United Parcel Service of America, Inc.Download PDFPatent Trials and Appeals BoardNov 25, 20202020004260 (P.T.A.B. Nov. 25, 2020) Copy Citation 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 Copy with citationCopy as parenthetical citation