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 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.
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.
Claim(s) 1, 2, 8-10, and 14-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Moran (US 20070185696 A1), hereinafter Mo, in light of Dykstra (US 20150105912 A1), hereinafter D.
With respect to claim 1, Mo discloses a control system (all components of fig. 4) for adjusting operation of a drill string of a drilling machine, the control system comprising: a classifier module (combination of elements 46, 47, 49-51 in fig. 4) including a neural network configured, during a drilling process, to classify a ground condition, and based on the ground condition to output a set of parameters for controlling operation of the drill string, and a range of permissible values for each parameter of the set of parameters (pgphs. 60-63, 156-158); a optimizing module (combination 48 and 52) configured to receive as inputs i) the output from the classifier module (shown in fig. 4, pgph. 63), and a cost function (other economic performance factors, pgph. 63, or increasing ROP at the expense of greater wear, pgph. 158, the optimization of which would be performed by the optimizer 52), the optimizing module configured to output, for each parameter of the set of parameters, a predetermined value (53) within the range of permissible values, based on the inputs (pgphs. 62, 63, 156-158), wherein the cost function includes a value corresponding to performance of the drill string and lifetime of consumables of the drill string (pgphs. 63, 158); and a parameter setpoint module configured to receive, as an input, the predetermined values, the parameter setpoint module configured to adjust operation of the drill string based on the predetermined values (pgph. 131, whatever adjusts drilling parameters to perform automated drilling is the setpoint module).
However, Mo fails to disclose using a genetic algorithm for the optimizing module.
Nevertheless, D discloses using a genetic algorithm (pgph. 39) in an optimizing module (104) which receives a range of parameters 214 and a cost function (pgphs. 42-50) to select specific values for the parameters (pgph. 42, 43, 51, 52).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to have used a genetic algorithm in the optimizing module of Mo in order to select the specific values for the parameters from a range of parameters in response to a cost function as taught by D (pgphs. 39-54) since this is the application of a known technique in a similar device to improve it in the same way with predictable and obvious results and a reasonable expectation for success.
With respect to claim 2, Mo further discloses wherein the genetic algorithm module is configured to receive the cost function from an operator of the drilling machine (pgph. 158, the driller specifies to the optimizing module that ROP is of the greatest concern to the detriment of bit life).
With respect to claim 8, Mo further discloses wherein the classifier module is configured to output the set of parameters for controlling operation of the drill string, and the range of permissible values for each parameter of the set of parameters, based on a difference between an expected operation of the drill string and a measured operation of the drill string (pgph. 163).
The limitations of claims 9, 10, 14-18 are substantially similar to those of claims 1, 2, and 8, rejected supra, the set of parameters of Mo being a subset of all possible drilling parameters, the inputting of the cost function recited in pgph. 158, whatever is used to program the value in is the input device.
Claim(s) 3-7, 11-13, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mo in light of D as applied to claims 1, 2, 8-10, and 14-18 above, and further in view of Purwanto (US 20110232968 A1), hereinafter Pur.
With respect to claim 3, while Mo discloses that maximizing ROP (which equates to maximizing performance and minimizing time to drill) decreases a lifetime of a drill bit (a consumable, pgph. 158), Mo and D fails to specifically disclose wherein the value of the cost function varies between a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, and a second extreme value to maximize a lifetime of the consumables.
Nevertheless, Pur discloses wherein the value of the cost function varies between a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, and a second extreme value to maximize a lifetime of the consumables (pgph. 48).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to have made the cost function of Mo vary as taught by Pur (pgph. 48) since this is the application of a known technique in a similar device to improve it in the same way with predictable and obvious results and a reasonable expectation for success.
With respect to claims 4 and 5, Pur further discloses wherein the value of the cost function varies between a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, and a second extreme value to maximize a lifetime of a drill bit of the drill string and wherein the value of the cost function varies among a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, a second extreme value to maximize a lifetime of the consumables, and at least one intermediate value between the first and second extreme values.
The limitations of claims 11-13 and 20 are substantially similar to those of claims 3-5, rejected supra, pgphs. 47 and 48 of Pur discussing entering in and altering values for the cost function.
With respect to claims 6 and 19, while none of the art discloses the input device being in a cab of the drilling machine, Mo in light of Pur disclose an operator inputting cost functions (pgph. 158, Mo, pgphs. 47, 48, Pur), examiner takes official notice that computers with input devices in operators cabs are notoriously well-known in the art, and placing a computer with an input device in an operator’s cab is merely the selection between a finite number of locations to place an input device on-site.
With respect to claim 7, Mo discloses a display (pgph. 104) which displays relevant information to a driller, and Pur discloses calculating a lifetime of at least one consumable of the consumables and an expected time to drill a hole (pgph. 39, Pur) which are both based on the cost function and would have been obvious to display.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 20250297547 A1 also discloses using ML to identify rock type, US 20140326449 A1 discloses using a genetic algorithm and models to determine optimum parameters in pgphs. 65-67. US 20090132458 A1 also teaches using multiple modules for data analysis and optimization (ADA, IIE, pgphs. 92, 94).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KIPP CHARLES WALLACE whose telephone number is (571)270-1162. The examiner can normally be reached Monday - Friday 12:00 PM - 8:00 PM.
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/KIPP C WALLACE/Primary Examiner, Art Unit 3674 08/25/2026
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