Prosecution Insights
Last updated: April 18, 2026
Application No. 18/762,487

PRESS MACHINE AND METHOD FOR DETECTING ABNORMALITY IN PRESS MACHINE

Non-Final OA §102§103§112
Filed
Jul 02, 2024
Examiner
LEYSON, JOSEPH S
Art Unit
1744
Tech Center
1700 — Chemical & Materials Engineering
Assignee
Aida Engineering Ltd.
OA Round
1 (Non-Final)
66%
Grant Probability
Favorable
1-2
OA Rounds
3y 1m
To Grant
99%
With Interview

Examiner Intelligence

Grants 66% — above average
66%
Career Allow Rate
485 granted / 738 resolved
+0.7% vs TC avg
Strong +36% interview lift
Without
With
+36.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
32 currently pending
Career history
770
Total Applications
across all art units

Statute-Specific Performance

§101
0.1%
-39.9% vs TC avg
§103
42.0%
+2.0% vs TC avg
§102
16.6%
-23.4% vs TC avg
§112
31.5%
-8.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 738 resolved cases

Office Action

§102 §103 §112
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 § 112 Claims 1-5 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. Claims 1-5 are replete with antecedent basis issues. The Examiner suggests the following amendments: (Currently amended) A press machine comprising: a detection unit that detects a load value during a press process on a material to be processed; a storage unit that stores the load value detected by the detection unit in association with identification information of a mold attached to the press machine during detection of the load value; a calculation unit that calculates a position of a load center acting on the press machine based on the stored load value, calculates the position of the load center as an eccentric amount from a center of the press machine to obtain an eccentric load, and generates distribution data of the eccentric load for each mold; a determination unit that determines an abnormality based on the eccentric load obtained on the basis of the load value detected by the detection unit and the distribution data of the eccentric load corresponding to the mold attached to the press machine during the detection of the load value; and a notification unit that notifies [[an]] the abnormality based on a determination result of the determination unit. (Currently amended) The press machine according to claim 1, wherein in the calculation unit, a plurality of eccentric load data arbitrarily selected by a user among an eccentric load data group corresponding to the same mold is defined as the distribution data of the eccentric load corresponding to the mold. (Currently amended) The press machine according to claim 2, further comprising a display control unit that causes a display unit to display an image in which [[an]] the eccentric load data group corresponding to the same mold is plotted. (Currently amended) The press machine according to claim 3, wherein the display control unit causes the display unit to display waveform data of a load value corresponding to the eccentric load data arbitrarily selected by [[a]] the user among the data group displayed on the display unit. An abnormality detection method for a press machine comprising: a detection step of detecting a load value during a press process on a material to be processed; a storage step of storing the load value detected in the detection step in association with identification information of a mold attached to the press machine during detection of the load value; a calculation step of calculating a position of a load center acting on the press machine based on the stored load value, calculating the position of the load center as an eccentric amount from a center of the press machine to obtain an eccentric load, and generating distribution data of the eccentric load for each mold; a determination step of determining an abnormality based on the eccentric load obtained on the basis of the load value detected in the detection step and the distribution data of the eccentric load corresponding to the mold attached to the press machine during the detection of the load value; and a notification step of notifying [[an]] the abnormality based on a determination result of the determination step. For further examination purposes, the scope of the claims are read in light of the suggested Examiner amendments. 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 and 5 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kurokawa (US 2018/0072010). (Claims 1, 5) Kurokawa (US 2018/0072010) teaches a press machine (fig. 1) and an abnormality detection method comprising: a detection unit 44 that detects a load value during a press process on a material to be processed [0047]; a storage unit 50 that stores the load value detected by the detection unit in association with identification information of a mold attached to the press machine during detection of the load value ([0045], the detected load value for the mold 22 being used in the press machine is stored in memory 50 which is an appropriate storage medium; the stored detected load values are later used in calculations); a calculation unit 46 that calculates a position of a load center acting on the press machine based on the stored load value, calculates the position of the load center as an eccentric amount from a center of the press machine to obtain an eccentric load, and generates distribution data of the eccentric load for each mold (fig. 5; [0048], [0050], [0063]-[0068], calculates a position of a load center based on the stored load value as an eccentric amount “e” from a center of the press machine (fig. 5) to obtain an amount of eccentricity of the slide 30, eccentric load P can therefore be calculated in accordance with the listed expressions; allowable values (distribution data) of the press load based on the amount of eccentricity (i.e., allowable eccentric loads) are calculated (generated) using a table [0050]); a determination unit 44 that determines an abnormality based on the eccentric load obtained on the basis of the load value detected by the detection unit and the distribution data of the eccentric load (allowable eccentric loads) corresponding to the mold attached to the press machine during the detection of the load value (figs. 1-2; [0049]-[0050], [0069]); a notification unit 45 that notifies the abnormality based on a determination result of the determination unit [0051-[0052]. 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) 2-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kurokawa (US 2018/0072010) in view of JP 2020-192577. Kurokawa (US 2018/0072010) disclose the press machine substantially as claimed, as mentioned above, except for the limitations of claims 2-4. JP 2020-192577 discloses a press machine comprising: a detection unit that detects a load value during a press process on a material to be processed [0018], [0026]; a storage unit 52 that stores the load value detected by the detection unit in association with identification information of a mold attached to the press machine during detection of the load value (fig. 1; [0022], [0026]; load values are associated to the used mold 31); a calculation unit that calculates load characteristics (load increase rate, load increase change) based on the stored load value, and generates distribution data of the load characteristics for each mold ([0027]-[0028], generates distribution data of the load characteristics (upper and lower thresholds for normal (allowable) operation) through test operations; the thresholds may be obtained by simulation (i.e., calculation) or actual measurements (i.e., test operations of the press machine)); a determination unit that determines an abnormality based on the load characteristics obtained on the basis of the load value detected by the detection unit and the distribution data of the load characteristics corresponding to the mold attached to the press machine during the detection of the load value ([0029]-[0031]; the load characteristics and the distribution data (predetermined upper and lower thresholds) are compared to determine if an abnormality is present); and a notification unit 51 that notifies the abnormality based on a determination result of the determination unit [0031]. Thus, JP 2020-192577 discloses generating distribution data including upper and lower thresholds for allowable load characteristics. The upper and lower thresholds define an allowable load characteristic data group corresponding to the same mold. As mentioned above, Kurokawa (US 2018/0072010) generating distribution data (allowable eccentric loads). It would have been obvious to one of ordinary skill in the art, at the time the invention was made, to modify the distribution data to include upper and lower thresholds, as disclosed by JP 2020-192577, because such a modification is known in the art and would enable the distribution data to include upper and lower thresholds for the allowable eccentric loads. It would have been further obvious to modify the press machine wherein in the calculation unit (where the distribution data is generated), a plurality of eccentric load data arbitrarily selected by a user among an eccentric load data group corresponding to the same mold is defined as the distribution data of the eccentric load corresponding to the mold. In other words, given the upper and lower thresholds, it would have been further obvious for a user to arbitrarily select a plurality of allowable eccentric load data (particular allowable eccentric loads within the upper and lower thresholds) among an allowable eccentric load data group (all the allowable eccentric loads between the upper and lower thresholds) to be used as the distribution data, with a reasonable expectation of success given that the selected allowable eccentric load data would still be within the upper and lower thresholds. As to claims 3-4, JP 2020-192577 further disclose a display control unit that causes a display unit to display an image in which a load characteristic data group corresponding to the same mold is plotted, wherein the display control unit causes the display unit to display waveform data of a load value corresponding to the load characteristic data (figs. 4-10; [0005], [0021], [0028]; the display unit 54 displays various information, the load characteristics to the same mold are plotted as waveform data as disclosed [0005], [0028] and shown in figs. 4-10). Thus, it would have been further obvious to modify the press machine to further comprise a display control unit that causes a display unit to display an image in which the eccentric load data group (load characteristics) corresponding to the same mold is plotted, wherein the display control unit causes the display unit to display waveform data of a load value corresponding to the eccentric load data (load characteristics), as disclosed by JP 2020-192577, because such a modification is known in the art and would provide an alternative configuration capable of data analysis. As mentioned above, since it would have been obvious to arbitrarily select particular load data among the data group (all the load data within the upper and lower thresholds) to use as the distribution data and since displaying waveform load data is known in the art, it would have been further obvious to display waveform data of a load value corresponding to data arbitrarily selected by the user among the data group to be displayed on the display unit. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Harrison et al. (US 3,161,044) and Spiesshofer (US 2015/0047517) disclose compensating for eccentric loads. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEPH S LEYSON whose telephone number is (571)272-5061. The examiner can normally be reached M-F 8am-4:30pm. 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, Sam Xiao Zhao can be reached at 5712705343. 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. /J.S.L/Examiner, Art Unit 1744 /XIAO S ZHAO/Supervisory Patent Examiner, Art Unit 1744
Read full office action

Prosecution Timeline

Jul 02, 2024
Application Filed
Mar 26, 2026
Non-Final Rejection — §102, §103, §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12600073
Apparatus For Adjusting The Thickness of a Resin Film Exiting an Extrusion Lip of a Blown Film Extruder
2y 5m to grant Granted Apr 14, 2026
Patent 12594707
PVC FLOORING PRODUCTION LINE
2y 5m to grant Granted Apr 07, 2026
Patent 12571130
METHODS AND APPARATUSES FOR FORMING PATTERNED FIBER ARRAYS WITH AUTOMATED TRACKS
2y 5m to grant Granted Mar 10, 2026
Patent 12537118
Striped Cable and Process and Apparatus for Making Same
2y 5m to grant Granted Jan 27, 2026
Patent 12535272
CONSTRUCTION METHOD OF FIBER LINING SURFACE OF ETHYLENE CRACKING FURNACE
2y 5m to grant Granted Jan 27, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

1-2
Expected OA Rounds
66%
Grant Probability
99%
With Interview (+36.5%)
3y 1m
Median Time to Grant
Low
PTA Risk
Based on 738 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month