 C.F.R. § 1.42. United
Parcel Service of America, Inc. is identified as the real party in interest.
Appeal Br. 4.
2 Claims 13, 18, 19, 22, and 23 are cancelled. Appeal Br. 47, 48, 51 (Claims
App.).
Appeal 2020-004260
Application 14/182,066

2
CLAIMED SUBJECT MATTER
Claims 1, 20, and 24 are independent. Claim 1 recites:
1. A service cycle management system for
dynamically routing an asset or commodity item within a post-
sales reverse service cycle loop of a supply chain to satisfy one
or more pre-defined outcome-based parameters defined by one
or more holders of the asset or commodity item, said system
comprising:
one or more memory storage areas containing:
(1) input data associated with said one or
more holders of said asset or commodity item, the
input data comprising customer data comprising
one or more requests for post-sales reverse service
cycle support associated with the asset or
commodity item;
(2) service data associated with a plurality of
service tasks configured for handling said asset or
commodity item within said reverse service cycle
loop; and
(3) provider data associated with one or
more capabilities of a plurality of service providers
and indicative of whether the plurality of service
providers are capable of performing at least one of
said plurality of service tasks; and
one or more computer processors configured to:
(A) receive a first portion of said input data,
said first portion comprising the customer data
comprising the one or more requests for post-sales
reverse service cycle support associated with the
asset or commodity item;
(B) retrieve a second portion of said input
data, said second portion comprising one or more
pre-defined parameters associated with handling of
said asset or commodity item within said reverse
service cycle loop, said one or more parameters
being pre-defined by said one or more holders and
being configured to define at least one outcome
Appeal 2020-004260
Application 14/182,066

3
desired by said holder, said at least one outcome
defining:
a preference for donating said asset or
commodity item; and
a preference for introducing said asset or
commodity to a secondary retail market and a
desired yield revenue resulting from said handling
of said asset or commodity item within said
reverse service cycle loop, wherein the desired
yield revenue comprises a recaptured value from
said asset or commodity item within the reverse
service cycle loop;
(C) determine an optimal handling of the
asset or commodity item within the reverse service
cycle loop, the optimal handling being determined
by a combination of:
i. determining one or more optimal
service tasks for handling of said asset or
commodity item within said reverse service
cycle loop, the one or more optimal service
tasks comprising at least one of (1) repair,
(2) refurbishment, (3) recycling, or (4)
donation of said asset or commodity item,
said determination being based at least in
part upon said service data, the service data
comprising a yield revenue associated with
the one or more optimal service tasks; and
ii. in response to determining said one
or more optimal service tasks, determining
one or more optimal service providers to
perform said one or more optimal service
tasks, said determination being based at least
in part upon said preference for donating
said asset or commodity item and said
desired yield revenue resulting from said
handling of said asset or commodity item
within said reverse service cycle loop, said
one or more determined optimal service
tasks, and said one or more pre-defined
Appeal 2020-004260
Application 14/182,066

4
parameters defined by said one or more
holders; and
(D) in response to receiving the customer
data comprising the one or more requests for post-
sales reverse service cycle support associated with
the asset or commodity item and determining said
one or more optimal service providers to perform
said one or more optimal service tasks,
automatically generate and transmit to one or more
systems operated by said one or more optimal
service providers one or more electronic
instructions, said one or more electronic
instructions being configured for automatic
initiation of performance of said one or more
optimal service tasks via execution of at least one
of said one or more systems, said execution
comprising dynamically directing physical routing
of said asset or commodity item within said
reverse service cycle loop so as to dynamically
satisfy said one or more parameters pre-defined by
said one or more holders of said asset or
commodity item and achieve said desired yield
revenue result.
Appeal Br. 43–45 (Claims App.).
REJECTIONS
Claims 1–12, 15–17, 20, 21, and 24 are rejected under 35 U.S.C.
§ 103 as unpatentable over Yang (US 2001/0034673 A1, pub. Oct. 25,
2001), Boesjes (US 7,363,249 B1, iss. Apr. 22, 2008), Shukla (US 2011/
0257991 A1, pub. Oct. 20, 2011), and Whitman (US 2002/0019785 A1, pub.
Feb. 14, 2002).
Claims 14 is rejected under 35 U.S.C. § 103 as unpatentable over
Yang, Boesjes, Shukla, Whitman, and Meldrum (US 2013/0018696 A1, pub.
Jan. 17, 2013).
Appeal 2020-004260
Application 14/182,066

5
ANALYSIS
Claims 1–12, 15–17, 20, 21, and 24
Rejected Over Yang, Boesjes, Shukla, and Whitman
Appellant argues claims as a group. Appeal Br. 16–37. We select
claim 1 as representative. Claims 2–12, 15–17, 20, 21, and 24 stand or fall
with claim 1. See 37 C.F.R. § 41.37(c)(1)(iv).
Regarding claim 1, the Examiner relies on Yang to teach a service
cycle management system that dynamically routes an asset or a commodity
item in a post-sales reverse service cycle loop of a supply chain including
memory storage areas containing input data comprising customer data of one
or more requests for post-sales reverse service cycle support associated with
the asset or commodity item. Non-Final Act. 3–5 (citing Yang ¶¶ 37, 38),
42 (citing id. ¶¶ 4, 21, 27, 37, 38); Ans. ¶¶ 4, 21, 27, 33, 35, 36).
Appellant argues that Yang may refer to a reverse logistics flow of
service parts in some passages, but paragraphs 37 and 38 refer to a forward
cycle to purchase parts via the supply chain. Appeal Br. 16–18. Appellant
argues that “[t]he customer’s request to purchase parts in a forward supply
chain does not teach customer data including a request for post-sales reverse
service cycle support, which is a request for return or repair of a previously-
purchased part.” Id. at 18; see Reply Br. 4–8.
The Examiner correctly finds that Yang receives customer input data
for marketplace 14 operations (Yang ¶ 27) that provide “reverse logistics”
cycles of returns of service parts processed through returns supply chain 28
and repair requests processed through repair center scheduling function 88
so planning function 86 can determine a net supply signal for supply chain
12 (id. ¶ 36). Ans. 4–5 (citing Yang ¶¶ 4, 21, 27, 36).
Appeal 2020-004260
Application 14/182,066

6
We disagree that Yang does not teach “a request for return or repair
of a previously-purchased part.” Appeal Br. 18. In Yang, customers return
service parts for replacement/repair in reverse logistics returns supply chain
28. Yang ¶¶ 21–23, 36. Customers input requests for “new” or “like new”
service parts, service parts repaired to different version levels, and service
parts that replace parts originally built-to-order. Id. ¶ 23; see id. ¶¶ 21–27.
We also agree that Yang uses “service data associated with a plurality
of service tasks configured for handling said asset or commodity item within
said reverse service cycle loop” as claimed. See Ans. 5–7. Appellant asserts
that “service tasks” are “tasks performed on an individual item in the reverse
service cycle loop, such as ‘(1) repair, (2) refurbishment, (3) recycling, or
(4) donation’ of an item.” Appeal Br. 21.
Yang teaches service parts planning function 86 that manages service
of parts flowing through returns supply chain 28 of a reverse logistics loop.
Yang ¶ 36. Repair center scheduling function 88 monitors a flow of service
parts in returns supply chain 28 and communicates information to planning
function 86 so planning function 86 may determine a net supply signal for
service parts within supply chain 12. Id. Customers return service parts to
distributors 20 for replacement or repair through a “reverse logistics” chain
for insertion into forward supply chain 22 in some cases. Id. ¶ 21. Service
data includes repair of service parts to “new” or “like new” condition, cycle
times for each repair operation, “good” returns that do not need inspection,
testing, or repackaging, repair parts to be scrapped/condemned, repair parts
refurbished to different version levels, repair parts built-to-order rather than
built-to-stock, and disassembly of multi-component assemblies that can be
recycled as multiple returned service parts. Id. ¶¶ 21, 23, 27.
Appeal 2020-004260
Application 14/182,066

7
Returned service parts requiring repairs will flow backward through
supply chain 22 to repair center 30 where they are repaired or furbished and
returned to supply chain 22. See id. ¶¶ 22, 23. Yang manages reverse cycle
logistics because “supply chain 22 typically depends heavily on the flow of
returned service parts through returns supply chain 28” so that “for effective
inventory planning and management, flows within both supply chain 22 and
returns supply chain 28 must be accurately modeled.” Id. ¶ 23.
We also agree with the Examiner that Yang teaches “provider data
associated with one or more capabilities of a plurality of service providers
and indicative of whether the plurality of service providers are capable of
performing at least one of said plurality of service tasks” as claimed. Ans.
7–8. Yang manages the inventory of service parts to allocate service parts
optimally between customers and to schedule service activities with service
parts that are available in the post-sale reverse service cycle loop. Id. ¶ 24.
Customers obtain service parts for service needs in a time period. Id. ¶ 38.
Service providers provide different repair cycle times, disassembly ability
for multi-component service parts, assessment of “good” returns that do not
require repair, scrapping or condemning some parts, repairing service parts
to different versions, and rebuilding repair parts to replace original built-to-
order parts. Id. ¶ 23. Post-sale service scheduling 100 coordinates service
parts requirements with service requests. Id. ¶ 40. Service scheduling 100
processes service requests and provides a promise date to a customer based
on provider data such as a pool of field engineers or other support personnel
who are skilled to handle a service request. Id. Customers adopt rules and
models to maintain inventories of service parts and determine which parts
are the most important for service providers to maintain. See id. ¶¶ 17–20.
Appeal 2020-004260
Application 14/182,066

8
Appellant asserts that Yang does not teach parameters pre-defined by
a holder and configured to define an outcome desired by the holder because
Yang does not teach a reverse service cycle or desired outcome. Appeal Br.
24–28. The Specification gives examples of (but does not explicitly define)
customer pre-defined parameters and desired outcomes as maximizing the
life cycle of a machine by performing repairs on broken parts. Spec. ¶ 57.
Another example is a pre-defined parameter to replace a machine if part “X”
breaks that results in collection, testing, and disassembly of a machine upon
the breakage of part “X”. Id. If a customer sets a parameter of at least a 5%
yield for reverse cycle processing, the system may skip refurbishment if the
yield is only 4% or if pre-defined parameters state that remanufacture and/or
recycling of component parts are not options. Id. ¶ 101. Even if a repair or
reuse of a machine may exceed a 5% minimum yield parameter, the system
may forego such option if another customer pre-defined parameter requires a
turnaround time of less than 48 hours, 99% of the time, and the system
cannot achieve that desired outcome. Id. ¶ 102.
Yang’s reverse cycle application 52 uses pre-defined parameters such
as (1) “good” returned service parts are sold or reused, (2) customers require
“new” service parts versus “like new” service parts, (3) service parts are
repaired a limited number of times, (4) some service parts are built-to-order
rather than built-to-stock, (5) service parts are replaced, repaired, scrapped,
or condemned, (6) parts are upgraded, and (7) parts are disassembled. Yang
¶¶ 18–23, 33, 35, 36. Yang uses parameters to forecast demand and allocate
service parts and services optimally. Id. ¶ 24; Ans. 9; Non-Final Act. 8–9.
Parameters help to maintain optimal service parts inventory levels and to
reduce operating costs and disruptions to operations. Yang ¶¶ 4, 9, 32–38.
Appeal 2020-004260
Application 14/182,066

9
Appellant contends that the references do not determine an optimal
handling of the asset or commodity item in the reverse service cycle loop
wherein the optimal service tasks include repair, refurbishment, recycling,
and/or donation. Appeal Br. 28.
In response, the Examiner points out that Yang’s system determines
optimal service parts inventory plans and service parts budget deployments
to determine optimal inventory targets for stocking locations in the supply
chain. Yang ¶¶ 35, 36; Non-Final Act. 9–10; Ans. 9–10. Yang determines
optimal locations to inventory service parts, optimal inventory levels at each
stocking location, and optimal allocation of service parts between customers
using the parameters described above and other factors. Yang ¶ 24; Ans. 9–
10. Yang’s reverse logistics returns supply chain 28 can optimize returned
service parts that are assemblies of multiple components by dismantling the
assemblies to yield multiple returned service parts. Yang ¶ 21. Returned
service parts that are in a “good” condition may be reinserted into supply
chain 22 without inspection, testing, or repackaging. Id. ¶¶ 22, 23. Other
returned service parts are scrapped or condemned. Id. ¶ 23. Repair parts
may be upgraded to a different version rather than ordering a new part. Id.
Excess inventory is identified relative to desired inventory targets and excess
inventory is transferred to stocking locations or disposed of to maintain a
desired net inventory. Id. ¶ 37. Yang optimizes the handling of returned
service parts via a reverse logistics process that optimizes repair, recycling,
and/or refurbishment of returned service parts for subsequent insertion back
into a forward supply chain in order to maintain optimal inventory levels at
distribution centers and inventory locations thereby to reduce the operating,
inventory, and customer care costs. Id. ¶¶ 4, 9, 21–23, 35–37.
Appeal 2020-004260
Application 14/182,066

10
Appellant argues that neither Yang nor Boesjes determines one or
more optimal service providers to perform one or more optimal service tasks
as claimed. Appeal Br. 32–33. Appellant asserts that Boesjes fulfills sales
orders to retailers versus service providers that perform services on an item
in a reverse service cycle. Id. at 33. Appellant contends that paragraph 36
of Yang describes forward supply chain suppliers so Boesjes’ description of
an optimal product distributor in a reverse cycle does not combine with
Yang to teach the optimal service provider feature. Reply Br. 13–14.
As discussed above, Yang uses a reverse logistics returns supply chain
to optimize repair, recycling, and refurbishment of returned service parts. A
skilled artisan would recognize that optimizing this process requires service
providers to perform optimal services of disassembly of multi-component
assemblies into multiple service parts, repair/upgrade to different versions,
repair to replace built-to-order parts, identification of “good” returns that do
not require repair, and repair/refurbishment functions sent to suitable repair
centers 30 at suitable locations. Id. ¶¶ 8, 18–23. Yang also allocates service
parts best suited for a service request with field engineers/support personnel
who are best qualified to handle each service request. Id. ¶¶ 40, 41.
The Examiner cites Boesjes to teach the knowledge in supply chain
management to find an optimum product provider. See Boesjes, 10:45–55;
Ans. 11. In combination with Yang’s selection of optimal service providers
to optimize reverse logistics on returned service parts by optimizing repairs,
upgrades, disassembly, recycling, or scrapping, and optimizing services for
customers (Yang ¶¶ 18–24, 40), Boesjes’ optimization of product supply
services would improve Yang’s delivery of optimal services by service
providers similarly and render obvious the “optimal service providers.”
Appeal 2020-004260
Application 14/182,066

11
For similar reasons, we also agree with the Examiner that Yang and
Boesjes render obvious dynamic physical routing of returned repair parts in
a reverse service cycle to dynamically satisfy a pre-defined parameter by
holders of the asset as claimed. Yang considers customer demands for new
service parts, the number of times parts are repaired, cycle times for repair
stages of returns supply chain 28, recycling multi-part assemblies, upgrading
parts to different versions, and optimal service locations and inventories in
order to allocate service parts dynamically and optimally among customers,
coordinate service parts availability and service activities, and to maintain an
optimum inventory at stocking locations that meet forecasted demand and
target customer service levels. Dynamic routing to distribution and repair
centers achieves desired yield revenue results such as optimal service parts
inventories, reduced operating costs, and optimized service budgets with the
target inventories updated at regular intervals as Boesjes also teaches. Yang
¶¶ 5, 9, 18–29, 33–36, 50; Boesjes, 12:4–50; see Ans. 12–13.
Accordingly, we sustain the rejection of claim 1 and claims 2–12, 15–
17, 20, 21, and 24, which fall with claim 1.
Claim 14
Rejected Over Yang, Boesjes, Shukla, Whitman, and Meldrum
Claim 14 depends from claim 1 and recites that “said one or more
parameters comprise a requirement that said one or more requests be
processed and said one or more outcome-based parameters be satisfied
within 48 hours of submittal of said one or more requests, 99% of the time.”
Appeal Br. 48 (Claims App.). Appellant argues that the references do not
teach a requirement that is received as a parameter from a holder of an item
to be handled in a post-sales reverse service cycle loop. Appeal Br. 38–41.
Appeal 2020-004260
Application 14/182,066

12
As discussed above, Yang already teaches customer requirements as
pre-defined parameters for handling an asset or commodity item in a reverse
service cycle received from a holder of an asset/item. Non-Final Act. 3–9.
Yang’s user pre-defined parameters for handling service parts in a reverse
logistics cycle loop include customers returning service parts to distributors
for replacement or repair, demanding “new” service parts or service parts
repaired to a different version, scrapping or condemning returned service
parts, repairing service parts to replace built-to-order parts, requiring optimal
inventories and allocations of service parts to meet target customer service
levels, and optimally allocating service parts in returns supply chain 28. See
Yang ¶¶ 18–24, 35–41. However, Yang does not teach numeric parameters
for performing such reverse supply chain processes as recited in claim 14.
Therefore, the Examiner relies on Shukla to teach the knowledge in
the art that customer parameters for processing requests in a reverse logistics
supply cycle can require or expect satisfaction within 48 hours of submitting
a request. Shukla teaches that products in a reverse cycle logistics loop are
shipped or delivered within 24 hours of receiving a purchase request for the
product. See Shukla ¶¶ 62–71. Whitman teaches that products returned in a
reverse cycle logistics loop are resold within hours of receipt of the products
to minimize losses. Whitman ¶ 146. Shukla and Whitman teach customer
requirements in reverse logistics cycles to ship/deliver products in 24 hours
or sell products in hours. Yang teaches customer requirement parameters to
process goods in reverse logistics cycles discussed above (see Ans. 14–15)
that would be improved similarly using Shukla’s and Whitman’s teachings.
Yang also teaches the importance of timeliness requirements to airline and
automobile industries that use reverse logistics processes. See Yang ¶ 9.
Appeal 2020-004260
Application 14/182,066

13
Again, Appellant attacks the teachings of the references in isolation
instead of as applied by the Examiner. Even if we consider the teachings in
isolation, Shukla teaches an exemplary customer requirement parameter to
process goods in a reverse supply cycle by shipping or delivering the items
within 24 hours of an order. Shukla illustrates a time frame that customers
expect or demand for products. Whitman illustrates a faster reverse supply
cycle that resells products within hours in an e-commerce setting. These
teachings illustrate what customers expect/require and what requirements a
business must meet to be successful in commerce by satisfying customer
expectations/requirements for reselling products in a reverse supply chain.
Meldrum teaches customer supply chain requirements of inventory
management to maintain product shelf availability at least 95% of the time.
Meldrum ¶¶ 1, 4. The Examiner reasons that this reliability rating of above
95% encompasses the claimed 99% of the time range and renders it obvious.
Ans. 14. Yang uses a reverse logistics supply cycle that satisfies customer
requirement parameters and customer service targets. The reverse logistics
cycle provides service parts through returns supply chain 28 to maintain
optimal service parts inventories and meet demand forecasts. Yang ¶¶ 21–
23, 34–36. Yang teaches the suitability of its reverse logistics and inventory
management process in industries that require high levels of reliability. In
the airline industry, the reverse logistics cycle must improve service parts
availability and predictability, produce fewer delayed and canceled flights,
lower operating costs, and improve customer satisfaction. In the automobile
industry, the reverse logistics cycle must improve supply chain efficiencies
to manage lean manufacturing processes better, meet build-to-order goals
more reliably, and reduce rush orders and overtime costs. See Yang ¶ 9.
Appeal 2020-004260
Application 14/182,066

14
When, as here, a prior art range overlaps a claimed range, it renders
that range obvious unless the claimed range is critical or yields unexpected
results. E.g., In re Peterson, 315 F.3d 1325, 1329–30 (Fed. Cir. 2003)
(“Selecting a narrow range from within a somewhat broader range disclosed
in a prior art reference is no less obvious than identifying a range that simply
overlaps a disclosed range. In fact, when, as here, the claimed ranges are
completely encompassed by the prior art, the conclusion is even more
compelling than in cases of mere overlap.”).
Accordingly, we sustain the rejection of claim 14.
CONCLUSION
In summary:
Claims
Rejected
35 U.S.C.
§
Reference(s)/
Basis
Affirmed Reversed
1–12, 15–17,
20, 21, 24
103 Yang, Boesjes,
Shukla, Whitman
1–12, 15–17,
20, 21, 24

14 103 Yang, Boesjes,
Shukla, Whitman,
Meldrum
14
Overall
Outcome
1–12, 14–17,
20, 21, 24

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).
AFFIRMED