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 . 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.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. The applicant's submission, the Reply of 16 December 2025, has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 16 December 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDS is being considered by the examiner.
Status of the Claims
The pending claims in the present application are claims 1-20, as presented in the Reply.
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.
Claims 1, 2, and 5-20 are rejected under 35 U.S.C. 103 as being unpatentable over WIPO Int’l Pub. No. 2022/194358 A1 to Kotriwala et al. (hereinafter referred to as “Kotriwala” (with an international filing date of 16 March 2021 and the US as a designated state), in view of U.S. Pat. App. Pub. No. 2020/0223642 A1 to Prutu (hereinafter referred to as “Prutu”), and further in view of U.S. Pat. App. Pub. No. 2021/0118066 A1 to Walker et al. (hereinafter referred to as “Walker”).
Regarding claim 1, Kotriwala discloses the following limitations:
“A computerized system comprising: one or more computer processors; and computer memory storing computer-useable instructions that, when used by the one or more computer processors, cause the one or more computer processors to perform operations comprising: ...” - Kotriwala discloses, “a computer hardware upgrade such as adding further memory and/or a further processor may be desired” (p. 4, ll. 9 and 10), and “The model is typically realized as a form of software for a computer, which can include, or be used together with, a database comprising data which is used by the software” (p. 9, ll. 14-16).
“... accessing, at a material processing engine, conveyance network data of a conveyance network, the conveyance network data comprising a plurality of source nodes, a plurality of sink nodes, and a plurality of network edges of the conveyance network; ...” - Kotriwala discloses, “Typically, a plurality of corresponding processing data and quality data are used for training or retraining the quality prediction model” (p. 7, ll. 6, and 7), “The processing data typically represent and/or include at least one parameter referring to a respective state of the processing device during operation and a material processing part of the processing device, respectively, more particular a respective state during processing the material” (p. 7, ll. 8-11), “a processing station and a processing device, respectively, can receive material, process the material, and dispense the processed material. In another example, a processing station/device can transfer material. In yet another example, a processing station/device can store the material. Combinations of such processes in one processing station are possible” (p. 8, ll. 18-21), “As already explained above, processing stations may include several processing devices for the material that operate in parallel and/or in a chain. For example, ore processing stations may include different processing devices referring to crushing, separating, concentrating and the like arranged in a chain” (p. 12, ll. 27 and 28), and “The process layout model can link (a number of) processing station layouts according to the material flow-paths between the processing stations. The linking of the processing stations according to the material flow-paths between the processing stations can result in a map of the network of material flow-paths. The processing stations can be nodes within the network of material flow-paths” (p. 20, ll. 27-31). Obtaining, by the model, processing data of processing stations that transfer material, wherein the processing stations are linked by material flow-paths, forming a map of a network where the processing stations are nodes, in Kotriwala, reads on the recited limitation.
“... based on the conveyance network data, identifying routing logic between the plurality of network edges of the conveyance network, ...” - See the aspects of Kotriwala that have been cited above. Kotriwala also discloses, “Material flow-paths can, in one example, include the type of expected material, the minimum or maximum amounts of material, the expected output material flow in dependence of the respective input material flow, the required time for processing the material or such. The representation of material flow-paths can be suitable for creating a material flow map of material between processing stations. The processing station layout enables a mapping of the material flow to and from each processing station. The mapped material flow typically does not represent the actual flow, i.e. transfer of material. The mapped material flow can be a mapped material flow-path, i.e. representing potential routes for the material, particularly between processing stations” (p. 15, ll. 9-17). Using the material flow-paths and related material flow data to identify and utilize potential routes for material between processing stations, in Kotriwala, reads on the recited limitation.
“... based on the routing logic, determining a surge flow routing logic corresponding to each of the plurality of network edges, ...” - Kotriwala discloses, “In particular, the information metamodel can utilize the process layout model for providing a map of the processing stations within the process, and the physical connections between the processing stations, particularly material flow-paths. The process layout model can be utilized for mapping a material flow within the industrial process, particularly all possible material flows” (col. 18, ll. 22-26), “The adaptive simulation model may be used to identify material blobs in the material flow and to export an event log file referring to the material blobs and representing the material flow” (col. 21, ll. 8 and 9), “Attributes of the material blobs can correlate to attributes of the material from which the material blobs are derived. In one example, attributes of a material blob can include information such as material quality, quantity, energy spent for processing, history of the material blob or such” (p. 21, l. 32 to p. 22, l. 2). Based on the material flow-paths, determining material blobs representing material flow through the material flow-paths, in Kotriwala, reads on the recited limitation.
“... accessing grindline performance data for the plurality of sink nodes, wherein the grindline performance data is associated with ore data of the plurality of source nodes, the ore data comprising mineralogical properties of an ore body; ...” - See the aspects of Kotriwala that have been cited above. Kotriwala also discloses, “a first ore grindability parameter of the ore feed is determined from the at least one sensor signal” (p. 2, ll. 5 and 6), “a gearless mill drive” (p. 13, l. 24), and “a semi-autogenous grinding (SAG) mill, an autogenous grinding (AG) mill, a ball mill, a rod mill, a tumbling mill, a gearless mill, a geared mill, a crusher, and high-pressure grinding rolls” (p. 14, l. 11-13). Accessing processing data related to grinding mills that are part of the network of processing stations and material flow-paths, wherein the processing data is associated with the grinding mills and their operation, and involves consideration of ore grindability parameters of ore feeds, in Kotriwala, reads on the recited limitation.
“... determining an expected amount of ore from the plurality of sources; ...” - See the aspects of Kotriwala that have been cited above. Determining attributes about material blobs, including their respective quantities, within the network of processing stations and material flow-paths, in Kotriwala, reads on the recited limitation.
The combination of Kotriwala and Prutu (hereinafter referred to as “Kotriwala/Prutu”) teaches limitations below of claim 1 that do not appear to be disclosed in their entirety by Kotriwala:
“... wherein identifying the routing logic comprises: determining that a first network edge of the plurality of network edges corresponds to a first variable speed conveyer, ...” - Prutu discloses, “an upstream conveyor 10” (para. [0058]), and “a variable frequency drive 12 (which drives conveyor 10)” (para. [0061]). Recognizing placement of the upstream conveyor, in Prutu, when applied in the context of the system in Kotriwala, reads on the recited limitation.
“... determining that a second network edge and a third network edges of the plurality of network edges correspond to a second conveyer and third conveyer of the plurality of conveyers, respectively, and ...” - Kotriwala discloses, “a power turn belt conveyor 30” and “a downstream conveyor 20” (para. [0058]), and “induction conveyors 40 and 50” (para. [0060]). Recognizing placement of the combined turn belt and downstream conveyors, and the induction conveyors, in Prutu, when applied in the context of the system in Kotriwala, reads on the recited limitation.
“... determining that, during a non-surge period, a flow of the first variable speed conveyor is split between the second conveyer and the third conveyer; ...” - See the aspects of Prutu that have been mentioned above. See also, FIG. 2 of Prutu, showing flow paths from the upstream conveyor to the turn belt and downstream conveyors or the induction conveyors. See also, FIG. 4 of Prutu, showing operations associated with “JAMMING,” “OVERLOAD,” and “OVERFLOW.” According to Prutu, “object overflow includes a determination that the density of objects on said conveyor is higher than a predetermined upper value” (para. [0013]). The jamming and overload scenarios, in Prutu, read on the recited “non-surge period” (as overflow in Prutu is a surge period). FIG. 5 of Prutu shows scenarios involving “Activate D1 and D3” and “Start IC 40 and BC 50 in Buffering Mode,” corresponding to the flow traveling along the upstream conveyor, power turn belt conveyor, and downstream conveyor being split off by diverts (D1 and D3) to the induction conveyor and buffering conveyor. Recognizing the relationship between the conveyors and flows, of Prutu, in the context of the system in Kotriwala, reads on the recited limitation.
“... wherein determining the surge flow routing logic comprises: determining that the first variable speed conveyer has maximum set point, ...” - See the aspects of Prutu that have been mentioned above. Prutu also discloses, “wherein object overflow includes a determination that the density of objects on said conveyor is higher than a predetermined upper value” (para. [0013]). Establishing the predetermined upper value for the density of objects on the conveyor, in Prutu, reads on the recited limitation. Note, it is the overflow scenario in Prutu that corresponds to the “surge flow,” not the jamming or overload scenarios.
“... determining that, during a surge period, the flow of the first variable speed conveyer exceeds the maximum set point, and ...” - See the aspects of Prutu that have been mentioned above. Determining that the density of objects on the conveyor is higher than the predetermined upper value, in Prutu, reads on the recited limitation. Elements of FIG. 6 of Prutu are indicative of the “surge period.”
“... responsive to determining that, during the surge period, the flow of the first variable speed conveyer exceeds the maximum set point, determining that the flow of the first variable speed conveyer in excess of the maximum set point is directed to a single one of the second conveyor or the third conveyer; ...” - See the aspects of Prutu that have been mentioned above. Prutu also discloses, “B) If during Step A, object overflow is detected on said conveying path, then conveyor speed along said path is modified such that the relative speed of a downstream portion of said conveyor is increased relative to the speed of an upstream portion of said conveyor, wherein object overflow includes a determination that the density of objects on said conveyor is higher than a predetermined upper value; C) If after Step B, a predetermined time passes and overflow continues, then objects along said conveying path are buffered to a separate overflow conveyor” (para. [0013]). Having logic to determine entry into the overflow condition, and direct the objects to the turn and belt and downstream conveyors, or to the overflow conveyors, in Prutu, reads on the recited limitation.
“... causing the conveyance network to operate in accordance with the overflow management configuration, wherein causing the conveyance network to operate in accordance with the overflow management configuration comprises: ...” - See the aspects of Prutu that have been mentioned above. Operating the conveyors in the overflow condition, in Prutu, reads on the recited limitation.
“... inputting the overflow management configuration into the conveyance network as at least one of a setting or control for the conveyance network, ...” - See the aspects of Prutu that have been mentioned above. Operational instructions or settings for operating the conveyors in the overflow condition, in Prutu, read on the recited limitation.
“... controlling the first variable speed conveyer according to the overflow management configuration, such that a material is conveyed by the first variable speed conveyer, ...” - See the aspects of Prutu that have been mentioned above. Controlling the variable frequency drive motor of the upstream conveyor to convey items, in Prutu, reads on the recited limitation.
“... determining that, during the surge period, the flow of the material on the first variable speed conveyer exceeds the maximum set point, and ...” - See the aspects of Prutu that have been mentioned above. Determining that there is object overflow on the upstream conveyor based on the density of objects on the conveyor being higher than the predetermined upper value, in Prutu, reads on the recited limitation.
“... responsive to determining that, during the surge period, the flow of the material on the first variable speed conveyer exceeds the maximum set point, controlling the second conveyor or the third conveyer according to overflow management configuration, such that the flow of the material in in excess of the maximum set point to be directed onto a single one of the second conveyor or the third conveyer.” - See the aspects of Prutu that have been mentioned above. After determining there is object overflow on the upstream conveyor, increasing the speed of the downstream conveyor to reduce the overflow by reducing the density of objects on the upstream conveyor, and/or diverting the overflow to the separate overflow conveyor, in Prutu, reads on the recited limitation.
Prutu discloses, “the use of belt conveyors, as well of methods and apparatuses for controlling said belt conveyors” (para. [0004]), similar to the claimed invention and to Kotriwala. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of conveyors, in Kotriwala, to include the overflow condition handling, of the system of conveyors in Prutu, for purposes of cost and time efficiencies, and for extending the lives of the conveyors, as taught by Prutu (see para. [0012]).
The combination of Kotriwala, Prutu, and Walker (hereinafter referred to as “Kotriwala/Prutu/Walker”) teaches limitations below of claim 1 that do not appear to be taught in their entirety by Kotriwala/Prutu:
“... based on the routing logic between the plurality edges, the surge flow routing logic, grindline performance data, and the expected amount of ore, generating an overflow management configuration comprising overflow risk data for the plurality of source nodes; and ...” - See the aspects of Kotriwala that have been cited above. Based on the mapped material flows, the sending of material blobs along material flow-paths, the routing to and out of processing stations that are grind mills, the ore quantities, generating plans to manage said flows (including overflows), in Kotriwala, reads on the recited “based on the routing logic between the plurality edges, the surge flow routing logic, grindline performance data, and the expected amount of ore, generating an overflow management configuration” limitation. Walker teaches, “Prediction window generation step 53 may provide a visual indication (e.g., shading 76) of the prediction window 40 for those future times when the number of haul trucks 18 at the crusher 16 is predicted to exceed the preferred maximum number (e.g., as indicated by dashed line 74) of haul trucks 18” (para. [0078]). Generating prediction window data showing preferred maximums with respect to material flows, in Walker, when applied in the context of the network of processing stations and material flow-paths, in Kotriwala/Prutu, reads on the recited “comprising overflow risk data for the plurality of source nodes” limitation.
Walker discloses “material processing systems” (para. [0001]), similar to the claimed invention and to Kotriwala/Prutu. It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the network of processing stations and material flow-paths, of Kotriwala/Prutu, to generate data about material flows relative to preferred maximums, as in Walker, to help ensure that operating limits are not exceeded, as taught by Walker (see para. [0084]).
Regarding claim 2, Kotriwala/Prutu/Walker teaches the following limitations:
“The system of claim 1, wherein the conveyance network data further comprises transshipment nodes, wherein the conveyance network data comprises design configurations and operational configurations of the conveyance network, wherein the conveyance network combines at least two source nodes of the plurality of source nodes to one sink node of the plurality of sink nodes.” - See the aspects of Kotriwala that have been cited above. The mapped network including nodes in the form of processing stations that transfer material, wherein processing data associated therewith includes processing station characteristics and processing parameters, and the nodes are part of parallel and chained nodes, in Kotriwala, reads on the recited limitation.
Regarding claim 5, Kotriwala/Prutu/Walker teaches the following limitations:
“The system of claim 1, wherein determining the amount of expected ore is based on formalizing ore delivery at the plurality of sources, wherein formalizing ore delivery comprises determining a fixed batch sizes that is either surging or at rest.” - See the aspects of Kotriwala that have been cited above. Determining material quantities based on material blobs (ores) being transported to processing stations, wherein the blobs are set quantities as depicted in FIG. 7 of Kotriwala, reads on the recited limitation.
Regarding claim 6, Kotriwala/Prutu/Walker teaches the following limitations:
“The system of claim 1, wherein the overflow management configuration minimizes conveyor overflow risk due to inconsistent ore processing rates while meeting stockpile height requirements.” - See the aspects of Kotriwala and Walker that have been cited above. Kotriwala also discloses, “a conveyor 330 and a stockpile 340” (p. 35, ll. 9 and 10). Walker also teaches, “Again, step 56 predicts the No-Material state based on the level 61 of ore 62 in surge bin 58, the crush out time, and the surge bin capacity. The crush out time is the time required by the crusher 16 to crush the excavated ore 14 discharged by a haul truck 18. The surge bin capacity is the capacity, typically measured in tons, of the surge bin 58. In this regard, the present invention establishes Low, Operating, and High limits, 84, 86, and 88, respectively, for the level 61 of crushed material 62 existing within surge bin 58. See FIG. 9. The Low limit 84 is that level 61 of crushed material 62 required to maintain a material bed 90 in the outlet end 82 of surge bin 58. If the level 61 of crushed material 62 drops below the Low limit 84, the crusher control system (not shown), will shut down the apron feeder (also not shown) to maintain the material bed 90, thereby protecting the apron feeder from damage” (para. [0082]). The handling of material blobs by conveyors, in Kotriwala, when operated in a way that keeps fluctuating amounts of material being delivered in a preferred range to ensure that material being processed is within low and high limits, as in Walker, reads on the recited limitation. The rationales for combining the teachings of the cited references, from the rejection of claim 1, also apply for purposes of rejecting claim 6.
Regarding claim 7, Kotriwala/Prutu/Walker teaches the following limitations:
“The system of claim 1, wherein determining an amount of expected ore is a function of fixed batch sizes associated with the plurality of sources.” - See the aspects of Kotriwala that have been cited above. Determining quantities of ores for the material blobs moving between processing stations, in Kotriwala, reads on the recited limitation.
Regarding claim 8, Kotriwala/Prutu/Walker teaches the following limitations:
“The system of claim 1, the operations further comprising: identifying an active network edge from the plurality of network edge; ...” - See the aspects of Kotriwala that have been cited above. Identifying potential routes between processing stations and designating them as actual material flow-paths, in Kotriwala, reads on the recited limitation.
“... identifying a respective surge flow routing logic for the active network edge; ...” - See the aspects of Kotriwala that have been cited above. Identifying material flow-paths with rising quantities of materials therein (including more material blobs), in Kotriwala, reads on the recited limitation.
“... based on the respective surge flow routing logic, determining one or more of the plurality of source nodes that pose a risk; and ...” - See the aspects of Kotriwala that have been cited above. Identifying material flow-paths having larger quantities of material blobs approaching, in Kotriwala, reads on the recited limitation.
“... determining a maximum overflow risk for the active network edge as a function of a simultaneous surge of the one or more of the plurality source nodes that pose the risk.” - See the aspects of Kotriwala and Walker that have been cited above. Determining routes in which the number of haul trucks is predicted to exceed preferred maximum numbers, and could overload downstream crushers, in Walker, when applied in the context of the material flow modelling in Kotriwala, reads on the recited limitation. The rationales for combining the teachings of the cited references, from the rejection of independent claim 1, also apply for purposes of rejecting claim 8.
Regarding claim 9, Kotriwala/Prutu/Walker teaches the following limitations:
“The system of claim 1, the operations further comprising constraining, via the material processing engine, the conveyance network such that nodes of the conveyance network do not have a maximum overflow risk.” - See the aspects of Kotriwala and Walker that have been cited above. Walker also teaches, “if too many haul trucks 18 are predicted to be at the crusher 16 at some future time, the director 38 may redirect one or more haul trucks 18 to other locations so as to minimize the idle time for haul trucks 18 at the crusher 16” (para. [0085]). The model controlling material flowing through flow-paths between processing stations, in Kotriwala, such that flows exceeding preferred maximums can be re-directed, as in Walker reads on the recited limitation. The rationales for combining the teachings of the cited references, from the rejection of independent claim 1, also apply for purposes of rejecting claim 9.
Regarding claim 10, Kotriwala/Prutu/Walker teaches the following limitations:
“The system of claim 1, the operations further comprising constraining the amount of expected ore to meet stockpile height requirement associated with the plurality of sink nodes.” - See the aspects of Kotriwala and Walker that have been cited above. The model controlling ore material flowing through flow-paths to processing stations, in Kotriwala, such that ore amounts are within low and high limits, in Walker, reads on the recited limitation. The rationales for combining the teachings of the cited references, from the rejection of claim 1, also apply for purposes of rejecting claim 10.
Regarding claims 11-15, while the claims are of different scope relative to claims 1, 5, and 8-10, the claims recite limitations similar to those recited by claims 1, 5, and 8-10. As such, the rationales applied to reject claims 1, 5, and 8-10 also apply for purposes of rejecting claims 11-15. Claims 11-15 are, therefore, also rejected under 35 USC 103 as obvious in view of Kotriwala/Prutu/Walker.
Regarding claims 16-20, while the claims are of different scope relative to claims 1, 5, and 8-10 and to claims 11-15, the claims recite limitations similar to those recited by claims 1, 5, and 8-15. As such, the rationales applied to reject claims 1, 5, and 8-15 also apply for purposes of rejecting claims 16-20. Claims 16-20 are, therefore, also rejected under 35 USC 103 as obvious in view of Kotriwala/Prutu/Walker.
Claims 3 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Kotriwala, in view of Prutu, further in view of Walker, and further in view of WIPO Int’l Pub. No. 2006/021052 A1 to Law et al. (hereinafter referred to as “Law”).
Regarding claim 3, the combination of Kotriwala, Prutu, Walker, and Law (hereinafter referred to as Kotriwala/Prutu/Walker/Law”) teaches limitations below that do not appear to be taught in their entirety by Kotriwala/Prutu/Walker:
“The system of claim 1, wherein the routing logic is identified as binary or variable, wherein the plurality of network edges correspond to a plurality of network arcs each labeled as an uninterrupted source-sink path or an interrupted source-sink path, wherein uninterrupted source-sink paths are configurable with fixed routing logic or variable routing logic; and ...” - Law discloses, “The equipment control attributes specify the operational parameters of equipment included in the material handling facility. This includes, without limitation: downstream equipment - which equipment can it feed to downstream, upstream equipment - which equipment can feed burden onto it, feed point from upstream equipment (distance in metres), for example where there are multiple feed points along a conveyor, whether the equipment is capable of variable speed operation, whether the equipment is capable reverse operation, full speed (m/s), drive power (kW), and stopping distance (m) - distance it takes to stop after receiving a stop command” (p. 7, ll. 17-27). Material handling devices that are capable of forward operation and/or reverse operation, and also variable speed operation, and are configured to operate as such, in Law, when applied in the context of the processing stations of Kotriwala/Prutu/Walker, reads on the recited limitation.
“... wherein interrupted source-sink paths are configurable with variable speed routing logic.” - See the aspects of Law that have been mentioned above. Material handling devices having variable speed operation, in Law, reads on the recited limitation.
Law teaches a “material handling system” (abstract) similar to the claimed invention and to Kotriwala/Prutu/Walker. It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the processing stations for material transfer, of Kotriwala/Prutu/Walker, to include the variable direction and/or speed operative capabilities, as described in Law, for expanding control capabilities or possibilities, as taught by Law (see p. 7, ll. 17 and 18).
Regarding claim 4, Kotriwala/Prutu/Walker/Law teaches the following limitations:
“The system of claim 1, wherein determining the surge flow routing logic is based on the following: if a network edge has a binary routing logic, the surge flow routing logic is such that surge only flows in a direction that ore is flowing; and ...” - See the aspects of Kotriwala that have been cited above. If a material flow-path routes material blobs representing ores in a forward direction from an upstream processing station to a downstream processing station, in Kotriwala, the arrangement reads on the recited limitation.
“... if a network edge has a variable routing logic, a binary direction is identified and the surge flow routing logic is such that surge risk flow is in the binary direction.” - See the aspects of Kotriwala and Law that have been cited above. If a material flow-path routes material blobs in a forward direction, as in Kotriwala, and then later in a reverse direction, as in Law, the arrangement reads on the recited limitation. The rationales for combining the teachings of the cited references, from the rejection of claim 1, also apply for purposes of rejecting claim 4.
Response to Arguments
On p. 11 of the Reply, the applicant requests reconsideration and withdrawal of the claim rejection under 35 USC 101. In view of the amendment to claim 11, the ineligibility rejection has been withdrawn.
On pp. 11-14 of the Reply, the applicant requests reconsideration and withdrawal of the claim rejections under 35 USC 103. The examiner finds the applicant’s arguments unpersuasive. Based on p. 13 of the Reply, it appears that the applicant’s position is that the overload condition, in Prutu, when interpreted as the “surge period,” fails to disclose, teach, or suggest various claim limitations. The rejection, however, treats the overload condition in Prutu as a type of “non-surge period,” and the overflow condition in Prutu as the “surge period.” Overload condition and overflow condition are not the same, in Prutu. With such an interpretation, Kotriwala/Prutu/Walker(/Law) teaches all recited limitations of the claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THOMAS Y. HO, whose telephone number is (571)270-7918. The examiner can normally be reached Monday through Friday, 9:30 AM to 5:30 PM Eastern.
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/THOMAS YIH HO/Primary Examiner, Art Unit 3624