Prosecution Insights
Last updated: April 19, 2026
Application No. 18/528,033

METHOD AND APPARATUS FOR EVALUATING HEALTH OF VEHICLE CHASSIS

Non-Final OA §102§103§112
Filed
Dec 04, 2023
Examiner
MARINI, MATTHEW G
Art Unit
2853
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
SKF (China) Co. Ltd.
OA Round
1 (Non-Final)
60%
Grant Probability
Moderate
1-2
OA Rounds
3y 6m
To Grant
82%
With Interview

Examiner Intelligence

Grants 60% of resolved cases
60%
Career Allow Rate
641 granted / 1060 resolved
-7.5% vs TC avg
Strong +21% interview lift
Without
With
+21.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 6m
Avg Prosecution
68 currently pending
Career history
1128
Total Applications
across all art units

Statute-Specific Performance

§101
13.1%
-26.9% vs TC avg
§103
45.2%
+5.2% vs TC avg
§102
28.0%
-12.0% vs TC avg
§112
11.3%
-28.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1060 resolved cases

Office Action

§102 §103 §112
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. Claim Objections Claim s 1 -3, 5 and 13 are objected to because of the following informalities: With respect to claim 1, line 2, “the wheel end and the reducer” lacks proper antecedent basis. Appropriate correction is required. With respect to claim 2, line 4 , “the fusion of data” lacks antecedent basis. Appropriate correction is required. Claim 3, line 15 there appears to be a missing “the” before chassis. Appropriate correction is required. Claim 5, line 2, there appears to be a missing “the” or “a” before reducer. Appropriate correction is required. Further, in line 6, “and” appear s to be missing before “gear teeth wear”. Claim 13, line 3 “the reducer” lacks proper antecedent basis. Claim Interpretation The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph: (A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function; (B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and (C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: a control unit in claim 13, with corresponding structure found in [00 75-0082 ] performing the claimed computer-implemented means-plus-function . Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b ) CONCLUSION.— The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the appl icant regards as his invention. Claim s 2-11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. With repect to claim 2 , the recite d “based on the fusion of the monitored vibration of at least one of the wheel end and the reducer and the monitoring data monitored by at least one other sensor” is unclear. What and when is a fusion of data occurring in the method? Is than an active step performed and by what? In addition, “the monitoring data” lacks antecedent basis and further renders the claim unclear. What is this monitoring data? Clarification is required. Claim 5 recites “detecting faults of reducer” and because the limitation lacks proper antecedent basis, it ’s unclear to the examiner if the claim intents to introduce, positively, a step of detecting faults of the reducer or a reducer. If applicant intented the , claim 5 does not further define the examiner elected alternative seen in the rejection below. However, if applicant intended a , then the claim recites a positively recited limitation. Clarification is required. To further, prosecution , the examiner has interpreted the claim as --the reducer--. Claim 12 recites “ receiving the early fault of the chassis and estimated the remaining useful lifetime of the chassis from the server .” The lack of proper antecedent basis creates confusion. The examiner is unsure what is estimating the remaining useful lifetime of the chassis and how; what are the metes and bounds of this estimation? What is the data or process involved? The examiner is unsure how the limitation further limits the method. Clarification is required. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis ( i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale , or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1 -11 and 13 is/are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Koons et al. (2017/0358151) . With respect to claim 1, Koons et al. teaches a method for health evaluation of vehicle chassis (Koons et al. teaches using system 150 to detect conditions of a chassis[ [0022]) comprising: monitoring the vibration of the wheel end by a vibration sensor (as Koon et al. teaches a subset of sensors 120 include vibration sensors, [0020], [0049] for the purpose of monitoring chassis vibrations; [0022]) wherein the vibration sensor (i.e. the subset of sensors 120; [0022], [0049]) is installed in the wheel end wheel locations (as Koon et al. discloses the subset being installed at the wheels locations and their respective suspension components; [0029], [0049]) for the purpose of monitoring (i.e. as the sensor and their respective subsets are positioned to sense vibrations occurring within the vehicle and its components during operation) ; based on the monitored vibration (via the sensors 120) of at least one of the wheel end [0022],[0049] , performing the health evaluation of the vehicle chassis (via the health check system 150) . With respect to claim 2, Koons et al. teaches the method wherein based on the monitored vibration of the wheel end (using the disclosed subset of sensors 120) , performing the health evaluation of the vehicle chassis (via system 150) further comprises: based on the fusion of the monitored vibration of the wheel end (via the subset of sensor 120) and the monitoring data monitored by at least one other sensor (i.e. another subset of sensors, as Koon et al. teaches in [0049] the disclosed method takes data from multiple sensors, aggregates them by location, and used that combined dataset to from a higher-level conclusion about the health) , performing the health evaluation of the vehicle chassis (using the aggregated data) , wherein the health evaluation includes anomaly detection and/or fault diagnosis (as the aggregated data used by the health system 150 aids in determining chassis issues; [0022], [0055]) . With respect to claim 3, Koons et al. teaches the method wherein the monitoring data monitored by the at least one other sensor includes abnormal sound (as Koon et al. teaches using microphones for detecting sound; [0017]) of other mechanical parts (like suspension or bushing components) of chassis monitored by an acoustic sensor (i.e. microphone) installed on the wheel end and/or the reducer (as Koon et al. teaches in [0021], the microphones are capable of being mounted at a gearbox or at the suspension of a wheel of the vehicle) . With respect to claim 4, because the claim does not further define the examiner elected alternative of claim 3 . Therefore, claim 4 does not further distinguish the invention over the prior art . With respect to claim 5 , because and in light of the above 112(b) rejection, the claim does not further define the examiner elected alternative of claim 3 . Therefore, claim 5 does not further distinguish the invention over the prior art . With respect to claim 6, Koons et al. teaches the method wherein the health evaluation comprises detecting mechanical faults based on the fusion of monitoring data of the vibration sensor (i.e. the subset of sensors 120 tasked to measured vibrations ; [0025] ) and the at least one other sensor (i.e. microphone ; [0021] ) , wherein the at least one other sensor (microphone) comprises the acoustic sensor and the speed sensor (i.e. as the speed is taught to be measured and recorded; see claim 17 of Koons et al.) wherein the mechanical faults include screw loosening and abnormal chassis resonator (as the taught sensors and health system 150 is capable of sensing any data that represents a screw loosening and an abnormal chassis resonator; insofar as how the evaluation is structurally defined to distinguish these faults) . With respect to claim 7, Koons et al. teaches the method wherein the fusion (i.e. the aggregated sensor data; [0049]) comprises assigning weights to the monitoring data of the vibration sensor and the at least one other sensor (as although paragraph [0049] does not explicitly teaches “assigning weights”, Koons et al. teaches comparing the sensor data with predetermined threshold data; the use of thresholds implies that sensor readings are weighted against known "good" or "bad" values by prioritizing specific data points, either vibrations or noise, over others to determine details of the health of the mechanical assemblies on the vehicle). With respect to claim s 8 and 10 , Koons et al. teaches the method wherein the fusion [0049] comprises, based on the monitoring data of the at least one other sensor (i.e. microphone) , adjusting the result of health evaluation of the vehicle chassis performed based on the monitored vibration of the wheel en d (as by using both sets of data, the health system 150 can adjust the results of the analysis by removing data that is wrongly classified or if the data is acceptable for the vehicle; [0054] ) . With respect to claim 9 , Koons et al. teaches the method wherein the fusion [0049] comprises assigning weights to the monitoring data of the vibration sensor (i.e. the subset of sensors tasked to sense vibrations) and the at least one other sensor ( microphone; as although paragraph [0049] does not explicitly teaches “assigning weights”, Koons et al. teaches comparing the sensor data with predetermined threshold data; the use of thresholds implies that sensor readings are weighted against known "good" or "bad" values by prioritizing specific data points, either vibrations or noise, over others to determine details of the health of the mechanical assemblies on the vehicle). With respect to claim 1 1 , Koons et al. teaches the method wherein the anomaly detection and/or the fault diagnosis are performed by an algorithm including a combination of a classical mechanism model (as Koons et al. teaches in [0042] a system that accesses “predetermined performance data” which is used for rule-based diagnosis, thereby reading on the claimed invention) . With respect to claim 13, Koons et al. teaches a n apparatus (Fig. 2) for health evaluation of vehicle chassis [0022] comprising: a vibration sensor (a subset of sensors 120, [0020]) configured to monitor vibration of the wheel end (as Koons et al. teach the vibration sensors being located at the wheel end of a vehicles suspension system; [0029], [0049]) , wherein the vibration sensor (the subsets of 120) is installed in the wheel end [0029, 0049] ; and a control unit (150) configured to perform health evaluation on the vehicle chassis based on the monitored vibration of the wheel end [0018], [0025] . Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis ( i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 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) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Koons et al. (2017/0358151) in view of Westlund et al. (2020/0363296) . With respect to claim 12, Koons et al. teaches the method wherein the health evaluation comprises: uploading data to be evaluated for health evaluation of the vehicle chassis to a server (Koons et al. teaches the health system tasked to perform the health evaluation is located on a server; [0017]) , wherein the data to be evaluated is associated with monitoring data of the vibration sensor (i.e. the data collected by the subset of sensors on the vehicle sensing vibrations) ; receiving the early fault of the chassis and estimated the remaining useful lifetime of the chassis from the server (as Koons et al. teaches receiving early fault data that indicates a specific service requirement; [0048], indicating a notification prior to a fault that incapacitates the vehicle). Koons et al. remains silent regarding the early fault of the chassis and estimated the remaining useful lifetime of the chassis are performed by an algorithm driven by big data and a machine learning model and based on the data to be evaluated. Westlund et al. teaches a similar method that includes estimated a remaining useful lifetime of the chassis ( Wes t lund et al. teaches a trained classifier used to determine data with respect to a chassis of vehicle; [0335] and alerting a user service is required prior to failure; [0039] or stopping the vehicle is the severity is high [0041], thereby reading of a remaining useful life, in light of the above 112(b) rejection ) are performed by an algorithm driven by big data ( Westlund et al. teaches aggregating fleet data; [0040]) and a machine learning model and based on the data to be evaluated. It would have been obvious to one of ordinary skill in the art before the effective filing of the instant invention to modify the model taught in Koons et al. to include the ML model, trained on bi g data from a fleet, as taught by Westlund et al. because Westlund et al. teaches such a modification improve s the system’s ability to distinguish false positives; thereby reducing unnecessary and costly repairs, [0003]. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Dingli et al. (11,568,687) teaches detecting damage in a vehicle using vibrational characteristics . Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT MATTHEW G MARINI whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)272-2676 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT Monday-Friday 8am-5pm . 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, FILLIN "SPE Name?" \* MERGEFORMAT Stephen Meier can be reached at FILLIN "SPE Phone?" \* MERGEFORMAT 571-272-2149 . 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. /MATTHEW G MARINI/ Primary Examiner, Art Unit 2853
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Prosecution Timeline

Dec 04, 2023
Application Filed
Mar 20, 2026
Non-Final Rejection — §102, §103, §112 (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

1-2
Expected OA Rounds
60%
Grant Probability
82%
With Interview (+21.2%)
3y 6m
Median Time to Grant
Low
PTA Risk
Based on 1060 resolved cases by this examiner. Grant probability derived from career allow rate.

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