Prosecution Insights
Last updated: October 26, 2026
Application No. 18/644,625

Methods and Systems for Controlling a Transport System

Non-Final OA §103
Filed
Apr 24, 2024
Priority
Apr 26, 2023 — EU 23170083.2
Examiner
LAUGHLIN, CHARLES S
Art Unit
2846
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Siemens Aktiengesellschaft
OA Round
3 (Non-Final)
77%
Grant Probability
Favorable
3-4
OA Rounds
6m
Est. Remaining
86%
With Interview

Examiner Intelligence

Grants 77% — above average
77%
Career Allowance Rate
306 granted / 399 resolved
+8.7% vs TC avg
Moderate +9% lift
Without
With
+9.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
27 currently pending
Career history
444
Total Applications
across all art units

Statute-Specific Performance

§101
2.9%
-37.1% vs TC avg
§103
52.9%
+12.9% vs TC avg
§102
33.0%
-7.0% vs TC avg
§112
9.7%
-30.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 399 resolved cases

Office Action

§103
DETAILED ACTION 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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 9/16/26 has been entered. Priority Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 1-2, and 5-14 are rejected under 35 U.S.C. 103 as being unpatentable over Wagner et al. (US 2024/0088809) in view of Zehnder et al. (US 2021/0124337). Regarding claim 1, Wagner discloses (Fig. 1): A method for controlling a transport system (Fig. 1, 1)with at least one linear and/or planar motor having a stator (2, ¶0022), at least one mover (Tn),and a controller (4) for automatically controlling movement of the at least one mover (Tn) relative to the stator (2, ¶0022), the method comprising: a) providing a thermal model for the transport system (¶0056); d) running a simulation of a temperature distribution within the at least one linear and/or planar motor during a simulated movement based on the selected movement plan using the thermal model (¶0056); e) executing the determined movement plan on the transport system using the controller (¶0072) only if the movement plan respects at least one predefined temperature limit within the simulation (¶0056); else, repeating element (d) with an adapted movement plan (¶0065-¶0068). Wagner does not disclose: b) generating one or more candidates for a movement plan using a mathematical optimization method and/or a heuristic method; c) verifying the one or more candidates to select the movement plan for the at least one mover according to a predefined movement task and, However, Zehnder teaches (Fig. 9): b) generating one or more candidates for a movement plan using a mathematical optimization method and/or a heuristic method (Fig. 9, M, selects multiple movement plans, ¶0046); c) verifying the one or more candidates to select the movement plan for the at least one mover according to a predefined movement task (¶0046) and, Regarding claim 1, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the linear motor simulation and planning method from Wagner that can make and change a movement plan based on a temperature model (¶0056) and create multiple movement models and select a movement model that’s the most optimal as taught by Zehnder (¶0046). This would improve efficiency of the system. Regarding claim 2, Wagner discloses (Fig. 1): wherein: b) through d) are each carried out several times, such that a plurality of consecutive movement plans is determined and executed; during the determination of each movement plan, at least one simulation of the temperature distribution within the at least one linear and/or planar motor is carried out; and the simulation of each of the following movement plans uses the temperature distribution obtained for the preceding movement plan as input (¶0052). Regarding claim 5, Wagner discloses (Fig. 1): wherein the thermal model comprises a physical model of the at least one linear and/or planar motor (¶0052). Regarding claim 6, Wagner discloses (Fig. 1): wherein: the simulation within uses a temperature correction module based on at least one artificial neural network (¶0070); and the temperature correction module serves to correct the simulated temperature distribution obtained from the thermal model (¶0056). Regarding claim 7, Wagner discloses (Fig. 1): further comprising adapting the temperature correction module using at least one physical measurement carried out during the operation of the transport system (from physical model, ¶0073). Regarding claim 8, Wagner discloses (Fig. 1): wherein the at least one physical measurement comprises a temperature measurement within the at least one motor and/or a measurement of an external physical parameter in the environment of the at least one motor (¶0056). Regarding claim 9, Wagner discloses (Fig. 1): wherein the temperature correction module is based on at least one artificial neural network being trained with data obtained from the operation of the transport system (¶0070). Regarding claim 10, Wagner discloses (Fig. 1): wherein the artificial neural network is being trained on a computing device (5) separate from the controller (4, ¶0025). Regarding claim 11, Wagner discloses (Fig. 1): wherein determining the movement plan is based on the minimization of a temperature within the at least one motor and at least one further criterion (¶0056). Regarding claim 12, Wagner discloses (Fig. 1): wherein: the transport system comprises one or more movers (fig. 1, Tn, Tn-1, etc.); and each mover functions as a carrier for a transported element (¶0022). Regarding claim 13, Wagner discloses (Fig. 1): A controller (Fig. 1, 4) for controlling the movement in a transport system (1) with at least one linear and/or planar motor having a stator (2) and at least one mover (Tn, Tn-1, ¶0022), wherein the controller: provides a thermal model for the transport system (¶0056); d) runs a simulation of a temperature distribution within the at least one linear and/or planar motor during a simulated movement based on the selected movement plan using the thermal model (¶0056); and e) Executes the movement plan on the transport system (¶0072) only if the movement plan respects at least one predefined temperature limit within the simulation (¶0056); else, repeating element (d) with an adapted movement plan (¶0065-¶0068). Wagner does not disclose: b) generates one or more candidates for a movement plan using a mathematical optimization method and/or a heuristic method c) verifies the one or more candidates to select the movement plan for the at least one mover according to a predefined movement task; e) executes the determined movement plan However, Zehnder teaches (Fig. 9): b) generates one or more candidates for a movement plan using a mathematical optimization method and/or a heuristic method (Fig. 9, M, selects multiple movement plans, ¶0046); c) verifies the one or more candidates to select the movement plan for the at least one mover according to a predefined movement task (¶0046); e) executes the determined movement plan(¶0046) Regarding claim 13, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the linear motor simulation and planning method from Wagner that can make and change a movement plan based on a temperature model (¶0056) and create multiple movement models and select a movement model that’s the most optimal as taught by Zehnder (¶0046). This would improve efficiency of the system. Regarding claim 14, Wagner discloses (Fig. 1): A transport system (Fig. 1, 1) comprising: at least one linear and/or planar motor having a stator (2, ¶0022), and at least one mover (Tn); and a controller (4) for automatically controlling the movement of the at least one mover (Tn) relative to the stator (2, ¶0022), wherein the controller ((4): a) provides a thermal model for the transport system (¶0056); d) runs a simulation of a temperature distribution within the at least one linear and/or planar motor during a simulated movement based on the selected movement plan using the thermal model (¶0056); and e) executes the determined movement plan on the transport system (¶0072) only if the movement plan respects at least one predefined temperature limit within the simulation (¶0056); else, repeating element (d) with an adapted movement plan (¶0065-¶0068). Wagner does not disclose: b) generates one or more candidates for a movement plan using a mathematical optimization method and/or a heuristic method c) verifies the one or more candidates to select the movement plan for the at least one mover according to a predefined movement task; e) executes the determined movement plan However, Zehnder teaches (Fig. 9): b) generates one or more candidates for a movement plan using a mathematical optimization method and/or a heuristic method (Fig. 9, M, selects multiple movement plans, ¶0046); c) verifies the one or more candidates to select the movement plan for the at least one mover according to a predefined movement task (¶0046); e) executes the determined movement plan(¶0046) Regarding claim 14, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the linear motor simulation and planning method from Wagner that can make and change a movement plan based on a temperature model (¶0056) and create multiple movement models and select a movement model that’s the most optimal as taught by Zehnder (¶0046). This would improve efficiency of the system. Response to Arguments Applicant's arguments filed 9/16/26 have been fully considered but they are not persuasive. Regarding applicant’s arguments pertaining to claims 1-14, applicant argues that Wagner does not teach multiple movement plans, but does concede the fact that Wagner teaches a simulation for checking the design of a transport device against a fixed movement plan. Examiner does agree that Wagner teaches a simulation for checking the design of a transport device against a fixed movement plan, and reconfiguring the device if it fails to meet thermal, electrical or mechanical specifications, this it taught in ¶0056 from Wagner. However, Examiner also agrees that Wagner does not explicitly disclose multiple movement plans, but, from the rejection above, Zehnder teaches multiple movement plans being simulated for a linear transport and optimizing the movement or production based on production and transport time using multiple routes or pans for multiple types of products using a linear motor system (¶0044, ¶0054). As such, examiner is maintaining the rejections of claims 1-2, and 5-14. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Kiendl (US 2021/01162192) – long stator linear motor system Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLES S LAUGHLIN whose telephone number is (571)270-7244. The examiner can normally be reached Monday - Friday. 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, Eduardo Colon-Santana can be reached at 571-272-2060. 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. /C.S.L./Examiner, Art Unit 2837 /KAWING CHAN/Primary Examiner, Art Unit 2837
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Prosecution Timeline

Apr 24, 2024
Application Filed
Jan 02, 2026
Non-Final Rejection mailed — §103
Mar 31, 2026
Response Filed
Jun 17, 2026
Final Rejection mailed — §103
Aug 03, 2026
Response after Non-Final Action
Sep 16, 2026
Request for Continued Examination
Sep 18, 2026
Response after Non-Final Action
Sep 29, 2026
Non-Final Rejection mailed — §103 (current)

Precedent Cases

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

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Prosecution Projections

3-4
Expected OA Rounds
77%
Grant Probability
86%
With Interview (+9.2%)
3y 0m (~6m remaining)
Median Time to Grant
High
PTA Risk
Based on 399 resolved cases by this examiner. Grant probability derived from career allowance rate.

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