Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 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.
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter.
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a software per se. The claim does not fall within at least one of the four categories of patent eligible subject matter because a computer program product is not a patentable subject matter. In the claim, “a computer program product” is not described as being embodied on a statutory medium in the specification, in which case the computer program product may be software per se. Such a recitation does not exclude the computer program product from being a software per se. Thus, the broadest, reasonable interpretation of the “a computer program product” in view of the specification encompasses non-statutory subject matter that is unpatentable under 35 USC 101.
Claims 1-2, and 4-16, and 18-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “selecting a pre-determined number of at least one of the multitude of process parameters based on determining, for a first product quantity of beer having undergone a first processing step as part of a brewing process, a first relation between a set of process parameters of the first processing step and at least one first product component parameter and/or a second relation between a set of ingredient parameters and at least one first product component parameter”, “identifying the at least one first product component potentially present in the first product quantity”, and “based on the multitude of process parameter values the multitude of ingredient parameter values and the first product component parameter value, determining a first relation score indicative of the first relation between each of the multitude of process parameter values and the first product component parameter value and/or a second relation score indicative of the second relation between each of the multitude of the ingredient parameter values and the first product component parameter value, and selecting the pre-determined number of at least one of the multitude of process parameters and the multitude of ingredient parameters having relation scores indicating strongest relation with the first product component parameter value”
The limitations of “selecting a pre-determined number of at least one of the multitude of process parameters based on determining, for a first product quantity of beer having undergone a first processing step as part of a brewing process, a first relation between a set of process parameters of the first processing step and at least one first product component parameter and/or a second relation between a set of ingredient parameters and at least one first product component parameter”, “identifying the at least one first product component potentially present in the first product quantity”, and “based on the multitude of process parameter values the multitude of ingredient parameter values and the first product component parameter value, determining a first relation score indicative of the first relation between each of the multitude of process parameter values and the first product component parameter value and/or a second relation score indicative of the second relation between each of the multitude of the ingredient parameter values and the first product component parameter value, and selecting the pre-determined number of at least one of the multitude of process parameters and the multitude of ingredient parameters having relation scores indicating strongest relation with the first product component parameter value” are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example language, “selecting”, “identifying” and “determining” in the context of this claim encompasses that the user mentally could make a decision, observation, and comparison. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements- “obtaining at least one first product component parameter value for the first product quantity related to the first product component; the method further comprising: at least one of obtaining, from a process data acquisition control system, process data comprising a multitude of process parameter values related to the first processing step of the first product quantity and obtaining from the process data acquisition control system, ingredient data comprising a multitude of ingredient parameter values related to a multitude of ingredients forming a basis for the first product quantity” which are simply insignificant extra solution activity of data gathering and transmission by acquiring data and information, the claim also recites elements- “A method executable by an electronic process analysis device, of” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Accordingly these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of transmitting data which is simply insignificant extra solution activity of a controller receiving data from a sensor which is considered to be well-understood, routine, conventional activity. The claim also recites elements- “A method executable by an electronic process analysis device, of”, which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 2 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “wherein the determining of the first relation score and/or the second relation score is also based on the at least one of the second process parameter value and the second ingredient parameter value” which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. Additionally the claim recites- “obtaining, from a process data acquisition control system, process data comprising at least one second process parameter value related to the second processing step of a second product quantity and obtaining, from the process data acquisition control system, ingredient data comprising at least one second ingredient parameter value related to the ingredient forming a basis for the second product quantity;” which is simply insignificant extra solution activity of data gathering and transmitting which is considered to be well-understood, routine, conventional activity. Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “wherein the brewing process comprises batch processing and wherein the first product quantity comprises at least one batch” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “wherein at least one of: the first process parameter value has a first process parameter timestamp associate therewith, indicative of a starting point of the first processing step; and the first ingredient parameter value has a first ingredient timestamp associated therewith indicative of a moment in time at which the first ingredient is added to the first product quantity.” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 6 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “wherein the brewing process is a continuous process, further comprising obtaining a throughput time interval of the first processing step indicative of the first product quantity undergoing the first processing step” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “wherein the first process parameter value is one of a control value and a measured value” which falls under field of use and technological environment- see MPEP 2106.05(h) Parker v. Flook ("Flook established that limiting an abstract idea to one field of use or adding token postsolution components did not make the concept patentable"). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “wherein the first ingredient parameter value is one of a weight of an amount of the first ingredient, a volume of the first ingredient and a quality of the first ingredient” which falls under field of use and technological environment- see MPEP 2106.05(h) Parker v. Flook ("Flook established that limiting an abstract idea to one field of use or adding token postsolution components did not make the concept patentable"). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “determining, based on the quality relation and a value of the at least one product component parameter, an objective quality score value of the first product quantity” which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. Additionally the claim recites- “obtaining an objective quality relation between numerical or Boolean quality score parameter data and at least one product component parameter” which is simply insignificant extra solution activity of data gathering and transmitting which is considered to be well-understood, routine, conventional activity. Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “based on the first quality score value, the second quality score value, the at least one first product component parameter value of the first product quantity and at least one second product component parameter value of the second product quantity, determining a quality relation between the first product component parameter and a quality score” which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. Additionally the claim recites- “obtaining a first quality score value for the first product quantity; obtaining a second quality score value for the second product quantity;” which is simply insignificant extra solution activity of data gathering and transmitting which is considered to be well-understood, routine, conventional activity. Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “based on the first quality score value, the second quality score value, at least one process parameter value of the first product quantity and at least one process parameter value of the second product quantity, determining a quality relation between the first product component parameter and a quality score” which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. Additionally the claim recites- “obtaining a first quality score value for the first product quantity; obtaining a second quality score value for the second product quantity;” which is simply insignificant extra solution activity of data gathering and transmitting which is considered to be well-understood, routine, conventional activity. Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “based on the first quality score value, the second quality score value, at least one ingredient parameter value of the first product quantity and at least one ingredient parameter value of the second product quantity, determining a quality relation between the ingredient parameter and a quality score” which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. Additionally the claim recites- “obtaining a first quality score value for the first product quantity; obtaining a second quality score value for the second product quantity” which is simply insignificant extra solution activity of data gathering and transmitting which is considered to be well-understood, routine, conventional activity. Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “wherein the relation score is indicative of a correlation between parameters between which the relation score is determined” which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits mental abstract ideas from claim 1. Additionally the claim recites- “wherein the obtained first process parameter value and the obtained first ingredient parameter value are provided to a neural network and the relation score is provided by the neural network” which is simply insignificant extra solution activity of data gathering and transmitting which is considered to be well-understood, routine, conventional activity. Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “wherein the first process parameter value is one of: Temperature; Conductivity; Colour; Transparency to visible light; Relative weight: Acidity; Sugar content; Viscosity; Energy added; and Control temperature of a machine executing the first processing step” which falls under field of use and technological environment- see MPEP 2106.05(h) Parker v. Flook ("Flook established that limiting an abstract idea to one field of use or adding token postsolution components did not make the concept patentable"). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “wherein the first product component parameter is at least one of the following: ethanol content; methanol content; sugar content; and carbon dioxide content” which falls under field of use and technological environment- see MPEP 2106.05(h) Parker v. Flook ("Flook established that limiting an abstract idea to one field of use or adding token postsolution components did not make the concept patentable"). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible.
Claim 18 is rejected under 35 U.S.C. 101 for similar reasons to claim 1.
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “A computer program product comprising computer executable code arranged to cause a computer, when the executable code is loaded in a memory connected to an electronic processing unit comprised by the computer for programming the electronic processing unit, to execute the method according to claim 1” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is 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.
Claim(s) 1-2, 4-16, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Blevins et al. US20100318934, herein Blevins), Lynn et al. (US20210265036, herein Lynn), and Mitchell et al. (US20170130178, herein Mitchell).
Regarding claim 1, Blevins teaches A method executable by an electronic process analysis device, of selecting a pre-determined number of at least one of the multitude of process parameters based on determining, for a first product quantity of … having undergone a first processing step as part of a …process ([0030] a process overview chart may display the status of one or more processes being monitored. From this overview chart, an operator may select a process variation graph showing any explained (e.g., modeled) and/or unexplained (e.g., un-modeled) variations within the process,[0025] process control systems provide analytic and/or statistical analysis of process control information), a first relation between a set of process parameters of the first processing step and at least one first product component parameter and/or a second relation between a set of ingredient parameters and at least one first product component parameter ([0030] The example OMS may determine contribution relationships between process and/or quality variables based on modeling and/or analyzing the process control system, [0038] The measured quality variables may be associated with process control information related to measuring characteristics of the process that are associated with at least a portion of a completed product) , the method comprising: identifying the at least one first product component potentially present in the first product quantity; and obtaining at least one first product component parameter value for the first product quantity related to the first product component ([0041] The analytic processor 114 may detect, identify, and/or diagnose process operation faults and predict the impact of any faults on quality variables and/or an overall quality variable associated with a quality of a resultant product of the process control system 106. Furthermore, the analytic processor 114 may monitor the quality of the process by statistically and/or logically combining quality and/or process variables into an overall quality variable associated with the overall quality of the process. The analytic processor 114 may then compare the values calculated for the overall quality variable and/or values associated with the other quality variables to respective thresholds) ; the method further comprising: at least one of obtaining, from a process data acquisition control system process data comprising a multitude of process parameter values related to the first processing step of the first product quantity and ([0041] The analytic processor 114 may detect, identify, and/or diagnose process operation faults and predict the impact of any faults on quality variables and/or an overall quality variable associated with a quality of a resultant product of the process control system 106. Furthermore, the analytic processor 114 may monitor the quality of the process by statistically and/or logically combining quality and/or process variables into an overall quality variable associated with the overall quality of the process. The analytic processor 114 may then compare the values calculated for the overall quality variable and/or values associated with the other quality variables to respective thresholds, [0100] The overview chart 502 is organized by process area and includes a state of a first process area (e.g., Process Area 1) and a second process area (e.g., Process Area 2). The first process area may correspond to the process control system 106. Each process area includes information associated with current and/or previous batches that may be used to alert a process control operator when a fault is detected), obtaining, from the process data acquisition control system ingredient data comprising a multitude of ingredient parameter values related to a multitude of ingredients forming a basis for the first product quantity; based on the multitude of process parameter values the multitude of ingredient parameter values and the first product component parameter value, determining a first relation score indicative of the first relation between each of the multitude of process parameter values and the first product component parameter value (Fig.11,[0030] The example OMS may determine contribution relationships between process and/or quality variables based on modeling and/or analyzing the process control system, [0038] The measured quality variables may be associated with process control information related to measuring characteristics of the process that are associated with at least a portion of a completed product,[0040] model and/or determine relationships between the measured process variables and/or quality variables associated with the process control system 106. These relationships between the measured process and/or quality variables may produce one or more calculated quality variables) and/or a second relation score indicative of the second relation between each of the multitude of the ingredient parameter values and the first product component parameter value, and selecting the pre-determined number of at least one of the multitude of process parameters (Fig. 11[0030] a process overview chart may display the status of one or more processes being monitored. From this overview chart, an operator may select a process variation graph showing any explained (e.g., modeled) and/or unexplained (e.g., un-modeled) variations within the process, [0041] the analytic processor 114 may then compare the values calculated for the overall quality variable and/or values associated with the other quality variables to respective thresholds. These thresholds may be based on the predetermined quality limits of the overall quality variable at different times within the process. For example, if an overall quality variable associated with a process exceeds a threshold for an amount of time, the predicted final quality of the resulting product may not meet quality metrics associated with the finished product, [0117] The variable trend graph 510 may be used by a process control operator to compare a process variable trend during the current batch process to trends of the variable during previous batch processes that finished with a product within quality thresholds ).
Blevins does not teach beer… brewing… the multitude of ingredients parameters having relation scores indicating strongest relations with the first product component parameter value
Mitchell teaches beer… brewing… ([0007] beer brewing system may adjust a brewing session based on data collected during the brewing session)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Blevin’s teaching of predicting process quality in a process control system using control and measured variables with Mitchell’s teaching of beer brewing system. The combined teaching provides an expected result of predicting process quality in a process control beer brewing system using control and measured variables. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
The combination of Blevins and Mitchell do not teach the multitude of ingredients parameters having relation scores indicating strongest relations with the first product component parameter value
Lynn teaches the multitude of ingredients parameters having relation scores indicating strongest relations with the first product component parameter value ([0025] The ranking engine 120 receives input data 150 (e.g., ingredients, ingredient property data, customer/consumer/user preference data, and the like), in one or more embodiments. The ingredient property data may include an identifier or name of the ingredient, one or more food type indicators (e.g., meat, non-meat protein, dairy, vegetable/vegetarian, fruit, gluten-free, nut-free, or a combination thereof), one or more nutritional values (e.g., values for vitamins, minerals, sodium, sugars, fats, cholesterol, carbohydrates, protein, fiber, and the like, expressed for instance in grams or milligrams per serving, as a percentage of daily recommended value, etc.), one or more functional benefit indicators (e.g., heart, cognitive, metabolism), and/or one or more functional risk indicators (e.g., heart, cognitive, metabolism). The nutritional values can be for a normalized unit of mass (e.g., 100 grams) or weight (e.g., 1 ounce). The ingredient property data, as well as customer/consumer/user preference data, market data, or any other data, can be stored in storage (e.g., cloud storage, local storage, object storage, database, catalog, relational database, associative database, and the like) included in or associated with the system 100.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 2, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1, further comprising at least one of obtaining, from a process data acquisition control system, process data comprising at least one second process parameter value related to the first processing step of a second product quantity and obtaining, from the process data acquisition control system (Blevins, [0006] a method includes receiving process control information relating to a process at a first time including a first value associated with a first measured variable and a second value associated with a second measured variable. The example method further includes determining if a variation based on the received process control information associated with the process exceeds a threshold and if the variation exceeds the threshold, calculating a first contribution value based on a contribution of the first measured variable to the variation and a second contribution value based on a contribution of the second measured variable to the variation, [0007] apparatus includes a batch data receiver a batch data receiver to receive process control information relating to a process at a first time including a first value associated with a first measured variable and a second value associated with a second measured variable, [0036] the communication components may include I/O cards to receive data from the field devices and convert the data into a communication medium capable of being received by the example controller), wherein the determining of the first relation score and/or the second relation score is also based on the at least one of the second process parameter value and the second ingredient parameter value ([0030] The example OMS may determine contribution relationships between process and/or quality variables based on modeling and/or analyzing the process control system, [0038] The measured quality variables may be associated with process control information related to measuring characteristics of the process that are associated with at least a portion of a completed product)
Lynn further teaches ingredient data comprising at least one second ingredient parameter value related to the ingredient forming a basis for the second product quantity ([0025] The ranking engine 120 receives input data 150 (e.g., ingredients, ingredient property data, customer/consumer/user preference data, and the like), in one or more embodiments. The ingredient property data may include an identifier or name of the ingredient, one or more food type indicators (e.g., meat, non-meat protein, dairy, vegetable/vegetarian, fruit, gluten-free, nut-free, or a combination thereof), one or more nutritional values (e.g., values for vitamins, minerals, sodium, sugars, fats, cholesterol, carbohydrates, protein, fiber, and the like, expressed for instance in grams or milligrams per serving, as a percentage of daily recommended value, etc.), one or more functional benefit indicators (e.g., heart, cognitive, metabolism), and/or one or more functional risk indicators (e.g., heart, cognitive, metabolism). The nutritional values can be for a normalized unit of mass (e.g., 100 grams) or weight (e.g., 1 ounce). The ingredient property data, as well as customer/consumer/user preference data, market data, or any other data, can be stored in storage (e.g., cloud storage, local storage, object storage, database, catalog, relational database, associative database, and the like) included in or associated with the system 100.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 4, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1,
Mitchell further teaches wherein the brewing process comprises batch processing and wherein the first product quantity comprises at least one batch ([0049] Such a system may allow customization and personalization of a batch of beer in a simple, easy to use manner, [0085] a user has a set of ingredients and may be preparing to brew a batch of beer, but the user may wish to have a thicker mouthfeel and less bitterness in the batch. The performance model 220 may be able to hold the ingredient list constant, and make adjustments to the brewing steps to achieve the user's request)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Blevin’s teaching of predicting process quality in a process control system using control and measured variables with Mitchell’s teaching of beer brewing system. The combined teaching provides an expected result of predicting process quality in a process control beer brewing system using control and measured variables. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 5, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1, wherein at least one of: the first process parameter value has a first process parameter timestamp associate therewith, indicative of a starting point of the first processing step and the first … parameter value has a first … time stamp associated therewith indicative of a moment in time at which the first …is added to the first product quantity (Blevins, [0147] The values may be stored based on a time at which the values were generated by the field devices (e.g., using a time stamp), by batch number, and/or by a stage within the batch).
Lynn further teaches ingredients is added ([0006] a new recipe for the target food product that incorporates a select food ingredient from the plurality of food ingredients)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 6, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1,
… further comprising obtaining a throughput time interval of the first processing step indicative of the first product quantity undergoing the first processing step (Blevins, [0028] The process control information is generated by field devices within the process control system and may be configured for, for example, process environment measurements (e.g., temperature, concentration, or pressure sensing), field device measurements (e.g., pump speed, valve position, or line speed), process status measurements, and/or process throughput measurements, [0006] receiving process control information relating to a process at a first time including a first value associated with a first measured variable and a second value associated with a second measured variable ).
Mitchell further teaches wherein the brewing process is a continuous process ([0071] When the measurements 120 may indicate that the desired beer may still be attainable with modifications to the brewing steps 116, the control system 112 may update the brewing steps 116 and continue the brewing process),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Blevin’s teaching of predicting process quality in a process control system using control and measured variables with Mitchell’s teaching of beer brewing system. The combined teaching provides an expected result of predicting process quality in a process control beer brewing system using control and measured variables. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 7, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1, wherein the first process parameter value is one of a control value and a measured value (Blevins, [0006] receiving process control information relating to a process at a first time including a first value associated with a first measured variable and a second value associated with a second measured variable ) .
Regarding claim 8, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1,
Lynn further teaches wherein the first ingredient parameter value is one of a weight of an amount of the first ingredient, a volume of the first ingredient and a quality of the first ingredient ([0025] The ingredient property data may include an identifier or name of the ingredient, one or more food type indicators (e.g., meat, non-meat protein, dairy, vegetable/vegetarian, fruit, gluten-free, nut-free, or a combination thereof), one or more nutritional values (e.g., values for vitamins, minerals, sodium, sugars, fats, cholesterol, carbohydrates, protein, fiber, and the like, expressed for instance in grams or milligrams per serving, as a percentage of daily recommended value, etc.), one or more functional benefit indicators (e.g., heart, cognitive, metabolism), and/or one or more functional risk indicators (e.g., heart, cognitive, metabolism). The nutritional values can be for a normalized unit of mass (e.g., 100 grams) or weight (e.g., 1 ounce), [0028] The ranking engine 120 can determine that the amount of vitamin C provided by an ingredient, apple, is greater than an amount of vitamin C that a customer/consumer/user prefers for any fruit ingredient, [0037] new recipe may include, specify or describe the select ingredient(s), an amount of each select ingredient) .
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 9, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1, further comprising: obtaining an objective quality relation between numerical or Boolean quality score parameter data and at least one product component parameter, and determining, (Blevins, Fig.11,[0030] The example OMS may determine contribution relationships between process and/or quality variables based on modeling and/or analyzing the process control system, [0038] The measured quality variables may be associated with process control information related to measuring characteristics of the process that are associated with at least a portion of a completed product,[0040] model and/or determine relationships between the measured process variables and/or quality variables associated with the process control system 106. These relationships between the measured process and/or quality variables may produce one or more calculated quality variables, [0007] calculate a predicted process quality based on the at least one corrective action at a time after the first time.).
Lynn further teaches based on the quality relation and a value of the at least one product component parameter, and objective quality score value of the first product quantity ([0028] the ranking engine 120 generates an ingredient score for each of the ingredients and generates rankings according to the ingredient scores (e.g., the ingredients are ranked from highest to lowest ingredient scores). In some embodiments, the ranking engine 120 generates a sub-score for each property, or other aspect, of the ingredient (e.g., the flavor, the texture, the cost) and combines or aggregates (e.g., aggregates, sums, adds) the sub-scores to arrive at the ingredient score for the ingredient. In some embodiments, the ranking engine 120 assigns a first score value if the property exceeds a predefined property threshold or a second score value if the property does not exceed the predefined property threshold.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 10, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1, further comprising:
Lynn further teaches obtaining a first quality score value for the first product quantity; obtaining a second quality score value for the second product quantity; based on the first quality score value, the second quality score value, the at least one first product component parameter value of the first product quantity and at least one second product component parameter value of the second product quantity, determining a quality relation between the first product component parameter and a quality score ([0028] the ranking engine 120 generates an ingredient score for each of the ingredients and generates rankings according to the ingredient scores (e.g., the ingredients are ranked from highest to lowest ingredient scores). In some embodiments, the ranking engine 120 generates a sub-score for each property, or other aspect, of the ingredient (e.g., the flavor, the texture, the cost) and combines or aggregates (e.g., aggregates, sums, adds) the sub-scores to arrive at the ingredient score for the ingredient. In some embodiments, the ranking engine 120 assigns a first score value if the property exceeds a predefined property threshold or a second score value if the property does not exceed the predefined property threshold…the ranking engine 120 assigns a first score value if the property exceeds a predefined property threshold or a second score value if the property does not exceed the predefined property threshold, [0052] determine a total amount of each nutrient in one serving of the target food product, and can indicate the presence or nutritional contribution of the corresponding nutrient via a weight (e.g., milligram), a contribution to the serving (e.g., percentage by weight of the nutrient relative to the total weight of the serving), a percentage of recommended daily consumption values, or any combination thereof. The recipe generator can generate a nutritional description according to any of the foregoing information )
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 11, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 2, further comprising:
Lynn further teaches obtaining a first quality score value for the first product quantity; obtaining a second quality score value for the second product quantity; based on the first quality score value, the second quality score value, at lest one process parameter value of the first product quantity and at least one process parameter value of the second product quantity, determining a quality relation between the process parameter and a quality score ([0028] the ranking engine 120 generates an ingredient score for each of the ingredients and generates rankings according to the ingredient scores (e.g., the ingredients are ranked from highest to lowest ingredient scores). In some embodiments, the ranking engine 120 generates a sub-score for each property, or other aspect, of the ingredient (e.g., the flavor, the texture, the cost) and combines or aggregates (e.g., aggregates, sums, adds) the sub-scores to arrive at the ingredient score for the ingredient. In some embodiments, the ranking engine 120 assigns a first score value if the property exceeds a predefined property threshold or a second score value if the property does not exceed the predefined property threshold…the ranking engine 120 assigns a first score value if the property exceeds a predefined property threshold or a second score value if the property does not exceed the predefined property threshold, [0052] determine a total amount of each nutrient in one serving of the target food product, and can indicate the presence or nutritional contribution of the corresponding nutrient via a weight (e.g., milligram), a contribution to the serving (e.g., percentage by weight of the nutrient relative to the total weight of the serving), a percentage of recommended daily consumption values, or any combination thereof. The recipe generator can generate a nutritional description according to any of the foregoing information).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 12, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1, further comprising:
Lynn further teaches obtaining a first quality score value for the first product quantity; obtaining a second quality score value for the second product quantity; based on the first quality score value, the second quality score value, at least one ingredient parameter value of the first product quantity and at least one ingredient parameter value of the second product quantity, determining a quality relation between the ingredient parameter and a quality score ([0028] the ranking engine 120 generates an ingredient score for each of the ingredients and generates rankings according to the ingredient scores (e.g., the ingredients are ranked from highest to lowest ingredient scores). In some embodiments, the ranking engine 120 generates a sub-score for each property, or other aspect, of the ingredient (e.g., the flavor, the texture, the cost) and combines or aggregates (e.g., aggregates, sums, adds) the sub-scores to arrive at the ingredient score for the ingredient. In some embodiments, the ranking engine 120 assigns a first score value if the property exceeds a predefined property threshold or a second score value if the property does not exceed the predefined property threshold…the ranking engine 120 assigns a first score value if the property exceeds a predefined property threshold or a second score value if the property does not exceed the predefined property threshold, [0052] determine a total amount of each nutrient in one serving of the target food product, and can indicate the presence or nutritional contribution of the corresponding nutrient via a weight (e.g., milligram), a contribution to the serving (e.g., percentage by weight of the nutrient relative to the total weight of the serving), a percentage of recommended daily consumption values, or any combination thereof. The recipe generator can generate a nutritional description according to any of the foregoing information).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 13, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1, wherein the relation score is indicative of a correlation between parameters between which the relation score is determined (Blevins, [0030] The example OMS may determine contribution relationships between process and/or quality variables based on modeling and/or analyzing the process control system, [0038] The measured quality variables may be associated with process control information related to measuring characteristics of the process that are associated with at least a portion of a completed product).
Regarding claim 14, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1,
Lynn further teaches wherein the obtained first process parameter value and the obtained first ingredient parameter value are provided to a neural network and the relation score is provided by the neural network ([0026] the ranking engine 120 filters (e.g., filters, prunes, extracts, keeps, or otherwise maintains) a subset of ingredients from the ingredients based on customer/consumer/user preference data. By way of a non-limiting example, the ranking engine 120 may receive a tag (e.g. a customer tag) indicating that meat-based ingredients are to be excluded from the subset of ingredients. A tag can be in the form of a note, indicator, instruction, guidance, restriction, modifier, setting, parameter, configuration, etc., to drive or control the ranking engine 120. The ranking engine 120 may generate a subset of ingredients excluding ingredients having a food type indicator that indicates presence or use of meat. In some embodiments, the tag may be provided in the form of a phrase, a sentence, a paragraph, and the like, and the ranking engine 120 uses natural language processing (e.g., using a trained neural network or machine learning model) to extract the preference data from the tag. In some embodiments, the ranking engine 120 bypasses filtering such that instead of generating a subset of ingredients, it enables the system to use all of the ingredients).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 15, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1,
Lynn further teaches wherein the first process parameter value is one of: Temperature; Conductivity; Colour; Transparency to visible light; Relative weight; Acidity; Sugar content ([0024] nutritional measures (e.g., measures for vitamins, minerals, calories, fats, cholesterol, carbohydrates, proteins, sugars, sodium, and so on); Viscosity; Energy added; and Control temperature of a machine executing the first processing step.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process such as sugar content. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process such as sugar content. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 16, The combination of Blevins, Mitchell, and Lynn teach The method according to claim 1,
Lynn further teaches wherein the first product component parameter is at least one of the following: ethanol content; methanol content; sugar content ([0024] nutritional measures (e.g., measures for vitamins, minerals, calories, fats, cholesterol, carbohydrates, proteins, sugars, sodium, and so on)); and carbon dioxide content.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process such as sugar content. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process such as sugar content. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 18, Blevins teaches An electronic process analysis device for selecting a pre-determined number of at least one of the multitude of process parameters based on determining, for a first product quantity of … having undergone a first processing step as part of a …process ([0007] a processor to determine if a variation based on the received process control information associated with the process exceeds a threshold, if the variation exceeds the threshold, calculate a first contribution value based on a contribution of the first measured variable to the variation and a second contribution value based on a contribution of the second measured variable to the variation, determine at least one corrective action based on the first contribution value, the second contribution value, the first value, or the second value, and calculate a predicted process quality based on the at least one corrective action at a time after the first time, [0030] a process overview chart may display the status of one or more processes being monitored. From this overview chart, an operator may select a process variation graph showing any explained (e.g., modeled) and/or unexplained (e.g., un-modeled) variations within the process,[0025] process control systems provide analytic and/or statistical analysis of process control information), a relation between at least one of a set of process parameters of the first processing step and a set of ingredient parameters on one hand and at least one first product component parameter on the other hand, the device comprising: an input arranged to perform ([0030] The example OMS may determine contribution relationships between process and/or quality variables based on modeling and/or analyzing the process control system, [0038] The measured quality variables may be associated with process control information related to measuring characteristics of the process that are associated with at least a portion of a completed product, [0035] The process control system 106 may include any number of field devices (e.g., input and/or output devices). The field devices may include any type of process control component that is capable of receiving inputs, generating outputs, and/or controlling a process. For example, the field devices may include input devices such as, for example, valves, pumps, fans, heaters, coolers, and/or mixers to control a process) , identifying the at least one first product component potentially present in the first product quantity; and obtaining at least one first product component parameter value for the first product quantity related to the first product component ([0041] The analytic processor 114 may detect, identify, and/or diagnose process operation faults and predict the impact of any faults on quality variables and/or an overall quality variable associated with a quality of a resultant product of the process control system 106. Furthermore, the analytic processor 114 may monitor the quality of the process by statistically and/or logically combining quality and/or process variables into an overall quality variable associated with the overall quality of the process. The analytic processor 114 may then compare the values calculated for the overall quality variable and/or values associated with the other quality variables to respective thresholds) ; and wherein the input is further arranged to perform at least one of obtaining, from a process data acquisition control system, process data comprising a multitude of first process parameter values related to the first processing step of the first product quantity and ([0041] The analytic processor 114 may detect, identify, and/or diagnose process operation faults and predict the impact of any faults on quality variables and/or an overall quality variable associated with a quality of a resultant product of the process control system 106. Furthermore, the analytic processor 114 may monitor the quality of the process by statistically and/or logically combining quality and/or process variables into an overall quality variable associated with the overall quality of the process. The analytic processor 114 may then compare the values calculated for the overall quality variable and/or values associated with the other quality variables to respective thresholds, [0100] The overview chart 502 is organized by process area and includes a state of a first process area (e.g., Process Area 1) and a second process area (e.g., Process Area 2). The first process area may correspond to the process control system 106. Each process area includes information associated with current and/or previous batches that may be used to alert a process control operator when a fault is detected), obtaining, from the process data acquisition control system ingredient data comprising a multitude of ingredient parameter values related to a multitude of ingredients forming a basis for the first product quantity; and wherein the electronic process analysis device comprises a processing unit arranged to determine, based on the multitude of process parameter values the multitude of ingredient parameter values and the first product component parameter value (Fig.11,[0030] The example OMS may determine contribution relationships between process and/or quality variables based on modeling and/or analyzing the process control system, [0038] The measured quality variables may be associated with process control information related to measuring characteristics of the process that are associated with at least a portion of a completed product,[0040] model and/or determine relationships between the measured process variables and/or quality variables associated with the process control system 106. These relationships between the measured process and/or quality variables may produce one or more calculated quality variables) a first relation score indicative of the first relation between each of the multitude process parameter values and the first product component parameter value and/or a second relation score indicative of the second relation between each of the multitude of the ingredient parameter values and the first product component parameter value; and select a pre-determined number of at least one of the multitude of process parameters (Fig. 11[0030] a process overview chart may display the status of one or more processes being monitored. From this overview chart, an operator may select a process variation graph showing any explained (e.g., modeled) and/or unexplained (e.g., un-modeled) variations within the process, [0041] the analytic processor 114 may then compare the values calculated for the overall quality variable and/or values associated with the other quality variables to respective thresholds. These thresholds may be based on the predetermined quality limits of the overall quality variable at different times within the process. For example, if an overall quality variable associated with a process exceeds a threshold for an amount of time, the predicted final quality of the resulting product may not meet quality metrics associated with the finished product, [0117] The variable trend graph 510 may be used by a process control operator to compare a process variable trend during the current batch process to trends of the variable during previous batch processes that finished with a product within quality thresholds ) wherein the electronic process analysis device further comprises an output arranged to provide data on at least one of the relation or the relation score indicative of a relation ([0040] These relationships between the measured process and/or quality variables may produce one or more calculated quality variables. A calculated quality variable may be a multivariate and/or linear algebraic combination of one or more measured process variables, measured quality variables, and/or other calculated quality variables. Furthermore, the OMS 102 may determine an overall quality variable from a combination of the measured process variables, measured quality variables, and/or calculated quality variables. The overall quality variable may correspond to a quality determination of the entire process and/or may correspond to a predicted quality of a resulting product of the process, [0065] processing the models with the measured values, and/or receiving the values associated with the calculated quality and/or overall quality variables as an output of the model).
Blevins does not teach beer… brewing… and the multitude of ingredient parameters having a relation scores indicating strongest relations with the product component parameter values
Mitchell teaches beer… brewing… ([0007] beer brewing system may adjust a brewing session based on data collected during the brewing session)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Blevin’s teaching of predicting process quality in a process control system using control and measured variables with Mitchell’s teaching of beer brewing system. The combined teaching provides an expected result of predicting process quality in a process control beer brewing system using control and measured variables. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
The combination of Blevins and Mitchell do not teach and the multitude of ingredient parameters having a relation scores indicating strongest relations with the product component parameter values
Lynn teaches and the multitude of ingredient parameters having a relation scores indicating strongest relations with the product component parameter values ([0025] The ranking engine 120 receives input data 150 (e.g., ingredients, ingredient property data, customer/consumer/user preference data, and the like), in one or more embodiments. The ingredient property data may include an identifier or name of the ingredient, one or more food type indicators (e.g., meat, non-meat protein, dairy, vegetable/vegetarian, fruit, gluten-free, nut-free, or a combination thereof), one or more nutritional values (e.g., values for vitamins, minerals, sodium, sugars, fats, cholesterol, carbohydrates, protein, fiber, and the like, expressed for instance in grams or milligrams per serving, as a percentage of daily recommended value, etc.), one or more functional benefit indicators (e.g., heart, cognitive, metabolism), and/or one or more functional risk indicators (e.g., heart, cognitive, metabolism). The nutritional values can be for a normalized unit of mass (e.g., 100 grams) or weight (e.g., 1 ounce). The ingredient property data, as well as customer/consumer/user preference data, market data, or any other data, can be stored in storage (e.g., cloud storage, local storage, object storage, database, catalog, relational database, associative database, and the like) included in or associated with the system 100.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Blevin’s and Mitchell’s teaching of predicting process quality in a beer brewing system with Lynn’s teaching of ranking ingredients in a process. The combined teaching provides an expected result of predicting process quality in a beer brewing system by ranking ingredients during the process. Therefore, one of ordinary skill in the art would be motivated to improve the accuracy and quality of beer produced in a brewing system.
Regarding claim 19, The combination of Blevins, Mitchell, and Lynn teach A computer program product comprising computer executable code arranged to cause a computer, when the executable code is loaded in a memory connected to an electronic processing unit comprised by the computer for programming the electronic processing unit, to execute the method according to claim 1 (Blevins, [0090] FIG. 4 may be implemented separately and/or in any combination using, for example, machine-accessible or readable instructions executed by one or more computing devices and/or computing platforms (e.g., the example processing platform P10 of FIG. 18).
Relevant Art Cited by Examiner
The following prior art made of record and not relied upon is cited to establish the level of skill in the applicant’s art and those arts considered reasonably pertinent to Applicant’s disclosure. See MPEP 707.05(c).
Mitchell, US20170029752 discloses a fermentation monitoring and management system.
Kinsman, US2938795 discloses a manufacturing and packing process of beers.
Inui, US20220202047 discloses a method for producing beverages including processes considering aroma ingredients evaluated using a scoring method.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YVONNE T FOLLANSBEE whose telephone number is (571)272-0634. The examiner can normally be reached Monday - Friday 1pm - 9pm.
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/YVONNE TRANG FOLLANSBEE/Examiner, Art Unit 2117
/ROBERT E FENNEMA/Supervisory Patent Examiner, Art Unit 2117
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