Prosecution Insights
Last updated: April 19, 2026
Application No. 18/170,077

SERVICE PARTS LIFECYCLE FORECASTING

Final Rejection §101
Filed
Feb 16, 2023
Examiner
MINOR, AYANNA YVETTE
Art Unit
3624
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
DELL PRODUCTS, L.P.
OA Round
4 (Final)
18%
Grant Probability
At Risk
5-6
OA Rounds
3y 6m
To Grant
43%
With Interview

Examiner Intelligence

Grants only 18% of cases
18%
Career Allow Rate
33 granted / 179 resolved
-33.6% vs TC avg
Strong +25% interview lift
Without
With
+24.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 6m
Avg Prosecution
47 currently pending
Career history
226
Total Applications
across all art units

Statute-Specific Performance

§101
37.9%
-2.1% vs TC avg
§103
33.6%
-6.4% vs TC avg
§102
12.0%
-28.0% vs TC avg
§112
14.1%
-25.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 179 resolved cases

Office Action

§101
DETAILED ACTION Acknowledgement This final office action is in response to the amendment filed on 12/11/2025. Status of Claims Claims 1, 10, and 18 have been amended. Claims 1, 3-5, 7-10, 12-14, 16-18, and 20 are now pending. Response to Arguments Applicant's arguments filed on 12/11/2025 regarding the 35 U.S.C. 101 rejection of claims 1, 3-5, 7-10, 12-14, 16-18, and 20 have been fully considered. The Applicant argues that (i) the claims are not directed to an abstract idea under Step 2A. For example, claim 1 recites a specific, computer-implemented process that automatically generates a Last Time Buy (LTB) quantity for an end-of-life purchase of the part before production is stopped, based on the claimed rest-of-lifecycle demand forecast. This ties the modeling pipeline to controlling a concrete service-parts replenishment process for deployed technical systems, rather than merely producing information "for consideration" in a business decision; (ii) the rejection's characterization of the claims as a mere "mental process" and "certain methods of organizing human activity" is not accurate. For example, claim 1 recites, in combination, (i) a constrained forecasting pipeline (demand-based and ASU-based forecasts, clustering, gamma- based modeling, and optimal-weight classification) and (ii) automatic generation of a concrete LTB quantity for an end-of-life purchase before production is stopped. At the real-world scale and complexity described in the specification, this process cannot practically be performed in the human mind; and (iii) claim 1 integrates any abstract idea into a practical application that controls a technical replenishment process for service parts used in deployed technical systems. The computing device does not merely "apply" an abstract idea on a generic computer. Instead, claim 1 uses the forecast to automatically determine an LTB quantity timed to an end-of- production event for a specific part, thereby improving the way service-parts lifecycle management is carried out for those systems. The Examiner respectfully disagrees with all arguments. The Examiner maintains the position that the claims reflect the abstract groups of Mental Processes, Certain Methods of Organizing Human Activity, and Mathematical Concepts because the claims describe a process of receiving requests for and generating demand forecasts for a part based on historical data (e.g. field incident rate, optimal weight, demand) which can practically be performed in the human mind with pen and paper. Receiving a request from a user for demand forecasts and transmitting the demand forecast to the user for consideration of a purchase order for the part reflects certain methods of organizing human activity (e.g. facilitating commercial interaction). Generating forecasts as described in the claims involves performing various mathematical calculations and operations. The Examiner submits that the process of forecasting, clustering, and classifying data can absolutely be performed in the mind and does not require a computer to do so. This process is reflected in the field of statistics and was performed manually before the invention of computers. The claims do not recite details or the complexity of forecasting, clustering, and classifying that would exclude the performance in the human mind and/or with pen and paper. Per MPEP 2106.04(a), a claim recites a judicial exception when the judicial exception is “set forth” or “described” in the claim. The Examiner also maintains the position that the additional elements recited in the claims and listed in Steps 2A(2) and 2B do not integrate the abstract idea into a practical application or provide significantly more. The additional elements do not improve the functioning of a computer or improve another technology or technical field. The additional elements reflect computing devices that are used to perform/automate the abstract idea. The Examiner does not find a direct or physical control mechanism of a technological component or system, beyond providing/displaying information (e.g. last time buy (LTB) quantity) to a user/person to assist in making a purchase decision. Providing this information may improve the timing of purchasing end of life parts (i.e. lifecycle management/scheduling), however, this improvement does not reflect an improvement in technology. There is no improvement in computer functionality or improvement in any other technological component or system beyond its original capabilities as a result of implementing the Applicant’s process. As per MPEP 2106.05(a)(I): “The Federal Circuit has also indicated that mere automation of manual processes or increasing the speed of a process where these purported improvements come solely from the capabilities of a general-purpose computer are not sufficient to show an improvement in computer-functionality. Also, per MPEP 2106.05(a)(II), an improvement in the abstract idea itself is not an improvement in technology. Therefore, the 35 U.S.C. 101 rejection is maintained. Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1, 3-5, 7-10, 12-14, 16-18, and 20 are rejected under 35 U.S.C. 101 because the claimed invention, “Service Parts Lifecycle Forecasting”, is directed to an abstract idea, specifically Mental Processes, Certain Methods of Organizing Human Activity, and Mathematical Concepts without significantly more. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements individually or in combination provide mere instructions to implement the abstract idea on a computer. Step 1: Claims 1, 3-5, 7-10, 12-14, 16-18, and 20 are directed to a statutory category, namely a process (claims 1, 3-5, 1-9, and 13-14), a machine (claims 10, 12, and 16-17), and a manufacture (claims 18 and 20). Step 2A (1): Independent claims 1, 10, and 18 are directed to an abstract idea of Mental Processes, Certain Methods of Organizing Human Activity, and Mathematical Concepts based on the following claim limitations: “receiving a request,…, for a rest-of-lifecycle demand for a part; generating,…, a demand-based forecast for the part; generating a training dataset by extracting demand data from a corpus of historical dispatch data relating to a plurality of historical parts; building a first classification model trained on the training dataset to assign the part to one or more a clusters; clustering, by the classification model, the plurality of historical parts that have completed their lifecycles into one or more clusters of the historical parts that have completed their lifecycles, wherein the clustering includes a plurality of demand curves; classifying, by the classification model, the part into one of the one or more clusters of the historical parts that have completed their lifecycles; and generating the rest-of-lifecycle demand forecast for the part based on the classification of the part into one of the one or more clusters of the historical parts that have completed their lifecycles; generating,…, an active service unit (ASU)-based forecast for the part based on a field incident rate of the part; estimating,…, an historical optimal weight for each of a plurality of historical parts for which lifecycle demand is known, the historical optimal weight indicative of dependency of demand-based forecasts and ASU-based forecasts to actual demand for the plurality of historical parts; predicting, …, an optimal weight to apply to the demand-based forecast and the ASU-based forecast for the part, the optimal weight predicted by a second classification model trained on the training dataset and the historical optimal weights; generating,…, a rest-of-lifecycle demand forecast for the part based on a combination of the demand-based forecast and the ASU-based forecast for the part according to the optimal weight, wherein the generating the rest-of-lifecycle demand forecast for the part includes: generating one or more subclusters within the cluster of the historical parts in which the part is classified into based on similarity of a mode and a width of fitted gamma distribution curves of the historical parts included in the cluster of the historical parts in which the part is classified into, wherein the fitted gamma distribution curves are based on gamma distributions fitted to data of the demand curves of the historical parts included in the cluster of the historical parts in which the part is classified into; assigning the part to one of the one or more subclusters; and determining gamma-related parameters, shape, rate, and height, from the fitted gamma distribution curves of the historical parts included in the subcluster; and transmitting,…, the rest-of-lifecycle demand forecast…for consideration of a purchase order of the part”. These claim limitations describes a process of receiving requests for and generating demand forecasts for a part by using trained models based on historical data (e.g. field incident rate, optimal weight, demand) and forecasting techniques (e.g. clustering, classifying, distribution curves) which can practically be performed in the human mind with pen and paper. Receiving a request from a user for demand forecasts and transmitting the demand forecast to the user for consideration of a purchase order for the part reflects certain methods of organizing human activity (e.g. facilitating commercial interaction). Dependent claims 3-5, 7-9, 12-14, 16-17, and 20 further describe the forecasting process/techniques (e.g. clustering, classifying, distribution curves, Monte Carlo simulation) and variables involved (e.g. historical demand, features of parts, optimal weight etc.). Generating forecasts involve performing various mathematical calculations and operations. Therefore, these limitations, under the broadest reasonable interpretation, fall within the abstract groupings of Mental Processes which include concepts performed in the human mind such as observations, evaluations, judgments, and opinions, Certain Methods of Organizing Human Activity which encompasses commercial interactions, and Mathematical Concepts which encompasses mathematical relationships, mathematical formulas or equations, and mathematical calculations. Mental Processes include claims directed to collecting information, analyzing it, and displaying certain results of the collection and analysis even if they are claimed as being performed on a computer. Certain Methods of Organizing Human Activity can encompass the activity of a single person (e.g. a person following a set of instructions), activity that involve multiple people (e.g. a commercial interaction), and certain activity between a person and a computer (e.g. a method of anonymous loan shopping). Therefore, claims 1, 3-5, 7-10, 12-14, 16-18, and 20 are directed to an abstract idea and are not patent eligible. Step 2A (2): This judicial exception is not integrated into a practical application. In particular, claims 1, 10, and 18 recite additional elements of “…by a computing device; a client application; a computing device comprising one or more non-transitory machine-readable mediums configured to store instructions; and one or more processors configured to execute the instructions stored on the one or more non-transitory machine-readable mediums, wherein execution of the instructions causes the one or more processors to carry out a process comprising; and a non-transitory machine-readable medium encoding instructions that when executed by one or more processors cause a process to be carried out”. These additional elements do not integrate the abstract idea into a practical application because the claims do not recite (a) an improvement to another technology or technical field and (b) an improvement to the functioning of the computer itself and (c) implementing the abstract idea with or by use of a particular machine, (d) effecting a particular transformation or reduction of an article, or (e) applying the judicial exception in some other meaningful way beyond generally linking the use of an abstract idea to a particular technological environment. These additional elements evaluated individually and in combination are viewed as computing devices that are used to perform the abstract idea of generating forecasts. Limitations that recite mere instructions to implement an abstract idea on a computer or merely uses a computer as a tool to perform an abstract idea are not indicative of integration into a practical application (see MPEP 2106.05(f)). Therefore, claims 1, 3-5, 7-10, 12-14, 16-18, and 20 do not include individual or a combination of additional elements that integrate the judicial exception into a practical application and thus are not patent eligible. Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. claims 1, 10, and 18 recite additional elements of …by a computing device; a client application; a computing device comprising one or more non-transitory machine-readable mediums configured to store instructions; and one or more processors configured to execute the instructions stored on the one or more non-transitory machine-readable mediums, wherein execution of the instructions causes the one or more processors to carry out a process comprising; and a non-transitory machine-readable medium encoding instructions that when executed by one or more processors cause a process to be carried out”. These additional elements evaluated individually and in combination are viewed as mere instructions to apply or implement the abstract idea on a computer. Applying an abstract idea on a computer does not integrate a judicial exception into a practical application or provide an inventive concept (see MPEP 2106.05(f)). Therefore, claims 1, 3-5, 7-10, 12-14, 16-18, and 20 do not include individual or a combination of additional elements that are sufficient to amount to significantly more than the judicial exception and thus are not patent eligible. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ayanna Minor whose telephone number is (571)272-3605. The examiner can normally be reached M-F 9am-5 pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached at 571-272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /A.M./Examiner, Art Unit 3624 /Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624
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Prosecution Timeline

Feb 16, 2023
Application Filed
Dec 03, 2024
Non-Final Rejection — §101
Mar 10, 2025
Response Filed
Apr 25, 2025
Final Rejection — §101
May 16, 2025
Interview Requested
Jun 03, 2025
Examiner Interview Summary
Jun 03, 2025
Applicant Interview (Telephonic)
Jul 01, 2025
Response after Non-Final Action
Jul 31, 2025
Request for Continued Examination
Aug 05, 2025
Response after Non-Final Action
Sep 05, 2025
Non-Final Rejection — §101
Dec 11, 2025
Response Filed
Feb 23, 2026
Final Rejection — §101 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

5-6
Expected OA Rounds
18%
Grant Probability
43%
With Interview (+24.7%)
3y 6m
Median Time to Grant
High
PTA Risk
Based on 179 resolved cases by this examiner. Grant probability derived from career allow rate.

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