DETAILED ACTION
Claims 1-20 are presented for examination. This office action is response to the submission on 10/10/2023.
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 .
Drawings
The drawings filed on 10/10/2023 are acceptable for examination proceedings.
Claim Objections
Claim 1 recites the limitations:
"the industrial process product" in line 6.
“the one or more blending products” in line 19.
“the one or more feed products” in line 20.
“the feed component” in line 23.
Claim 11 recites the limitation:
“the feed component” in lines 23-24.
There is insufficient antecedent basis for these limitations in these claims. For the purposes of examination, examiner interprets these terms to be introduced in the lines indicated above.
Claim 1 is objected to because of the following informalities: Lines 8-9 read “wherein the optimization time period is less the first time period;”. Examiner believes this should read “wherein the optimization time period is less than the first time period;” (Typo).
Claim 6 is objected to because of the following informalities: Line 1 reads “The system of claim 3, the processor” Examiner believes this should read “The system of claim 3, wherein the processor” (Typo).
Claim 10 is objected to because of the following informalities: Line 1 reads “The system of claim 9, the processor is further…”. Examiner believes this should read “The system of claim 9, wherein the processor is further” (Typo).
Claim 11 is objected to because of the following informalities: Lines 8-9 read “wherein the optimization time period is less the first time period;”. Examiner believes this should read “wherein the optimization time period is less than the first time period;” (Typo).
Appropriate correction 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent Claims 1 and 11
Claim 1 is drawn to a system and claim 11 is drawn to a method. Therefore claims 1 and 11 fall under one of the four categories of statutory subject matter (process/method, machines/products/apparatus, manufactures, and compositions of matter).
Step 2A: Is the claim directed to a law of nature, a natural phenomenon (product of nature), or an abstract idea?
It is an abstract idea.
Step 2A-Prong 1: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes.
MPEP 2106.04(a) - “Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion).”
Claims 1 and 11 are directed to a judicially recognized exception of an abstract idea without significantly more. Each of claims 1 and 11 recites functions below that under the limitations broadest reasonable interpretation, enumerates mental concepts. Other than reciting generic computer elements “a memory comprising one or more instructions; and a processor communicatively coupled with the memory,” (as recited in claim 1), nothing in the claims preclude the functions from the mental concept.
The mere nominal recitation of a generic processor to perform the mental concept does not take the claim limitations out of the abstract idea (See MPEP 2106.04(a)(2)(III)).
“and wherein the processor is configured to: determine a first time period to produce the industrial process product to fulfill one or more orders;” A human can determine a time period to produce industrial process product (judgment).
“determine an optimization time period, wherein the optimization time period is less the first time period;” A human can determine an optimized time less than the first time period (judgment).
“in response to determination of the optimization time period: update industrial process product characteristics based on at least the first time period and the optimization time period;” A human can update process product characteristics based on the two times (judgment).
“update blending component characteristics indicative of availability of one or more blending components for the batch process based on the updated industrial process product characteristics, the first time period, and the optimization time period;” A human can update blending component characteristics indicating availability based on the updated process product characteristics and time (evaluation).
“in response to completing the production of the industrial process product for an order of the one or more orders, determine product spent characteristics associated with the one or more blending products;”, A human can determine product spent characteristics in response to completion of production of an order (judgment).
“update demand data for the one or more feed products utilized for blending the one or more blending products based on the product spent characteristics;” A human can update demand data for feed products based on the product spent characteristics (judgment).
Step 2A-Prong 2: Does the claim recite additional element that integrate the judicial exception into a practical application?
No.
2106.05(f) Mere Instructions To Apply An Exception
“As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do "‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’". Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on "the draftsman’s art").”
The following is using generic computer elements:
“a memory comprising one or more instructions; and a processor communicatively coupled with the memory,”
2106.05(g) Insignificant Extra-Solution Activity
The term "extra-solution activity" can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process, e.g., a step of obtaining information about credit card transactions, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps in order to detect whether the transactions were fraudulent. An example of post-solution activity is an element that is not integrated into the claim as a whole, e.g., a printer that is used to output a report of fraudulent transactions, which is recited in a claim to a computer programmed to analyze and manipulate information about credit card transactions in order to detect whether the transactions were fraudulent.
The following is pre-solution activity (mere data gathering):
“receiving an optimization request to optimize an industrial process that produces an industrial process product” (claim 11)
The following is post-solution activity:
“transmit a control signal to control the flow of the feed component in the continuous process.” (claim 1)
MPEP 2106.05(h) – Field of Use
MPEP 2106.05(h) states: “Another consideration when determining whether a claim integrates the judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.”
“wherein the processor is configured to control an industrial process that includes a continuous process and a batch process,” is directed towards implementing a method to the field of use of controlling an industrial process including a continuous and batch process.
“A system for controlling an industrial process, the system comprising:” is directed towards implementing a system to the field of use of controlling an industrial process.
The examiner has considered the limitations together as a single abstract idea for Step 2A Prong Two rather than as a plurality of separate ideas to be analyzed individually.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
The additional elements amount to implementing a generic processor and memory towards a field of use and insignificant pre and post solution activity. “Courts have held computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking). On the other hand, courts have held computer-implemented processes to be significantly more than an abstract idea (and thus eligible), where generic computer components are able in combination to perform functions that are not merely generic.” DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1257-59, 113 USPQ2d 1097, 1105-07 (Fed. Cir. 2014). ”Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display” Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).
MPEP 2106.05(d)(II)(i) provides support that receiving or transmitting data over a network is well understood, routine, and conventional.
As such, claims 1 and 11 are not patent eligible.
Dependent Claims 2-10, 12-20:
Step 1:
Claims 2-10 are drawn to a system, claims 12-20 are drawn to a computer implemented method, therefore each of claims 2-10 and 12-20 fall under one of four categories of statutory subject matter (process/method, machines/products/apparatus, manufactures, and compositions of matter). Nonetheless, dependent claims 2-10 and 12-20 are also ineligible for the same reasons given with respect to claims 1 and 11.
Steps 2A-2B:
Claim 2 recites further the insignificant input-solution activity of receiving an optimization request (See MPEP 2106.05(g)).
Claims 2-10 and 12-20 recite further the mental abstract concepts of determining whether time data satisfies a criterion, determining product spent characteristics based on industrial process product characteristics or virtual spent components, tracking virtual content based on an optimization time period, determining product spent characteristics based on process product characteristics, determining product spent characteristics based on content of material in blending components, measuring utilization of feed products by back-calculating product feed products, updating demand data for feed products based on product spent characteristics, resetting the first time period in response to updating demand data, updating demand data in response to a change in demand for industrial process product, and generating batch blending recipes based on updated demand data (See MPEP 2106.04(a)(2)(III)).
The additional functions that are form of insignificant extra-solution activities, do not amount to significantly more than an abstract idea because the court decisions have determined that this additional steps to be well-understood, routine, and conventional when claimed in a merely generic manner for data storing, collecting and transmitting (See MPEP § 2106.05(d)(II)(i: Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information)) or (iv: Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)), See further Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016))).
As such, claims 2-10 and 12-20 are not patent eligible.
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.
Claims 1-4, 6, 11-14 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Lu (US20210132591A1), in view of Polarine (US20050197930A1).
Claim 1:
Lu teaches “A system for controlling an industrial process, the system comprising: a memory comprising one or more instructions; and a processor communicatively coupled with the memory,” (Lu teaches controllers including processing devices 142 and memories 144 for storing instructions used by the processing devices 142 in Lu [0055] "In particular embodiments, the various controllers and operator stations in FIG. 1 may represent computing devices. For example, each of the controllers 106, 114, 122, 130, 138 could include one or more processing devices 142 and one or more memories 144 for storing instructions and data used, generated, or collected by the processing device(s) 142. Each of the controllers 106, 114, 122, 130, 138 could also include at least one network interface 146, such as one or more Ethernet interfaces or wireless transceivers. Also, each of the operator stations 116, 124, 132, 140 could include one or more processing devices 148 and one or more memories 150 for storing instructions and data used, generated, or collected by the processing device(s) 148. Each of the operator stations 116, 124, 132, 140 could also include at least one network interface 152, such as one or more Ethernet interfaces or wireless transceivers."
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“wherein the processor is configured to control an industrial process that includes a continuous process and a batch process,” (Lu teaches that the process controlled may include continuous processes and discontinuous processes i.e. batch processes in Lu [0141] "FIG. 20 is a schematic illustration of a process 2000 for ultimately converting raw ingredients into finished products. In some instances, raw ingredients 2002 may be converted into intermediate components 2004 in a continuous process 2006. The intermediate components 2004 may then be converted into final products 2008 in a discontinuous process 2010. It will be appreciated that the discontinuous process 2010 may occur in a batch fashion, or parts of the discontinuous process 2010 may occur in a batch fashion. In some instances, parts of the discontinuous process 2010 may occur in a continuous or assembly-line fashion, but may occur over a different time frame than the continuous process 2006."),
“and wherein the processor is configured to: determine a first time period to produce the industrial process product to fulfill one or more orders;” (Lu teaches a master MPC controller 302 that optimizes planning, controlling inventories, manufacturing activities, or product qualities in Lu [0074] "Each MPC controller 302, 304 a-304 n supports economic optimization and multivariable control functions. The master MPC controller 302 uses a planning model 200 (such as a yield-based single-period planning model) to provide an initial steady-state gain matrix, and relevant model dynamics can be determined using operating data of the plant (such as historical data). The master MPC controller 302 operates to control product inventories, manufacturing activities, or product qualities within the plant. The embedded economic optimizer of the master MPC controller 302, which is furnished with the same planning model structure and economics, could therefore reproduce the single-period offline planning optimization but in an online and real-time manner."; Lu teaches that the master MPC controller 302 optimizes the plant, generating the best achievable plan in Lu [0078] "The master MPC controller 302 is a real-time plan executor that understands the big picture from the planning model 200 and uses each unit's MPC models 250 for advanced process control. The master MPC controller 302 can therefore optimize the plant in concert with the slave MPC controllers 304 a-304 n, generating the best-achievable plan while honoring all units' constraints."; Lu teaches determining a time frame for a final product produced in a batch process i.e. an order in Lu [0144] "In some cases, the concepts of intermediate components 2004 being produced in a continuous process such as the continuous process 2006 while final products 2008 are produced in a discontinuous process (e.g. batch process) such as the discontinuous process 2010 may be applicable to a number of other industries. In some cases, intermediate components such as the intermediate components 2004 may be produced during a process that runs over a first time frame. Final products, such as the final products 2008, may be produced during another process that runs over a second time frame that is different from the first time frame. In some cases, the second time frame may at least partially overlap the first time frame, but this is not required. The second time frame may occur immediately after the first time frame, or in some cases the second time frame may occur at some time in the future subsequent to the first time frame."),
“in response to determination of the optimization time period: update industrial process product characteristics based on at least the first time period and the optimization time period;” (Lu teaches that in an example, if there is a high demand for a product A higher than product B, it may be lucrative to use memory chips i.e. intermediate products only for product A i.e. final products, which would cause the timeline of production of product A to be finished earlier i.e. the process product characteristics would be updated to produce more of product A in Lu [0145] "As an example, the final product may be any of a number of different computer products. One of the intermediate components may be a memory chip. It will be appreciated that the memory chips are produced in a lengthy process that includes semiconductor fabrication. This lengthy process may be considered as a continuous or nearly continuous process. A particular brand and model of memory chip may be used during the assembly of any of a variety of different computer products. It will be appreciated that assembly of a particular computer product occurs over a different time frame than the production of the memory chip that is used in assembling a particular computer representing that particular computer product. If there is a high demand for computer product A, and a lower demand for computer product B, it may be more lucrative to use more of the memory chips in assembly computers of product A, and not to assembly any (or very many) computers of product B."),
“update blending component characteristics indicative of availability of one or more blending components for the batch process based on the updated industrial process product characteristics, the first time period, and the optimization time period;” (Lu teaches that the disclosure pertains to production of petroleum products from blending components in Lu [0142] "It will be appreciated that much of this disclosure pertains to the production of petroleum products from blending components that are produced from petroleum stocks. Some of all of these blending components may be considered as being distillation column products. The raw ingredients 2002 may be crude oil, which can of course vary considerably in its individual molecules and molecular distribution, may enter a distillation column at an oil refinery or related facility. A variety of different blends of molecules may be pulled off of the distillation column. Relatively lighter blends (smaller molecular weight molecules) may be pulled off towards the top of the distillation column while relatively higher blends (larger molecular weight molecules) may be pulled off at relatively lower levels on the distillation column."; Lu teaches that intermediate components (computer chip A) i.e. blending component may be influenced by the demand of computer product A i.e. the planned production of product A which is affected by the time periods may affect the planned production of processor chip A, which may be regarded as blending components in Lu [0146] "As a related example, two of the intermediate components may be processor chips. Processor chip A is only used in computer product A, and processor chip B is only used in computer product B. It will be appreciated that the relative demand for computer product A and computer product B as final products may influence the earlier production of the intermediate components. It is helpful to take into account what final product(s) may be produced, or are desired, when determining how to allocate raw ingredients, energy consumption, labor costs and the like when planning production of intermediate components."),
“update demand data for the one or more feed products utilized for blending the one or more blending products based on the product spent characteristics;” (Lu teaches a method for optimizing continuous conversion of initial components i.e. feed products into blending components, which would require updating the demand for initial components as blending component demands are updated in Lu [0167] "An optimization is performed that includes the continuous conversion of initial components into the plurality of blending components as well as subsequent production of the plurality of desired fuel products, subject to the constraints on each of one or more of the initial components, the constraints on each of the plurality of blending components, the recipe for each of the plurality of desired fuel products, and the quantity of each of the plurality of desired fuel products to be produced, as indicated at block 2808."), and
“transmit a control signal to control the flow of the feed component in the continuous process.” (Lu teaches a method for optimizing continuous conversion of initial components into blending components that are used to make desired fuel products, which involves controlling the continuous manufacturing process based on the optimization i.e. it transmits a control signal to control flow of feed components in Lu [0167] "FIG. 28 is a flow diagram showing an illustrative method 2800 for optimizing continuous conversion of initial components into a plurality of blending components that are then used as inputs to make a plurality of desired fuel products. Constrains are received on each of one or more of the initial components, as indicated at block 2802. Constraints are received on each of the plurality of blending components (e.g. intermediate components), as indicated at block 2804. Information is received on the plurality of desired fuel products to be produced from the plurality of blending components including a quantity of each of the plurality of desired fuel products to be produced and one or more recipes that specifies how the plurality of blending components are to be combined to form each of the plurality of desired fuel products, as indicated at block 2806. An optimization is performed that includes the continuous conversion of initial components into the plurality of blending components as well as subsequent production of the plurality of desired fuel products, subject to the constraints on each of one or more of the initial components, the constraints on each of the plurality of blending components, the recipe for each of the plurality of desired fuel products, and the quantity of each of the plurality of desired fuel products to be produced, as indicated at block 2808. In some cases, the optimization may be performed using equation (32) or the like. The continuous manufacturing process and the subsequent production of the plurality of desired fuel petroleum-based products may be controlled based at least in part upon the optimization, as indicated at block 2810.").
Lu does not appear to explicitly teach “in response to completing the production of the industrial process product for an order of the one or more orders, determine product spent characteristics associated with the one or more blending products;” However, Polarine does teach this claim limitation (Polarine teaches that each dispensing cycle i.e. after completion of production of industrial process product, the inventory will be updated to deduct inventory of dispensed quantities of stock components i.e. determine product spent characteristics associated with blending products in Polarine [0098] "Means 60 for configuring computer readable program code devices to cause client computer 10 or host computer 12 to generate an updated inventory. As shown in FIG. 5, means 60 comprise means 62 for configuring computer readable program code devices to cause client computer 10 or host computer 12 to (a) deduct from the current inventory dispensed quantities of the stock composition, the stock components, or a combination thereof to generate an adjusted current inventory; (b) deduct from the supplementary inventory dispensed additional quantities of the stock composition, dispensed quantities of the missing stock components, or a combination thereof, to generate an adjusted supplementary inventory; and (c) add the adjusted current inventory and the adjusted supplementary inventory. The aforementioned sum then becomes the updated inventory. It should be noted the updated inventory would then become the stored inventory in the subsequent dispensing cycle.").
Lu and Polarine are analogous art because they are from the same field of controlling and monitoring production. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Lu and Polarine before him/her, to modify the teachings of an Plant-wide optimization including batch operations of Lu to include the updating of inventory each cycle of Polarine because adding the Monitoring device used for producing compositions of Polarine would ensure the product quality of the composition and reduce costs as described in Polarine [0171-0172] “The process and the device of the present invention helps in eliminating the dispensing of poor quality substitution of components listed in the formula, thereby preventing the production of sub-standard compositions... As the contents in the container are consumed, an updated inventory can be transmitted to the manufacturer by allowing the manufacturer access to client computer 10 or host computer 12, which can be alternatively operated by the manufacturer. The updated inventory then becomes the current inventory in the subsequent dispensing cycle provided the user, such as a collision repair shop, makes no unauthorized additions or deletions to the current inventory. Thus, the process of the present invention helps in ensuring the product quality of the composition. Additionally, since the manufacturer is aware of which component has been used up, the manufacturer can automatically augment the user with those depleted components without any formal request from the user, thereby reducing the time require to supply the components consumed by the user. Moreover, the manufacturer can also assist the user in reducing his inventory by supplying the components, just in time as they are used up. Moreover, the manufacturer can also bill the user on an “as-used-basis” for the cost of only the stock composition or components actually consumed. As a result, the user's out-of-pocket cost can be reduced.”
Claim 2:
Lu in view of Polarine teaches “The system of claim 1, wherein the processor is further configured to receive an optimization request in response to a determination that time data for the industrial process satisfies a defined criterion.” (Lu teaches that in an example, if there is a high demand for a product A higher than product B, it may be lucrative to use memory chips only for product A, which would cause the timeline of production of product A to be finished earlier i.e. if the existing time data for production of product A is too late, it can reoptimize such that production of product A finishes earlier in Lu [0145] "As an example, the final product may be any of a number of different computer products. One of the intermediate components may be a memory chip. It will be appreciated that the memory chips are produced in a lengthy process that includes semiconductor fabrication. This lengthy process may be considered as a continuous or nearly continuous process. A particular brand and model of memory chip may be used during the assembly of any of a variety of different computer products. It will be appreciated that assembly of a particular computer product occurs over a different time frame than the production of the memory chip that is used in assembling a particular computer representing that particular computer product. If there is a high demand for computer product A, and a lower demand for computer product B, it may be more lucrative to use more of the memory chips in assembly computers of product A, and not to assembly any (or very many) computers of product B.").
Claim 3:
Lu in view of Polarine teaches “The system of claim 1, wherein the processor is further configured to determine the product spent characteristics associated with the one or more blending products by determining the product spent characteristics based on industrial process product characteristics for the industrial process product” (Lu teaches an aggregate lifting specification 2400 that provides components required to produce the desired products of aggregate lifting specification 2300 i.e. it determines the amount of blending products required to produce the completed products in Lu [0153] "FIG. 24 is a graphical representation of an aggregate lifting specification 2400 that provides the individual components that will be necessary to produce the desired products shown in the aggregate lifting specification 2300. The vertical axis provides an indication of volume, in this case barrels, while the horizontal axis provides an indication of individual intermediate components. In this particular example, the intermediate components include FCC gas 2402, reformate 2404, C4 2406, alkylate 2408, straight run gas 2410 and C18 2412. It will be appreciated that there may be a number of additional intermediate components that, for simplicity, are not illustrated in the aggregate lifting specification 2400."
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“or one or more virtual spent components for the one or more blending products, wherein the one or more virtual spent components are associated with (Lu teaches that the inventory volumes of processing units and pool tanks can be tracked dynamically i.e. a virtual content tracker in Lu [0111] "Among other things, the benefits of using base model structures include designing a limited number of base structures (such as two in the example above), where the base structures provide flexibility in terms of how the units and tanks are connected. For example, processing units and pool tanks could be fixed after configuration, and the states of inventory volumes/properties can be tracked dynamically. Connections between processing units and pool tanks could be stateless and changed on-the-fly. Moreover, a planning model for master MPC controllers can be constructed on the fly. In addition, the cascaded architecture can easily take advantage of intermediate feedback as long as intermediate input-output signals can be adequately measured, and this approach can support improved model updating as its structure aligns more naturally with real processing units.").
Claim 4:
Lu in view of Polarine teaches “The system of claim 3, wherein the processor is further configured to utilize the virtual content tracker to track the product spent characteristics associated with the one or more blending products based on the optimization time period.” (Lu teaches tracking of blending components for the next m-days i.e. the optimization time period in Lu [0153] "FIG. 24 is a graphical representation of an aggregate lifting specification 2400 that provides the individual components that will be necessary to produce the desired products shown in the aggregate lifting specification 2300. The vertical axis provides an indication of volume, in this case barrels, while the horizontal axis provides an indication of individual intermediate components. In this particular example, the intermediate components include FCC gas 2402, reformate 2404, C4 2406, alkylate 2408, straight run gas 2410 and C18 2412. It will be appreciated that there may be a number of additional intermediate components that, for simplicity, are not illustrated in the aggregate lifting specification 2400.").
Claim 6:
Lu in view of Polarine teaches “The system of claim 3, the processor is further configured to determine the product spent characteristics based on monitoring content of material included in the one or more blending components.” (Lu teaches an aggregate lifting specification 2400 that provides components required to produce the desired products of aggregate lifting specification 2300 i.e. it determines the amount of blending products required to produce the completed products, which require different blending components which would affect the blending component inventory in Lu [0153] "FIG. 24 is a graphical representation of an aggregate lifting specification 2400 that provides the individual components that will be necessary to produce the desired products shown in the aggregate lifting specification 2300. The vertical axis provides an indication of volume, in this case barrels, while the horizontal axis provides an indication of individual intermediate components. In this particular example, the intermediate components include FCC gas 2402, reformate 2404, C4 2406, alkylate 2408, straight run gas 2410 and C18 2412. It will be appreciated that there may be a number of additional intermediate components that, for simplicity, are not illustrated in the aggregate lifting specification 2400.").
Claim 11:
Lu teaches “A method for controlling an industrial process, the method comprising: at a device with a processor and a memory comprising one or more instructions:” (Lu teaches controllers including processing devices 142 and memories 144 for storing instructions used by the processing devices 142 in Lu [0055] "In particular embodiments, the various controllers and operator stations in FIG. 1 may represent computing devices. For example, each of the controllers 106, 114, 122, 130, 138 could include one or more processing devices 142 and one or more memories 144 for storing instructions and data used, generated, or collected by the processing device(s) 142. Each of the controllers 106, 114, 122, 130, 138 could also include at least one network interface 146, such as one or more Ethernet interfaces or wireless transceivers. Also, each of the operator stations 116, 124, 132, 140 could include one or more processing devices 148 and one or more memories 150 for storing instructions and data used, generated, or collected by the processing device(s) 148. Each of the operator stations 116, 124, 132, 140 could also include at least one network interface 152, such as one or more Ethernet interfaces or wireless transceivers."),
“receiving an optimization request to optimize an industrial process that produces an industrial process product;” (Lu teaches that in an example, if there is a high demand for a product A higher than product B, it may be lucrative to use memory chips only for product A, which would cause the timeline of production of product A to be finished earlier i.e. if the existing time data for production of product A is too late, it can reoptimize such that production of product A finishes earlier in Lu [0145] "As an example, the final product may be any of a number of different computer products. One of the intermediate components may be a memory chip. It will be appreciated that the memory chips are produced in a lengthy process that includes semiconductor fabrication. This lengthy process may be considered as a continuous or nearly continuous process. A particular brand and model of memory chip may be used during the assembly of any of a variety of different computer products. It will be appreciated that assembly of a particular computer product occurs over a different time frame than the production of the memory chip that is used in assembling a particular computer representing that particular computer product. If there is a high demand for computer product A, and a lower demand for computer product B, it may be more lucrative to use more of the memory chips in assembly computers of product A, and not to assembly any (or very many) computers of product B."),
“and in response to the optimization request: determining, by the processor, a first time period to produce the industrial process product to fulfill one or more orders;” (Lu teaches a master MPC controller 302 that optimizes planning, controlling inventories, manufacturing activities, or product qualities in Lu [0074] "Each MPC controller 302, 304 a-304 n supports economic optimization and multivariable control functions. The master MPC controller 302 uses a planning model 200 (such as a yield-based single-period planning model) to provide an initial steady-state gain matrix, and relevant model dynamics can be determined using operating data of the plant (such as historical data). The master MPC controller 302 operates to control product inventories, manufacturing activities, or product qualities within the plant. The embedded economic optimizer of the master MPC controller 302, which is furnished with the same planning model structure and economics, could therefore reproduce the single-period offline planning optimization but in an online and real-time manner."; Lu teaches that the master MPC controller 302 optimizes the plant, generating the best achievable plan in Lu [0078] "The master MPC controller 302 is a real-time plan executor that understands the big picture from the planning model 200 and uses each unit's MPC models 250 for advanced process control. The master MPC controller 302 can therefore optimize the plant in concert with the slave MPC controllers 304 a-304 n, generating the best-achievable plan while honoring all units' constraints."; Lu teaches determining a time frame for a final product produced in a batch process i.e. an order in Lu [0144] "In some cases, the concepts of intermediate components 2004 being produced in a continuous process such as the continuous process 2006 while final products 2008 are produced in a discontinuous process (e.g. batch process) such as the discontinuous process 2010 may be applicable to a number of other industries. In some cases, intermediate components such as the intermediate components 2004 may be produced during a process that runs over a first time frame. Final products, such as the final products 2008, may be produced during another process that runs over a second time frame that is different from the first time frame. In some cases, the second time frame may at least partially overlap the first time frame, but this is not required. The second time frame may occur immediately after the first time frame, or in some cases the second time frame may occur at some time in the future subsequent to the first time frame."),
“determining, by the processor, an optimization time period, wherein the optimization time period is less the first time period;” (Lu teaches that in an example, if there is a high demand for a product A higher than product B, it may be lucrative to use memory chips i.e. intermediate products only for product A i.e. final products, which would cause the timeline of production of product A to be finished earlier i.e. an optimization time period in Lu [0145] "As an example, the final product may be any of a number of different computer products. One of the intermediate components may be a memory chip. It will be appreciated that the memory chips are produced in a lengthy process that includes semiconductor fabrication. This lengthy process may be considered as a continuous or nearly continuous process. A particular brand and model of memory chip may be used during the assembly of any of a variety of different computer products. It will be appreciated that assembly of a particular computer product occurs over a different time frame than the production of the memory chip that is used in assembling a particular computer representing that particular computer product. If there is a high demand for computer product A, and a lower demand for computer product B, it may be more lucrative to use more of the memory chips in assembly computers of product A, and not to assembly any (or very many) computers of product B."; Lu teaches that raw ingredients 2002 may be crude oil, intermediate components 2004 may be blending components, final products 2008 may be fuel products i.e. rather than the computer components mentioned in Lu [0145], the prioritization of a product may be applied to oil production in Lu [0142-0143] "It will be appreciated that much of this disclosure pertains to the production of petroleum products from blending components that are produced from petroleum stocks. Some of all of these blending components may be considered as being distillation column products. The raw ingredients 2002 may be crude oil, which can of course vary considerably in its individual molecules and molecular distribution, may enter a distillation column at an oil refinery or related facility. A variety of different blends of molecules may be pulled off of the distillation column. Relatively lighter blends (smaller molecular weight molecules) may be pulled off towards the top of the distillation column while relatively higher blends (larger molecular weight molecules) may be pulled off at relatively lower levels on the distillation column. Some of these blends may be ready to be used at this stage in creating final products, while others of these blends may still need to go through additional processing within an oil refinery or similar facility before they are ready to be used in creating final products. The blends, whether ready immediately post-distillation, or after additional processing, may be considered as being blending components, which are an example of the intermediate components 2004. The blending components may be blended using a variety of different recipes into a number of final products 2008. The final products 2008 may, in the case of an oil refinery, include fuel products such as but not limited to regular gasoline, premium gasoline, aviation fuel, diesel fuel, fuel oil and others."),
"in response to determining the optimization time period: updating, by the processor, industrial process product characteristics based on at least the first time period and the optimization time period;" (Lu teaches that in an example, if there is a high demand for a product A higher than product B, it may be lucrative to use memory chips i.e. intermediate products only for product A i.e. final products, which would cause the timeline of production of product A to be finished earlier i.e. the process product characteristics would be updated to produce more of product A in Lu [0145] "As an example, the final product may be any of a number of different computer products. One of the intermediate components may be a memory chip. It will be appreciated that the memory chips are produced in a lengthy process that includes semiconductor fabrication. This lengthy process may be considered as a continuous or nearly continuous process. A particular brand and model of memory chip may be used during the assembly of any of a variety of different computer products. It will be appreciated that assembly of a particular computer product occurs over a different time frame than the production of the memory chip that is used in assembling a particular computer representing that particular computer product. If there is a high demand for computer product A, and a lower demand for computer product B, it may be more lucrative to use more of the memory chips in assembly computers of product A, and not to assembly any (or very many) computers of product B."),
“updating, by the processor, blending component characteristics indicative of availability of one or more blending components for the batch process based on the updated industrial process product characteristics, the first time period, and the optimization time period;” (Lu teaches that the disclosure pertains to production of petroleum products from blending components in Lu [0142] "It will be appreciated that much of this disclosure pertains to the production of petroleum products from blending components that are produced from petroleum stocks. Some of all of these blending components may be considered as being distillation column products. The raw ingredients 2002 may be crude oil, which can of course vary considerably in its individual molecules and molecular distribution, may enter a distillation column at an oil refinery or related facility. A variety of different blends of molecules may be pulled off of the distillation column. Relatively lighter blends (smaller molecular weight molecules) may be pulled off towards the top of the distillation column while relatively higher blends (larger molecular weight molecules) may be pulled off at relatively lower levels on the distillation column."; Lu teaches that intermediate components (computer chip A) i.e. blending component may be influenced by the demand of computer product A i.e. the planned production of product A which is affected by the time periods may affect the planned production of processor chip A, which may be regarded as blending components in Lu [0146] "As a related example, two of the intermediate components may be processor chips. Processor chip A is only used in computer product A, and processor chip B is only used in computer product B. It will be appreciated that the relative demand for computer product A and computer product B as final products may influence the earlier production of the intermediate components. It is helpful to take into account what final product(s) may be produced, or are desired, when determining how to allocate raw ingredients, energy consumption, labor costs and the like when planning production of intermediate components."),
“updating, by the processor, demand data for the one or more feed products utilized for blending the one or more blending products based on the product spent characteristics;” (Lu teaches a method for optimizing continuous conversion of initial components i.e. feed products into blending components, which would require updating the demand for initial components as blending component demands are updated in Lu [0167] "An optimization is performed that includes the continuous conversion of initial components into the plurality of blending components as well as subsequent production of the plurality of desired fuel products, subject to the constraints on each of one or more of the initial components, the constraints on each of the plurality of blending components, the recipe for each of the plurality of desired fuel products, and the quantity of each of the plurality of desired fuel products to be produced, as indicated at block 2808."), and
“transmitting, by the processor, a control signal to control the flow of the feed component in the continuous process.” (Lu teaches a method for optimizing continuous conversion of initial components into blending components that are used to make desired fuel products, which involves controlling the continuous manufacturing process based on the optimization i.e. it transmits a control signal to control flow of feed components in Lu [0167] "FIG. 28 is a flow diagram showing an illustrative method 2800 for optimizing continuous conversion of initial components into a plurality of blending components that are then used as inputs to make a plurality of desired fuel products. Constrains are received on each of one or more of the initial components, as indicated at block 2802. Constraints are received on each of the plurality of blending components (e.g. intermediate components), as indicated at block 2804. Information is received on the plurality of desired fuel products to be produced from the plurality of blending components including a quantity of each of the plurality of desired fuel products to be produced and one or more recipes that specifies how the plurality of blending components are to be combined to form each of the plurality of desired fuel products, as indicated at block 2806. An optimization is performed that includes the continuous conversion of initial components into the plurality of blending components as well as subsequent production of the plurality of desired fuel products, subject to the constraints on each of one or more of the initial components, the constraints on each of the plurality of blending components, the recipe for each of the plurality of desired fuel products, and the quantity of each of the plurality of desired fuel products to be produced, as indicated at block 2808. In some cases, the optimization may be performed using equation (32) or the like. The continuous manufacturing process and the subsequent production of the plurality of desired fuel petroleum-based products may be controlled based at least in part upon the optimization, as indicated at block 2810.").
Lu does not appear to explicitly teach “in response to completing the production of the industrial process product for an order of the one or more orders, determining product spent characteristics associated with the one or more blending products;” However, Polarine does teach this claim limitation (Polarine teaches that each dispensing cycle i.e. after completion of production of industrial process product, the inventory will be updated to deduct inventory of dispensed quantities of stock components i.e. determine product spent characteristics associated with blending products in Polarine [0098] "Means 60 for configuring computer readable program code devices to cause client computer 10 or host computer 12 to generate an updated inventory. As shown in FIG. 5, means 60 comprise means 62 for configuring computer readable program code devices to cause client computer 10 or host computer 12 to (a) deduct from the current inventory dispensed quantities of the stock composition, the stock components, or a combination thereof to generate an adjusted current inventory; (b) deduct from the supplementary inventory dispensed additional quantities of the stock composition, dispensed quantities of the missing stock components, or a combination thereof, to generate an adjusted supplementary inventory; and (c) add the adjusted current inventory and the adjusted supplementary inventory. The aforementioned sum then becomes the updated inventory. It should be noted the updated inventory would then become the stored inventory in the subsequent dispensing cycle.").
Lu and Polarine are analogous art because they are from the same field of controlling and monitoring production. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Lu and Polarine before him/her, to modify the teachings of an Plant-wide optimization including batch operations of Lu to include the updating of inventory each cycle of Polarine because adding the Monitoring device used for producing compositions of Polarine would ensure the product quality of the composition and reduce costs as described in Polarine [0171-0172] “The process and the device of the present invention helps in eliminating the dispensing of poor quality substitution of components listed in the formula, thereby preventing the production of sub-standard compositions... As the contents in the container are consumed, an updated inventory can be transmitted to the manufacturer by allowing the manufacturer access to client computer 10 or host computer 12, which can be alternatively operated by the manufacturer. The updated inventory then becomes the current inventory in the subsequent dispensing cycle provided the user, such as a collision repair shop, makes no unauthorized additions or deletions to the current inventory. Thus, the process of the present invention helps in ensuring the product quality of the composition. Additionally, since the manufacturer is aware of which component has been used up, the manufacturer can automatically augment the user with those depleted components without any formal request from the user, thereby reducing the time require to supply the components consumed by the user. Moreover, the manufacturer can also assist the user in reducing his inventory by supplying the components, just in time as they are used up. Moreover, the manufacturer can also bill the user on an “as-used-basis” for the cost of only the stock composition or components actually consumed. As a result, the user's out-of-pocket cost can be reduced.”
Claim 12:
The limitations of claim 12 are substantially the same as claim 2 and it is rejected for the same reasons.
Claim 13:
The limitations of claim 13 are substantially the same as claim 3 and it is rejected for the same reasons.
Claim 14:
The limitations of claim 14 are substantially the same as claim 4 and it is rejected for the same reasons.
Claim 16:
The limitations of claim 16 are substantially the same as claim 6 and it is rejected for the same reasons.
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Lu (US20210132591A1), in view of Polarine (US20050197930A1), further in view of Kocis et al. (US20140379112A1).
Claim 6:
Lu in view of Polarine teaches “The system of claim 3,” as described above. Neither Lu or Polarine appear to explicitly teach “wherein the processor is further configured to utilize the asynchronous update scheme to determine the product spent characteristics associated with the one or more blending products based on the industrial process product characteristics to produce the industrial process product.” However, Kocis does teach this claim limitation (Kocis teaches an asynchronous update scheme which may provide inventory level calculations i.e. product spent characteristics in Kocis [0108] "Building upon the approach defined above, the methodology for handling time intervals and scheduling calculations is as follows. The scheduling of process operations for the production entities is performed on the basis of time intervals that are specific to the individual production entities. The scheduling of other activities, such as purchases or sales, is also performed on the basis of the time intervals that are specific to the individual production entities. Inventory level calculations in the tanks can provide the interface between other production entities (including the virtual production activities of purchases and sales) which can have asynchronous schedules.").
Lu, Polarine, and Kocis are analogous art because they are from the same field of controlling and monitoring production. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Lu, Polarine, and Kocis before him/her, to modify the teachings of an Plant-wide optimization including batch operations of Lu modified to include the updating of inventory each cycle of Polarine to include the asynchronous update scheme providing inventory level calculations of Kocis because adding the modeling tool for planning the operation of refineries of Kocis would allow the asynchronous time interval model to solve simultaneous planning and scheduling optimization models to be coupled as described in Kocis [0138] “Alternatively, a single-period version of the facility model can be solved repeatedly for each simulation time period (e.g. 1 minute, 5 minutes, 10 minutes, etc). This calculation can be performed as the solution of a square system of equations for the production facility. Alternatively, a sequence of production entity and tank submodels can be solved where the sequence follows the flow of material through the production facility. The calculations are repeated for each simulation time period until the time horizon is simulated completely. In this case, the time horizon may be divided into a greater number of time intervals of shorter duration compared to the time intervals that would be preferred for optimization purposes, A finer representation of time may be desirable to report the operation of the facility and all the production entities, These shorter and greater number of simulation time slices can be feasible since the simulation calculations are less computationally demanding than the solution of the corresponding optimization model. With this approach, the optimization functionality of the asynchronous time interval model to solve simultaneous planning and scheduling optimization models can be coupled with detailed scheduling simulation functionality.”
Claim 16:
The limitations of claim 16 are substantially the same as claim 6 and it is rejected for the same reasons.
Claims 7-9 and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Lu (US20210132591A1), in view of Polarine (US20050197930A1), further in view of Varvarezos et al. (US20120296690A1).
Claim 7:
Lu in view of Polarine teaches “The system of claim 1,” as described above. Neither Lu or Polarine appear to explicitly teach “wherein utilization of the one or more feed products is measured by determining the one or more blending products, the product spent characteristics, and then back-calculating the product feed products.” However, Varvarezos does teach this claim limitation (Varvarezos teaches an equation for determining the volume of a component contributing to a blend i.e. it determines the feed product used for a blend based on the product used in the blend in Varvarezos [0091] "5) Equation (12) defines the total volume of component (c) contributing to blend (b) in the time horizon. Equation (13) defines the total property barrels (i) for component (c) in blend (b) in the time horizon. These equations take into account the special handling of the start and stop periods."
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Lu, Polarine, and Varvarezos are analogous art because they are from the same field of controlling and monitoring production. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Lu, Polarine, and Varvarezos before him/her, to modify the teachings of an Plant-wide optimization including batch operations of Lu modified to include the updating of inventory each cycle of Polarine to include the determination of volume of components contributed to blends of Varvarezos because adding the rundown blending optimization apparatus of Varvarezos would optimize event volumes simultaneously with blend recipes, which a person having ordinary skill in the art would recognize as an improvement to operation of the refinery as described in Varvarezos [0022] “Historical Aspen MBO was subsequently improved to overcome the above limitations by a rigorous approach to modeling and solving the blending problem that removes the simplifications stated above. Improved Aspen MBO technology resulted. In the improved Aspen MBO technology, first, the number and duration of event periods are determined automatically by the intersection of all the events in the campaign (such as component changes, blends, shipments, receipts or transfers). Second, all the nonlinear properties are calculated properly using a nonlinear blending library. In addition, the users can provide their own proprietary blending correlations. Lastly, all event volumes (blend, shipment, receipt and transfer) are optimized simultaneously with the blend recipes. The modeling formulation provides an event-driven, accurate and detailed representation of the blending operations of any complex refinery.”
Claim 8:
Lu in view of Polarine further in view of Varvarezos teaches “The system of claim 7, wherein the processor is further configured to update the demand data for the one or more feed products utilized for blending the one or more blending components based on the product spent characteristics” (Lu teaches a method for optimizing continuous conversion of initial components i.e. feed products into blending components that are used to make desired fuel products, which would update the demand data for the initial components in Lu [0167] "FIG. 28 is a flow diagram showing an illustrative method 2800 for optimizing continuous conversion of initial components into a plurality of blending components that are then used as inputs to make a plurality of desired fuel products. Constrains are received on each of one or more of the initial components, as indicated at block 2802. Constraints are received on each of the plurality of blending components (e.g. intermediate components), as indicated at block 2804. Information is received on the plurality of desired fuel products to be produced from the plurality of blending components including a quantity of each of the plurality of desired fuel products to be produced and one or more recipes that specifies how the plurality of blending components are to be combined to form each of the plurality of desired fuel products, as indicated at block 2806. An optimization is performed that includes the continuous conversion of initial components into the plurality of blending components as well as subsequent production of the plurality of desired fuel products, subject to the constraints on each of one or more of the initial components, the constraints on each of the plurality of blending components, the recipe for each of the plurality of desired fuel products, and the quantity of each of the plurality of desired fuel products to be produced, as indicated at block 2808. In some cases, the optimization may be performed using equation (32) or the like. The continuous manufacturing process and the subsequent production of the plurality of desired fuel petroleum-based products may be controlled based at least in part upon the optimization, as indicated at block 2810."), and
“and in response to updating the demand data, reset the first time period.” (Lu teaches production inventories and product properties can be controlled dynamically with real-time measurement feedback i.e. when demand data is updated, it may reset the time horizon in Lu [0077] "Certain optimization settings can also be modified from conventional MPC optimization settings in order to capture additional benefits in real-time. Some similarities and differences between the traditional MPC approach and the cascaded MPC solution could include the following: The objective function can remain the same as in the offline planning counterpart. The time horizon in the master MPC controller 302 can be an online tuning parameter, such as one ranging from several hours to several days or weeks, and it can be shorter than the time horizon used in offline (particularly multi-period) planning The tuning can be set to capture more benefits in the form of just-in-time manufacturing. Considerations for tuning may include (as examples) how far in advance product orders are placed, the variance of product orders (both in quantities and grades), what additional buy/sell opportunities can be pursued, and what semi-finished components can be exchanged with partners or bought/sold on the spot market. Production inventories and product properties can be controlled dynamically with real-time measurement feedback. Product orders within the time horizon are known, as opposed to being estimated in the offline counterpart. The master MPC controller 302 can produce a just-in-time production plan as opposed to a plan based on assumed orders. The planning model 200 used in the master MPC controller 302 can be updated in real-time with a yield validation mechanism associated with the slave MPC controllers 304 a-304 n. After cross-validation (such as for metering errors), measured yields can be used to update the planning model 200, and the master MPC controller 302 can generate a more accurate profitable production plan.").
Claim 9:
Lu in view of Polarine further in view of Varvarezos teaches “The system of claim 8, wherein the processor is further configured to update the demand data by updating one or more portions of the demand data in response to a change in demand for the industrial process product.” (Lu teaches that intermediate components (computer chip A) i.e. blending component may be influenced by the demand of computer product A i.e. the planned production of product A, which may be the industrial process product, may affect the planned production of processor chip A in Lu [0146] "As a related example, two of the intermediate components may be processor chips. Processor chip A is only used in computer product A, and processor chip B is only used in computer product B. It will be appreciated that the relative demand for computer product A and computer product B as final products may influence the earlier production of the intermediate components. It is helpful to take into account what final product(s) may be produced, or are desired, when determining how to allocate raw ingredients, energy consumption, labor costs and the like when planning production of intermediate components.").
Claim 17:
The limitations of claim 17 are substantially the same as claim 7 and it is rejected for the same reasons.
Claim 18:
The limitations of claim 18 are substantially the same as claim 8 and it is rejected for the same reasons.
Claim 19:
The limitations of claim 19 are substantially the same as claim 9 and it is rejected for the same reasons.
Claims 10 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Lu (US20210132591A1), in view of Polarine (US20050197930A1), further in view of Varvarezos et al. (US20120296690A1), further in view of Welch et al. (US5712481A).
Claim 10:
Lu in view of Polarine, further in view of Varvarezos teaches “The system of claim 9,” as described above. None of Lu, Polarine, or Varvarezos appear to explicitly teach “the processor is further configured to generate one or more batch blending recipes based on the updated demand data.” However, Welch does teach this claim limitation (Welch teaches that a blending recipe is continuously optimized i.e. the recipe will be updated when demand data changes in Welch [Column 9 line 66 - Column 10 line 17] "In FIG. 4, the use of multistreaming, whereby the component streams are switched sequentially to a single probe using valves, is illustrated; however, multiplexing, whereby a probe is located at each control point; or a combination of both; can also be used. In a multistreaming operation such as that illustrated in FIG. 4, components 410, 420, 430, 440, 450 and 460 are sequentially routed to the sample cell or sample probe of NIR 470 which analyzes each stream for properties or components of interest (e.g., benzene). A signal for each stream (proportional to vol % benzene) is then transmitted to optimizing software such as GINO. The GINO software, resident in blending computer 480, then continuously optimize and update the blend recipe, then downloads the updated recipe to Blend Ratio Control (BRC) software which is resident in Distributed Control System (DCS) 490. The BRC software is capable of controlling DCS 490 which in turn adjusts the position of valves 405, 415, 425, 415, 445, and 455 to change the flow rates of components 410, 420, 430, 440, 450 and 460, respectively.").
Lu, Polarine, Varvarezos, and Welch are analogous art because they are from the same field of controlling and monitoring production. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Lu, Polarine, Varvarezos, and Welch before him/her, to modify the teachings of an Plant-wide optimization including batch operations of Lu modified to include the updating of inventory each cycle of Polarine, further modified to include the determination of volume of components contributed to blends of Varvarezos to include the continuous blending recipe optimization of Welch because adding the continuous optimization of blending recipes of Welch would allow for the recipes to be constantly updated, which a person having ordinary skill in the art would recognize as an improvement to the refining process as described in Welch [Column 9 line 66 - Column 10 line 17] "In FIG. 4, the use of multistreaming, whereby the component streams are switched sequentially to a single probe using valves, is illustrated; however, multiplexing, whereby a probe is located at each control point; or a combination of both; can also be used. In a multistreaming operation such as that illustrated in FIG. 4, components 410, 420, 430, 440, 450 and 460 are sequentially routed to the sample cell or sample probe of NIR 470 which analyzes each stream for properties or components of interest (e.g., benzene). A signal for each stream (proportional to vol % benzene) is then transmitted to optimizing software such as GINO. The GINO software, resident in blending computer 480, then continuously optimize and update the blend recipe, then downloads the updated recipe to Blend Ratio Control (BRC) software which is resident in Distributed Control System (DCS) 490. The BRC software is capable of controlling DCS 490 which in turn adjusts the position of valves 405, 415, 425, 415, 445, and 455 to change the flow rates of components 410, 420, 430, 440, 450 and 460, respectively."
Claim 20:
The limitations of claim 20 are substantially the same as claim 10 and it is rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wadha et al. (US20140194657A1) teaches recipes that are optimized on a day-to-day basis in Wadha [0058] "FIG. 5(A) shows a system where property data is available for 4 streams, every day and FIG. 5(B) shows that component stream proportions (recipes) are changed/optimized on a day-to-day basis.”
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Lehman et al. (US20060230787A1) teaches batch formulation software may appropriate amounts of raw materials to satisfy a recipe in Lehman [0042] "Alternatively, batch formulation software 126, in operative communication with batch controller 122, may meter in real-time, and otherwise deliver, appropriate amounts of virgin raw materials from material supply 260 to satisfy the recalculated batch recipe. "
Mu et al. (US20160042074A1) teaches continuous recipe optimization for an oil refinery at the beginning of each batch cycle or in fixed frequency in Mu [0080] "The inputs of the recipe optimization (RO) system are receiving information from different systems include the LIMS, the historian, and the tank gauging system. Particularly, the lab quality analysis results of both component tank and the product tank heel oil quality should be from the LIMS at the beginning of each blending batch cycle or in fixed frequency for continuous process. The component tank volume and product tank heel volume should be either from the historian or tank gauging system directly at the beginning of each blending batch cycle or in fixed frequency for continuous process. The communication between each system could be through OPC (OLE for process control) client or flat file exchange in the agreed format. The other information of the recipe optimization (RO) system such as the tank capacity, different limitations, optimization target, product oil quality specification, etc. should be defined in the recipe optimization RO server by a system user using the user interface 20. The outputs of the recipe optimization (RO) system, including the best recipe ratio and rate from each component tank to each product tank, the optimized target value, the predicted product oil quality, would be displayed in the recipe optimization (RO) server monitor, and the instructions of the recommended recipe ratio could be downloaded to the OMS/BOM for implementation at the beginning of each blending batch cycle or in fixed frequency for continuous process."
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Zachary A Cain whose telephone number is (571)272-4503. The examiner can normally be reached Mon-Fri 7:00-3:30 CST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kenneth M Lo can be reached at (571) 272-9774. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Z.A.C./ Examiner, Art Unit 2116
/KENNETH M LO/ Supervisory Patent Examiner, Art Unit 2116