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 .
Examiner Remarks
Claims 16-18 are not seen as directed towards a computer program or software as a recording medium is noted to be non-transitory in the specification [Current Application 00161].
Claims 13-15 are still rejected under 101 as software per se as a result of trying to claim a program. A non-transitory element storing the program could be a method of updating claims 13-15, but claims 16-18 already recite a non-transitory storage medium (which means duplicate claims might be created). Modifying or cancelling claims 13-15 to address the current claim rejections is required.
Claim 4 is objected to for the reasons noted in the Claim Objections section. Otherwise, as noted in the Response to Arguments, the applicant’s arguments in regards to 101 (aside from 13-15) or 103 rejections were persuasive.
Two failed attempts to contact the applicant on 09/01/2026 and 09/02/2026 occurred. However, the examiner is open to performing an interview to go over the issues currently present in the application in hopes of addressing them without requiring a further round of prosecution.
Response To Arguments
Remarks page 14, Applicant contends:
Claims are amended to correct the identified objections in claim 1 and 4.
Response:
Claim 1 is acknowledged to be amended to fix the association objection for claim 1. However, claim 4 doesn’t appear to have any amendments to address the objection in claim 4 and no remark appears to argue anything in regards to claim 4. As a result, the claim 1 objection is removed, but the claim 4 objection is maintained.
Remarks page 14-16, Applicant contends:
The currently amended claims satisfy 101.
Response:
The currently amended claims are seen as satisfying 101 requirements for claims except claims 13-15, as the applicant’s arguments of the claims being directed towards an improvement are seen as convincing.
Aspects regarding whether an agreement was reached in the previous action under 101 was addressed in the previous application remarks for page 13 of remarks.
Remarks page 17-25, Applicant contends:
The currently recited claims are allowable under 103.
Response:
The applicant’s arguments regarding the combination not being obvious are persuasive. As a result, the 103 rejections are removed.
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: irregularity-presence-or-absence estimation unit… [Current Application 0091] screening unit… [Current Application 0091] simulation unit… [Current Application 0091] in claim 1.
Claim 2 contains the limitations of acceptance evaluation unit… [Current Application 0091] response data correction unit… [Current Application 0091].
All other claims, excluding claims 5-8 which only depend upon such claims, are claims that recite the above units or recite a combination of such units. Examples include claim 3 which recites simulation unit… [Current Application 0091] acceptance evaluation unit… [Current Application 0091] response data correction unit… [Current Application 0091] , or examples include claim 10 which is analogous to claim 1.
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.
Paragraphs 83-85, and 91 of specification is used as the interpretation of the structure for the units in the claims. [Current application 0091]: “The control unit 72 is a control section that performs various processes for the polishing recipe determination device 70. As illustrated in Fig. 5, the control unit 72 has an irregularity-presence-or-absence estimation unit 72a, the screening unit 72b, a simulation unit 72c, an acceptance evaluation unit 72d, and a response data correction unit 72e. These units may be implemented by a processor in the polishing recipe determination device 70 executing a predetermined program or may be mounted by hardware.”
The units, as noted above, are a part of the polishing recipe determination device 70, which is shown in Figure 5 of the drawings. Paragraph 83 of the specification notes that the polishing recipe determination devices utilizes a bus for transmitting information between the elements ([Current Specification 0083]: “These units are connected to each other being capable of communicating with each other through a bus.”). Paragraph 85 then mentions the storage unit is a hard disk or similar hardware ([Current Specification 0085]: “The storage unit 73 is, for example, a magnetic data storage such as a hard disk. The storage unit 73 stores various items of data handled by the control unit 72. The storage unit 73 stores area response data 73a, a polishing recipe 73b, an actual polishing result 73c, and a simulation polishing result 73d.”). The combination of the teachings of paragraph 91 and paragraphs 83-85 are seen as noting units that could be software or hardware that are implemented in hardware, such as the bus and hard disk.
Claim Objections
Claim 4 is objected to because of the following informalities: claim 4 recites “a machine learning relationship” for both “the first trained model” and “the second trained model”. Claim 1 already recites the “a first trained model” or “a second trained model” “trained on a machine-learning relationship”. This means claim 4 appears to either introduce new machine learning relationships for the models or is trying to redefine or modify the machine learning relationships for the models.
Claim 4, as noted above, can appear to be directed towards replacing/redefining the machine learning relationships noted in claim 1 to include the type of the irregularity. Should that be the interpretation simply updating the “a” in the “a machine learning relationship” to “the” for either relationship in claim 4 might create another objection or possibly a 112 rejection as a result of the confusion on which relationships must be followed to fit the claims (such as whether to use the relationships from claim 1 or the relationships in claim 4).
Another interpretation for the direction of claim 4 can be trying to add an additional training step to use different machine learning relationships. This direction should be updated to recite the additional training step or such to properly indicate that the machine learning relationships in claim 4 are different than that of claim 1, as well as to indicate that claim 1 is not being redefined but instead the relationships being used are being changed.
Appropriate correction from applicant is required.
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 13-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claims are directed towards software per se.
In regards to Claim 13:
Step 1: Is the claim directed towards a process, machine, manufacture, or composition of matter?
No, the claim is directed towards software per se.
Claim 13 recites the following software per se:
A polishing recipe determination program causing a computer to execute a process for determining a polishing recipe based on area response data acquired by changing a pressure for each area in a top ring, the program causing the computer to execute the steps of
The claim limitation directly try to claim a “program” for a computer
As claim 13 is otherwise analogous to claim 1, the other steps are not included for claim 1 is not rejected under 101. Meaning claim 13 is only rejected as a result of trying to claim software.
In regards to Claim 14:
Claim 14 is rejected for the same reason as claim 13, as claim 14 still claims the program (software per se) of claim 13.
In regards to Claim 15:
Step 1: Is the claim directed towards a process, machine, manufacture, or composition of matter?
No, the claim is directed towards software per se.
Claim 15 recites the following software per se
A polishing recipe determination program causing a computer to execute a process for determining a polishing recipe based on area response data acquired by changing a pressure for each area in a top ring, the program causing the computer to execute the steps of
As claim 15 is otherwise analogous to claim 3, the other steps are not included for claim 3 is not rejected under 101. Meaning claim 15 is only rejected as a result of trying to claim software.
Allowable Subject Matter
Claims 1-3, 10-12, 16-18 are allowable.
Claim 4 is objected to. Claim 5 is dependent upon objected claim 4.
Claims 13-15 are rejected under 101, but otherwise contain allowable subject matter and could be allowable if rewritten to satisfy requirements under 101.
The following is an examiner’s statement of reasons for allowance:
The prior art of record teaches relevant information about the claim limitations as noted by the previous office action.
However, the claim 1 in the application is deemed to be directed to a nonobvious improvement over the prior art of record.
The prior art of record teaches limitations as noted in previous office action dated 9 March 2026.
The currently amended claims include subject matter from claims 6-8, such as in claim 1:
Wherein the area response data is data that a variation in an amount of removal by polishing or a variation in a polishing removal rate is divided by a variation in an air bag pressure on positions on a wafer
The above limitation is seen as indicating information related to what Sakurai teaches as noted in the previous office action for claims 6-8.
The currently amended claims also provide further indication of an apparatus or system using the determined recipe:
Wherein the polishing controller is configured to polish the wafer by at least controlling the pressure for each area in the top ring using the determined recipe
The information regarding aspects around the limitation appear to be related to what Dhandapani teaches in paragraph 29 ([Dhandapani 0029]: “The described polishing apparatus has many associated process parameters that control the operation of the polishing apparatus or describe the state of the apparatus or the polishing environment. Process parameters that control the operation of the polishing apparatus (and that can be set, at least initially, by the tool control module 92) (‘control parameters’) include the following: rotation rate of platen 22; rotation rate of carrier head 50; pressure of the chambers [Wherein the polishing controller is configured to polish the wafer by at least controlling the pressure for each area in the top ring using the determined recipe where other aspects of a top ring and polishing of wafers is presented earlier] 52a-52c; and polishing time.”)
The closest prior art of record teaches:
Dhandapani, as noted in the previous office action, has many relevant parts related to the current invention’s claims, but fails to properly teach the claims as recited.
As an example, Dhandapani does not teach the irregularity-presence-or-absence estimation unit as recited, but Dhandapani indicates related elements the use of previous substrates in paragraph 32, the irregularities on the surface of a wafer in paragraph 31, but does not indicate that the there is a machine learning system for detecting the presence of an irregularity (these elements are noted in the previous office action in the section of “Dhandapani does not explicitly teach” for claim 1).
As a result, another reference was utilized to bring in the teachings of the irregularity-presence-or-absence estimation unit. Godbole, as indicated in [Godbole Introduction page 1] and [Godbole Section 7 Conclusions and Future Work page 7], is teaches the indication of using machine learning, such as a neural network, to detect defects or irregularities.
However, Dhandapani also does not explicitly teach the screening unit. Dhandapani, as noted in the previous office action, indicates having a desired thickness profile in paragraph 12 (which is seen as having a desired result without the irregularity present), but Dhandapani does not indicate machine learning is used to estimate new area response data after the removal of the irregularity.
As a result, Bhaskar was utilized as a reference as teaching aspects related to using machine learning to create/estimate data related to data that is absent of irregularity in paragraph 94.
Both Godbole and Bhaskar are indicated to be in related fields of endeavor and to have good motivations for why the elements being taught from them would have been motivated to be used in a combination. However, as brought up in the response from the applicant, aspects of the combination do not appear to be as obvious. While elements of the system/method of the current invention appears to have elements in previous works, the currently recited prior art teaches some of the elements individually and not specifically in combination. For example, Godbole was used to teach the irregularity-presence-or-absence estimation unit and Bhaskar was used to teach the screening unit. Dhandapani was used in the teaching of the simulation unit. While parts of what the units do are taught by these references, the units are intended to work together in the currently recited invention. Thus the aspects of the combination not properly taught by the prior art recited is the interactions between the units that ties what would otherwise be individual elements together.
For example, the irregularity-presence-or-absence estimation unit is intended to act as a trigger for aspects of the screening unit for the data the irregularity-presence-or-absence estimation unit detects as having an irregularity. By teaching the screening unit and the irregularity-presence-or-absence estimation unit in different references separately, this interaction between the units is not obviously taught. Second, the simulation unit noted to be taught by Dhandapani is intended to work with the output of the irregularity-presence-or-absence estimation unit or screening unit, which as those units are not taught by Dhandapani the interaction of using the other units outputs is not inherently obvious.
Smith et al ("Novel Techniques for the Run by Run Process Control of Chemical-Mechanical Polishing") from 1996 indicates teachings for feedback and controllers for wafers. Smith notes utilizing neural networks to find corrected controls in 3.4.2 on page 22, which provides an indication that teachings related to using machine learning to improve systems related to improve polishing for things like polishing controllers (as a polishing controller is noted in the claims) is known in the art. However, Smith does not provide an indication of the units as described in the claims. Smith mentions simulations in section 6.2 but does not appear to indicate the simulation unit as recited. Smith notes CMP or chemical mechanical polishing has elements for correcting drift ([Smith 2.2 page 13]: “Specifically, the process control technique used for CMP must be capable of tracking and correcting linear drifts in removal rate as well as step changes in removal rate due to pad changes.”). Smith later notes that a recipe is generated using predictions ([Smith 3.1 page 16]: “The basic idea of the adaptation is to make a prediction of the offset term at discrete-time n by adding an EWMA of the trend (or slope) in the offset to an EWMA of the value of the offset. This prediction is used with the model to generate the next recipe as in the EWMA controller.”). This means Smith appears to elements related to the screening unit (as Smith notes generating corrections) and the simulation unit (as Smith notes generating a recipe using predictions). However, Smith does not appear to note detecting irregularities in the same way as recited by the claims, as Smith does not note collecting area response data with a top ring. Smith notes aspects related to pressure throughout the document, but doesn’t indicate the pressure is for a top ring and instead appears to be more generically for a polishing apparatus. Smith notes detecting shifts/drifts (4.5 page 39) or irregularities in simulations (in 6.2 page 84, but this appears to be referring to noise as an irregularity). On page 12 in section 2.1 Smith notes aspects to dividing to time or amount removed in regards to removal/removal rate (related to but does not appear to teach “wherein the area response data is data that a variation in an amount of removal by polishing or a variation in a polishing removal rate is divided by a variation in an air bag pressure on positions on a wafer”), but does not appear to indicate dividing by air bag pressure. Thus Smith et al is noted to be relevant art discussing many of the aspects noted in the primary reference, but the specifics on the units and how the units function appear to be outside of what Smith teaches.
RANGANATHAN et al (US 20210301655A1) teaches aspects related to the detection and correction of anomalies in data collected about a tool ([RANGANATHAN 0003]: "Once log data becomes available, an accurate petrophysical analysis thereof includes detection and correction of anomalies. An anomaly in the recorded log data is a measurement or set of measurements that do not conform to the expected tool response in the borehole. This could be caused, for example, by enlarged borehole or erratic borehole wall shape (rugosity) and is a bad hole point. Note that presence of an anomaly is signaled by an outlier value.") and notes the use of machine learning along with steps such as quality assessment ([RANGANATHAN 0004]: "The machine learning, ML, workflow set forth in this article includes: (1) exploratory data analysis, (2) outlier identification, (3) well grouping based on similarity, (4) reconstruction based on prediction and (5) quality assessment."). The elements taught by RANGANATHAN are seen as relevant as the applicant argued an alternative interpretation of the claims to be that anomalous data was being detected and corrected rather than correcting the polishing of a wafer. The aspects of RANGANATHAN are related to but do not necessarily teach an irregularity-presence-or-absence estimation unit (as the primary purpose is detecting anomalies/irregularities) as RANGANATHAN notes detecting anomalous data and the screening unit (as the purpose of the screening unit in the alternative interpretation could be for creating data without the anomaly/irregularity) as RANGANATHAN notes correcting anomalies.
Stine et al (US 20190146032 A1) is relevant as the reference indicates the use of anomalous data detection in wafer processing or production ([0010]: "In one embodiment the trace data for the circuit traces identified as normal circuit traces can be stored into a file or data structure containing the IC chips identified as normal IC chips. The abnormal IC chips can thereafter be segregated or subjected to additional destructive tests to confirm proper functionality. The failure detection data can be new or updated as the system receives new or updated failure detection data over the computer network(s). The machine learning algorithm can then be used to classify the updated data as either normal trace data or abnormal trace data based on comparing it with the trace data for the normal IC chips stored in the file or data structure, which can be used for throughput improvement of the process or burn-in reduction." Where indication of motivation and support for wafers is further provided in paragraph 24), thus providing an indication of teachings in RANGANATHAN having relevance in the current field of endeavor.
RANGANATHAN and Stine do not however appear to make the current invention obvious, as while both references reveal teachings about an alternative interpretation, neither have any indication of being combined with Dhandapani to create the claims as currently recited as RANGANATHAN does not indicate aspects related to creating recipes for wafers to create a connection to the simulation unit recited in the claims. Stine helps by indicating aspects related to wafers, but also does not indicate much information to support combining to have units as recited by the claims.
Thus the current application teaches a method that differs from what is taught in prior art. As a result, the claims in the application are deemed to be directed to a non-obvious improvement over the prior art of record.
Claim 3 is indicated as being allowable for a similar reason as claim 1. Claim 3 recites a polishing controller, simulation unit, acceptance evaluation unit, and a response data correction unit. Aspects related to the teachings are taught by prior art as indicated in previous office action or related material above. Related aspects from Dhandapani are noted in the previous office as well. Claim 3 is non-obvious for reason of while numerous aspects appear recited in prior art, the combination as recited is non-obvious. The units within the claims perform limitations that require connections to the other units. As a result, the teachings of the units individually, even with a motivation to have the individual element, does not appear to make the whole invention obvious as the combination introduces elements that would not be obviously taught. Emami-Naeini notes aspects of the units as described in claim 3 and relevant pieces are noted from Dhandapani (as indicated in previous office action rejection for claim 3 and claim 2), but the combination as particularly described in the claims does not appear obvious. Emami-Naeini appears to indicate the elements related to the looping for correcting (given further support in the run to run control idea present in Emani-Naeini III Control of Semiconductor Processes page 5), but aspects for the acceptance evaluation unit as taught in Emani-Naeini does not appear to connect to elements such as the response data correction unit, for Emani-Naeini doesn’t appear to recite aspects for the acceptance evaluation unit decision being used in a response data correction unit. Meaning while Emani-Naeini indicates aspects of the units, the combination of the units is not properly taught. Emani-Naeini also does not indicate the use of area response data as input data, which makes the combination with Dhandapani to try and teach the current claims less obvious.
Independent claims 1 and analogous (10, 13, 16) contain allowable subject matter for the reasons cited for claim 1. The remaining claims are allowable because they depend on one of the allowable independent claims.
Independent claims 3 and analogous (12, 15, 18) contain allowable subject matter for the reasons cited for claim 3. The remaining claims are allowable because they depend on one of the allowable independent claims.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Su et al (US 20200356011 A1) is considered relevant art as Su et al notes a process that involves something similar to simulating a result and having a machine learning model perform corrections on the result.
Shanmugasundram et al (US 20020197745 A1) is considered relevant art as Shanmugasundram et al notes the manipulation of a wafer during processing where a polishing recipe is determined for the wafer.
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 CHRISTOPHER D DEVORE whose telephone number is (703)756-1234. The examiner can normally be reached Monday-Friday 7:30 am - 5 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michael J Huntley can be reached at (303) 297-4307. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/C.D.D./Examiner, Art Unit 2129
/HAL SCHNEE/Primary Examiner, Art Unit 2129
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