DETAILED ACTION
Amendment received 13 January 2026 are pending and have been considered as follows. Claims 1-10 are pending and have been considered as follows.
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:
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;
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
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 limitations use 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 limitations are: “storage device that stores” in Claim 1; “communication device configured to receive” in Claim 1; and “processing unit configured to create” in Claim 1.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they 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 these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid 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 limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 4-8, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Ueda (US Pub. No. 2018/0354125) in view of Sciog (US Pub. No. 2019/0030712).
As per Claim 1, Ueda discloses a robot data processing server (120) (Fig. 8; ¶14, 86-89) comprising:
a storage device (102, 103, 104) that stores operation result data (as per 106, 108) including plural sets of data (S1, S2, …; D1, D2, …), each set (S1, S2, …; D1, D2, …) of which includes an operation program (as per “decision making section 122 generates and outputs a command value C” in ¶78) for an industrial robot (160’) and operations (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that moves the axis of the robot” in ¶31) of the robot (160’) responding to the operation program (as per “decision making section 122 generates and outputs a command value C” in ¶78) from one time (as per “the previous learning cycle” in ¶42) or another (as per “a current learning cycle” in ¶42) (Figs. 1-2, 6, 8; ¶27-45, 75-82, 86-89);
a communication device (21, 20, 19, 172) configured to receive an operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) by communicating with an external device (60) via a wide area network (172), the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) being the operation program (as per “controller 1 performs the compensation or the like of a command for controlling the robot based on a program or teaching data” in ¶32) created in the external device (60) (Figs. 1, 8; ¶27-32, 86-89), and
a processing unit (101) configured to create trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) based on the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) received by the communication device (21, 20, 19, 172) and the operation result data (as per 106, 108) stored in the storage device (102, 103, 104), wherein the trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) indicates operations of the robot (160’) for the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) (Figs. 1-2, 6, 8; ¶27-45, 75-82, 86-89).
Ueda does not expressly disclose:
wherein the communication device further receives additional information including a weight of a workpiece that is a working object of the robot; and
wherein the processing unit is configured to create trajectory data based on the weight of the workpiece.
Sciog discloses a picking system (300) that includes an identification station (302), a picking station (306), and a robotic manipulator (308) (Fig. 4; ¶38). The identification station (302) is configured for identifying an article (¶38). The picking station (306) is reachable with the robotic manipulator (308) (¶38). The robotic manipulator (308) is configured for picking the article from the picking station (306) (¶38). Once the article is identified by the identification station (302), a record containing data about the identified article is retrieved from a memory of a database, the information including: weight; a location of a center of gravity; and a point cloud describing the orientation of the article (Figs. 4-5; ¶38-40). The picking system (300) then determines an appropriate picking location of the article based on the information (Figs. 4-5; ¶40-41). In this way, the system reduces inefficiencies in handling an article (¶21-22, 41). Like Ueda, Sciog is concerned with robot control systems.
Therefore, from these teachings of Ueda and Sciog, one of ordinary skill in the art before the effective filing date would have found it obvious to apply the teachings of Sciog to the system of Ueda since doing so would enhance the system by reducing inefficiencies. Applying the teachings of Sciog to the system of Ueda would result in a system that operates:
“wherein the communication device further receives additional information including a weight of a workpiece that is a working object of the robot” in that the system of Ueda would receive data as per Sciog; and
“wherein the processing unit is configured to create trajectory data based on the weight of the workpiece” in that operation of the system of Ueda would be informed by data as per Sciog.
As per Claim 4, the combination of Ueda and Sciog teaches or suggests all limitations of Claim 1. Ueda further discloses wherein data (as per “teaching data input from the teach pendant 60” in ¶29) that the communication device (21, 20, 19, 172) receives from the external device (60) are a part of data (as per “A random-access memory (RAM) 13 stores temporary calculation data or display data and various data or the like input by an operator via a teach pendant 60” in ¶28; as per “The teach pendant 60 receives information from the controller 1 via the interface 19 to display the same” in ¶30) stored in the external device (60), the part excluding three-dimensional data and including text data (as per “a hardware key” in ¶30) (Figs. 1, 8; ¶27-32, 86-89).
As per Claim 5, the combination of Ueda and Sciog teaches or suggests all limitations of Claim 1. Ueda further discloses the processing unit (101) uses a trajectory creation model (as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) to create the trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) for the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29), the trajectory creation model (as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) being built through machine-learning (as per 120) of the operation result data (as per 106, 108) (Figs. 1, 6, 8; ¶27-32, 75-82, 86-89).
As per Claim 6, the combination of Ueda and Sciog teaches or suggests all limitations of Claim 1. Ueda further discloses wherein the communication device (21, 20, 19, 172) transmits (as per “The teach pendant 60 receives information from the controller 1 via the interface 19 to display the same” in ¶30) to the external device (60) the trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) created by the processing unit (101) (Figs. 1, 6, 8; ¶27-32, 75-82, 86-89).
As per Claim 7, the combination of Ueda and Sciog teaches or suggests all limitations of Claim 1. Ueda further discloses wherein the processing unit (101) evaluates the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) based on the trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) for the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29), and creates a modification program (as per SA04, SA06) obtained by modifying the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) such that the modification program (as per SA04, SA06) has a higher evaluation (as per SA05) than that of the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29), and the communication device (21, 20, 19, 172) transmits to the external device (60) the modification program (as per SA04, SA06) created by the processing unit (10) (Figs. 1-2, 4, 6, 8; ¶27-45, 62-63, 75-82, 86-89).
As per Claim 8, the combination of Ueda and Sciog teaches or suggests all limitations of Claim 7. Ueda further discloses wherein the processing unit (101) repeats (as per “By repeatedly performing such a learning cycle” in ¶43) a process of creating the modification program (as per SA04, SA06) and evaluating the trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77), and the communication device (21, 20, 19, 172) transmits to the external device (60) the modification program (as per SA04, SA06) for which the trajectory data satisfies (as per NO at SA08) an evaluation criterion (as per SA08) (Figs. 1-2, 4, 6, 8; ¶27-45, 62-63, 75-82, 86-89).
As per Claim 10, Ueda discloses a method for calculating trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) for an industrial robot (as per “industrial robot” in ¶28; 160’) (Figs. 1-2, 6; ¶27-50, 75-82), the method comprising:
receiving an operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) by communicating with an external device (60) via a wide area network (172), the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) being an operation program (as per “controller 1 performs the compensation or the like of a command for controlling the robot based on a program or teaching data” in ¶32) created in the external device (60) (Figs. 1, 8; ¶27-32, 86-89); and
creating trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) based on the received operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) and operation result data (as per 106, 108) including plural sets of data (S1, S2, …; D1, D2, …), each set (S1, S2, …; D1, D2, …) of which includes an operation program (as per “decision making section 122 generates and outputs a command value C” in ¶78) for the robot (160’) and operations (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that moves the axis of the robot” in ¶31) of the robot (160’) responding to the operation program (as per “decision making section 122 generates and outputs a command value C” in ¶78) from one time (as per “the previous learning cycle” in ¶42) to another (as per “a current learning cycle” in ¶42), the trajectory data (as per “Upon receiving the command, the servo amplifier 40 drives a servo motor 50 that drives the axis of the robot” in ¶31; as per “The machine learning device 120 of the controller 2 includes … software … and hardware … for outputting the learned compensation amount of the teaching position in the control of the robot according to the teaching position included in the teaching data of the robot as a command for the controller 2” in ¶77) indicating operations of the robot (160’) for the operation verification program (as per “teaching data input from the teach pendant 60” in ¶29) (Figs. 1-2, 6, 8; ¶27-45, 75-82, 86-89).
Ueda does not expressly disclose:
receiving additional information including a weight of a workpiece that is a working object of the robot; and
wherein creating trajectory data is based on the weight of the workpiece.
See rejection of Claim 1 for discussion of teachings of Sciog.
Therefore, from these teachings of Ueda and Sciog, one of ordinary skill in the art before the effective filing date would have found it obvious to apply the teachings of Sciog to the system of Ueda since doing so would enhance the system by reducing inefficiencies. Applying the teachings of Sciog to the system of Ueda would result in a system that operates:
by “receiving additional information including a weight of a workpiece that is a working object of the robot” in that the system of Ueda would receive data as per Sciog; and
“wherein creating trajectory data is based on the weight of the workpiece” in that operation of the system of Ueda would be informed by data as per Sciog.
Claims 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Ueda (US Pub. No. 2018/0354125) in view of Sciog (US Pub. No. 2019/0030712), further in view of Kobayashi (US Pub. No. 2020/0338740).
As per Claim 2, the combination of Ueda and Sciog teaches or suggests all limitations of Claim 1. Ueda does not expressly disclose wherein the additional information is information not included in the operation verification program and being information necessary to create the trajectory data.
See rejection of Claim 1 for discussion of teachings of Sciog.
Kobayashi discloses a robot system (10) that includes three robots (6, 7, 8), a control device (15), and a teaching device (19) (Fig. 1; ¶43-50). The teaching device (19) includes a storing section for teaching (28) that stores a program for teaching (35) in which a teaching procedure for operation data (37) is described and identification act data (36) for indicating an identification act of identifying the robot of the three robots (6, 7, 8) (Fig. 2; ¶53-59). The teaching device (19) further includes a display section (23) to display various kinds of information for operating the robots (6, 7, 8) (Fig. 1; ¶50-51). The display section (23) displays the identification act data (36) that includes data of a robot name and model of a robot (Fig. 3; ¶74-78). The display section (23) also displays operation data (37) that includes point data that describes locations for moving a specified robot (6, 7, 8) (Fig. 5; ¶82-85). In this way, the operator can confirm transmission of data to a target robot (¶123-134). Like Ueda, Kobayashi is concerned with robot control systems.
Therefore, from these teachings of Ueda, Sciog, and Kobayashi, one of ordinary skill in the art before the effective filing date would have found it obvious to apply the teachings of Sciog and Kobayashi to the system of Ueda since doing so would enhance the system by: reducing inefficiencies; and facilitating the transmission of data to a target robot. Applying the teachings of Sciog and Kobayashi to the system of Ueda would result in a system that operates “wherein the additional information is information not included in the operation verification program and being information necessary to create the trajectory data” in that the pendant (60) of Ueda would be adapted to include and transmit data as per Kobayashi.
As per Claim 3, the combination of Ueda, Sciog, and Kobayashi teaches or suggests all limitations of Claim 2. Ueda does not expressly disclose wherein the additional information includes at least one of a model type of the robot and a kind of work tool used by the robot.
See rejection of Claim 1 for discussion of teachings of Sciog.
See rejection of Claim 2 for discussion of teachings of Kobayashi.
Therefore, from these teachings of Ueda, Sciog, and Kobayashi, one of ordinary skill in the art before the effective filing date would have found it obvious to apply the teachings of Sciog and Kobayashi to the system of Ueda since doing so would enhance the system by: reducing inefficiencies; and facilitating the transmission of data to a target robot. Applying the teachings of Sciog and Kobayashi to the system of Ueda would result in a system that operates “wherein the additional information includes at least one of a model type of the robot and a kind of work tool used by the robot” in that the pendant (60) of Ueda would be adapted to include and transmit data as per Kobayashi.
Claim 9 rejected under 35 U.S.C. 103 as being unpatentable over Ueda (US Pub. No. 2018/0354125) in view of Sciog (US Pub. No. 2019/0030712), further in view of Arita (US Pub. No. 2017/0248941).
As per Claim 9, the combination of Ueda and Sciog teaches or suggests all limitations of Claim 1. Ueda does not expressly disclose wherein the communication device communicates via the Internet with the external devices disposed in plural facilities, respectively.
See rejection of Claim 1 for discussion of teachings of Sciog.
Arita discloses a production system (10) that includes at least one manufacturing cell (11), a cell controller (12), and a host computer (13) (Fig. 1; ¶30-32). The manufacturing cell (11) is a group of manufacturing machines (16-1, 16-2, … 16-n) in the form of industrial robots (23) (Figs. 1-2A; ¶30-34, 52-55). The manufacturing cell (11) is installed in a factory for manufacturing products whereas the cell controller (12) and host computer (13) are located in a different building from the factory (¶31). In one embodiment, the host computer (13) is located in an office remote from the factory such that the cell controller (12) and host computer (13) are connected to each other via a communication device (15) in the form of an internet network (¶32). In this way, the system facilitates production planning (¶32, 35). Like Ueda, Arita is concerned with robot control systems.
Therefore, from these teachings of Ueda, Sciog, and Arita, one of ordinary skill in the art before the effective filing date would have found it obvious to apply the teachings of Sciog and Arita to the system of since doing so would enhance the system by: reducing inefficiencies; and facilitating production planning. Applying the teachings of Sciog and Arita to the system of Ueda would result in a system that operates “wherein the communication device communicates via the Internet with the external devices disposed in plural facilities, respectively” in that the system of Ueda would be adapted to include production planning via the system of Arita.
Response to Arguments
Applicant's arguments filed 13 January 2026 have been fully considered as follows.
Applicant does not address the statement of claim interpretation under 35 USC 112(f). Accordingly, claim interpretation under 35 USC 112(f) is maintained as indicated above.
Applicant argues rejections under 35 USC 112(b) should not be maintained in view of the amendments (page 5 of Amendment). This argument is persuasive. Therefore, these rejections are not maintained.
Applicant argues that rejections under 35 USC 102 should not be maintained in view of the amendments (page 5-6 of Amendment). Upon further consideration of the teachings of Ueda in view of the amended claim language, rejections under 35 USC 102 are not maintained. However, the amendments necessitated the new ground(s) of rejection presented above.
Applicant argues that rejections of Claim 1 and 10 under 35 USC 103 in view of Ueda and Kobayashi would not be proper in view of the amendments (page 5-6 of Amendment). However, Claims 1 and 10 are not rejected under 35 USC 103 in view of Ueda and Kobayashi. Accordingly, Applicant’s argument is moot.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Fujishima (US Pub. No. 2003/0065481), Sugaya (US Pub. No. 2016/0332297), Yamamoto (US Pub. No. 2017/0185076), Takahashi (US Pub. No. 2017/0220008), Matsudaira (US Pub. No. 2018/0071913), Watanabe (US Pub. No. 2018/0180085), and Koshiishi (US Pub. No. 2020/0285224) disclose robot control systems.
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.
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/STEPHEN HOLWERDA/Primary Examiner, Art Unit 3656