DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office action is in response to correspondence received February 9, 2025.
Claims 1, 6-10, and 15-18 are amended. Claims 19-26 have been added. Claims 1, 2, 6-11, and 15-26 are pending and have been examined.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on February 9, 2026 has been entered.
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, 2, 6-11, and 15-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim(s) 1 recite(s):
A method to receive measurement data for determining carbon footprint for one or more products assembled by the assembly unit, the method comprising: collecting real-time data generated by at least one product counter sensor configured to detect a number of products assembled by the assembly unit over time; determining a number of assembled products in a period of time, based on the measurement data generated by the at least one product counter sensor; collecting real-time measurement data to measure an amount of energy supplied to the assembly unit over time, storing the collected real-time measurement data in a [data store] using a [data store] protocol; determining an amount of supplied energy in the period of time based on the measurement data collected from the at least one energy supply sensor and stored in the [data store] ; obtaining, energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit; estimating an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time, based on the energy carbon footprint information; determining a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the period of time, based at least on the number of assembled products in the period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time; and [presenting] a per-assembled-product carbon-footprint value derived from the real-time measurement data collected
Claim 9 recites:
determining carbon footprint for one or more products assembled by an assembly unit, receive, real-time measurement data from the assembly unit; , and a [data store] wherein collect real-time measurement data to detect a number of products assembled by the assembly unit over time, wherein the determine a number of assembled products in a period of time, based on the measurement data collect real-time measurement data generated to measure an amount of energy supplied to the assembly unit over time, and to store the collected real-time measurement data using a protocol, wherein determine an amount of supplied energy in the period of time based on the measurement data generated ; obtain energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit; estimate an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time, based on the energy carbon footprint information; determine a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the period of time, based at least on the number of assembled products in the period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time and, [presenting] a per-assembled-product carbon-footprint value derived from the real-time measurement data collected .
Claim 10 recites:
determining carbon footprint for one or more products assembled by an assembly unit, store real-time measurement data collected; and receive measurement data collected in real-time to detect a number of products assembled by the assembly unit over time, ; determine a number of assembled products in a period of time, based on the measurement data generated receive, , measurement data collected in real-time and generated to measure an amount of energy being supplied to the assembly unit over time, determine an amount of supplied energy in the period of time, based on the measurement data generated ; obtain energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit; estimate an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time, based on the energy carbon footprint information; determine a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the period of time, based at least on the number of assembled products in the period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time; and [present] , a per-assembled-product carbon-footprint value derived from the real-time measurement data collected wherein the determination of the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the period of time is further based on component carbon footprint information associated with components in the rejected products.
Claim 18 recites:
determining carbon footprint for one or more products assembled by an assembly unit, store measurement data collected from physical sensors , and receive, measurement data collected in real-time and generated detect a number of products assembled by the assembly unit over time, ; determine a number of assembled products in a period of time, based on the measurement data generated ; receive, , measurement data collected in real-time and generated to measure an amount of energy supplied to the assembly unit over time, determine an amount of supplied energy in the period of time based on the measurement data generated ; obtain energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit; estimate an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time, based on the energy carbon footprint information; determine a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the period of time, based at least on the number of assembled products in the period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time; and [present] a per-assembled-product carbon-footprint value derived from the real-time measurement data collected .
Claims 1, 9, 10, and 18 recite an abstract idea that is a mental process. That is because the steps detailed above are steps of observation and judgment. The receiving obtaining steps are observation because under a broadest reasonable interpretation one could observe information coming from a sensor including real-time information which is simply information as it is happening, imperceptible to the time between the instant something occurs that is being measured and the measurement (a counter on an assembly line for example, counting items as they go by). The judgement steps are determining and estimating steps which one could do mentally or with pen and paper. Storing data in a data store is a further observation step that can be done with pen and paper. Protocols are simply rules and here, broadly claimed (“by a protocol”) could be rules that one follows mentally. Combined the steps are a mental process which one could take one step at a time and therefore the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. The additional elements are under a broadest reasonable interpretation taught by generic computing components that collect, store, analyzed, and display data. In combination they could be taught by a generic computer (generic computers collect, store, analyze, and display data) as described in pars 086-094. The sensors are recited performing in their ordinary capacity as data collection/generation elements that simply output the data they are designed to output. In combination, the additional elements amount to generic computing components coupled with sensors to receive the data from the sensors, which is no more than reciting instructions to apply the abstract idea to a computer connected to sensors. These are therefore instructions to apply the abstract idea to a computer with sensors, see MPEP 2106.05(f)(2), which is not a practical application of an abstract idea.
The additional elements of claim 1 are:
[steps] performed by a monitoring system comprising a gateway and a processor, the gateway configured to
[data from] from physical sensors, using a communication protocol,
from an assembly unit
via the gateway,
wherein the at least one product counter sensor comprises at least one of the physical sensors
generated by at least one energy supply sensor configured to
wherein the at least one energy supply sensor comprises at least one of the physical sensors;
by the monitoring system,
generated by the at least one product counter sensor and the at least one energy supply sensor
by the processor
via the gateway
database
by the processor
displaying, on a graphical user interface
The additional elements of claim 18 are:
A computer program product comprising a non-transitory, computer-readable medium storing computer-executable code for
the code executable by a computer monitoring system having a memory and at least one processor, wherein the memory is configured to
by a gateway
using a communication protocol
wherein execution of the code by the processor of the computer monitoring system causes the processor to:
from the memory,
by at least one product counter sensor configured to
wherein the at least one product counter sensor comprises at least one of the physical sensors
by the at least one product counter sensor
by at least one energy supply sensor configured to
wherein the at least one energy supply sensor comprises at least one of the physical sensors;
display, on a graphical user interface,
via the gateway,
Claim 9:
A monitoring system for
the system comprising: a gateway configured to
, from physical sensors, using a communication protocol
a processor; and a database
the gateway is configured to
generated by at least one product counter sensor configured
at least one product counter sensor comprises at least one of the physical sensors; the processor is configured to
generated by the at least one product counter sensor, the gateway is configured to
by at least one energy supply sensor configured
wherein the at least one energy supply sensor comprises at least one of the physical sensors;
the monitoring system is configured
generated by the at least one product counter sensor and the at least one energy supply sensor
database
the processor is further configured to:
by the at least one energy supply sensor
displaying, on a graphical user interface,
via the gateway
Claim 10:
A monitoring system for
the system comprising: a memory configured to
by a gateway from physical sensors using a communication protocol
at least one processor coupled to the memory and configured to:
from the memory
by the gateway and generated by at least one product counter sensor configured
wherein the at least one product counter sensor comprises at least one of the physical sensors
by the at least one product counter sensor;
by at least one energy supply sensor configured
wherein the at least one energy supply sensor comprises at least one of the physical sensors;
by the at least one energy supply sensor
display, on a graphical user interface
via the gateway
Claim 18:
A computer program product comprising a non-transitory, computer-readable medium storing computer-executable code for
the code executable by a computer monitoring system having a memory and at least one processor, wherein the memory is configured to
by a gateway
using a communication protocol
wherein execution of the code by the processor of the computer monitoring system causes the processor to:
from the memory,
by at least one product counter sensor configured to
wherein the at least one product counter sensor comprises at least one of the physical sensors
by the at least one product counter sensor
by at least one energy supply sensor configured to
wherein the at least one energy supply sensor comprises at least one of the physical sensors;
display, on a graphical user interface,
via the gateway,
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because for the same reasons that the claims are not a practical application they are not significantly more than the abstract idea. In other words, instructions to apply an abstract idea to a computer is not significantly more than the abstract idea. See MPEP 2106.05(f)(2).
Per the dependent claims:
Claims 2 and 11, which are similar in scope, are a field of use limitation describing the kind of industrial environment measured, field of use under MPEP 2106.05(h) is not a practical application or significantly more.
Claims 7 and 16, which are similar in scope, further describe, as well, the abstract idea with further obtaining and determining steps, as well as displaying which is analyzed in the same way as in the independent claims, above.
Claims 6, 8 and 15, 17, which are similar in scope, describes displaying information such as a graph which is something that can be done with pen and paper and is therefore a mental process and displaying information on a computer screen is an apply it limitation for a computing device, which is not a practical application or significantly more.
Claim 19 recites categories of sensors that could count and these are further apply it limitations as they are performing in their ordinary capacity, to count objects as they go by, in some way. Likewise with a “reject counter sensor” which is a functional description of a sensor (ie, no structural limitation except “sensor”).
Claim 20 describes displaying various information where the information is patent ineligible, mental process (graphs, “breakdowns,” etc, is able to be presented with pen and paper) and displaying is using a computer in an apply it manner.
Claim 21 recites detecting number of products assembled, the detecting (receiving, observing, collecting, equivalent to these) counted objects is a part of the mental process of claim 1 and using a product sensor is an apply it limitation, analyzed the same way as the product sensor or counter sensor is analyzed in the independent claim rejection.
Claim 22, similar to claim 21, recites an energy sensor being used in its ordinary capacity and therefore is an apply it limitation and then the act of measuring energy is a further mental process limitation of observation.
Claims 23-26, which are similar in scope, recite further mental process steps of obtaining information of various kinds which one can do through observation. Reciting that this is caused by a processor or done by a processor or equivalent is an instruction to apply the abstract idea to a computer. Therefore claims 23-26 further describe the abstract idea of the independent claims.
Therefore claims 1, 2, 6-11, and 15-26 are rejected under 35 USC 101.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 2, 6-9, 18, 19, 21, and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wollack et al., US PGPUB 20220237628 A1 (“Wollack”), in view of Schoeneboom et al., US PGPUB 20220108327 A1 ("Schoeneboom").
Per claims 1, 9, and 18, which are similar in scope, Wollack teaches method, performed by a monitoring system comprising a gateway and a processor, the gateway configured to receive, from physical sensors, using a communication protocol, measurement data from an assembly unit for determining carbon footprint for one or more products assembled by the assembly unit, the method comprising in par 020: “During production of the materials, greenhouse gases such as methane and/or carbon dioxide are destroyed (or sequestered) through the conversion of methane to carbon dioxide, carbon dioxide to oxygen, and other processes. Various sensors and user input devices may monitor a production process and record production details such as the weight of material produced, the amount of greenhouse gas destroyed or sequestered, the amount of power used (e.g., electricity, fuel, or other resources consumed during production), the amount of water used in production, working conditions (e.g., the average wages and average working hours of workers involved in production of the carbon-sequestering raw materials), other production inputs, an expected rate of decay of the carbon-sequestering matter, and batch information (e.g., identification information), as examples.”
Wollack then teaches collecting, via the gateway, real-time measurement data generated by at least one product counter sensor configured to detect a number of products assembled by the assembly unit over time in par 030: “As yet more examples, the concentrator 116, treatment equipment 118, dryer 120, and/or scale 112 may include sensors for measuring relevant properties of the reaction products (e.g., the concentrator may record the weights of inputs and outputs and the scale 122 may record the weight of finished polymer). In at least some embodiments, the entirety (or nearly the entirety) of the production process is automatically monitored and relevant sensor readings automatically recorded.”
Wollack then teaches wherein the at least one product counter sensor comprises at least one of the physical sensors n par 030: “As yet more examples, the concentrator 116, treatment equipment 118, dryer 120, and/or scale 112 may include sensors for measuring relevant properties of the reaction products (e.g., the concentrator may record the weights of inputs and outputs and the scale 122 may record the weight of finished polymer). In at least some embodiments, the entirety (or nearly the entirety) of the production process is automatically monitored and relevant sensor readings automatically recorded.”
Wollack then teaches determining, by the processor, a number of assembled products in a period of time, based on the measurement data generated by the at least one product counter sensor in par 33: “In at least some embodiments, vendor 130 may send a materials packet such as second 150b. Second packet 150b may include any desired information including, but not limited to, the identity of the vendor (sometimes referred to as a fabricator), a unit count, an indication of the amount of polymer used, an indication of the amount of resins products, a production date, a ship date, a type of carbon-sequestering material or resin produced, and an amount of power consumed by the vendor during processing of the polymer.” Sensors which provide this information are taught in pars 65, 66, 68, 79.
Wollack then teaches collecting, via the gateway, real-time measurement data generated by at least one energy supply sensor configured to measure an amount of energy being supplied to the assembly unit over time in par 40: “In some embodiments, the packet 150c may additionally include mileage, fuel consumed, and/or other data associated with shipment and other movement of the product and its component parts up to the shipment of the product 168.”
Wollack then teaches wherein the at least one energy supply sensor comprises at least one of the physical sensors in par 20 “Various sensors and user input devices may monitor a production process and record production details such as the weight of material produced, the amount of greenhouse gas destroyed or sequestered, the amount of power used (e.g., electricity, fuel, or other resources consumed during production),” See also par 020 for the energy sensor and energy used in the production process, ie real time.
Wollack then teaches storing, by the monitoring system, the collected real-time measurement data generated by the at least one product counter sensor and the at least one energy supply sensor in a database using a database protocol in par 074 and references to storing in a blockchain in Wollack (see 54-69 but not limited to this) as blockchain teaches a database as it is a decentralized ledger.
Wollack then teaches determining, by the processor, an amount of supplied energy in the period of time, based on the measurement data collected via the gateway from the at least one energy supply sensor and stored in the database in par 20 “Various sensors and user input devices may monitor a production process and record production details such as the weight of material produced, the amount of greenhouse gas destroyed or sequestered, the amount of power used (e.g., electricity, fuel, or other resources consumed during production),”
Wollack then teaches determining, by the processor, a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the period of time, based at least on the number of assembled products in the period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time in par 53: “Another method for tracking carbon credits on a per-unit basis is shown in FIG. 3, which is a flow diagram of an illustrative method 300. The illustrative method 300 begins at block 302, where a blockchain node receives at least one data packet detailing carbon sequestered during production of raw materials such as a polymer or one or more proteins. The packet received in block 302 may be, as an example, a packet such as first packet 150a of FIG. 1A. The packet received in block 302 may include information such as a finished weight of raw materials, an amount of carbon-dioxide (or other greenhouse gas) consumed (e.g., destroyed or otherwise sequestered), an amount of power used, an amount of greenhouse gases produced as a result of the production, and identification information such as information identifying a batch of raw materials or identifying the producer of the raw materials, as examples (though not each is required in every embodiment).”
Wollack does not teach obtaining, by the processor, energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit
estimating, by the processor, an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time, based on the energy carbon footprint information;
displaying, on a graphical user interface, a per-assembled-product carbon-footprint value derived from the real-time measurement data collected via the gateway.
Schoeneboom teaches a method for determining a carbon footprint of a product. See abstract.
Schoeneboom teaches obtaining, by the processor, energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit in par 40: " The energy data is usually transformed into carbon footprints by taking into account the energy sources and their specific greenhouse gas emissions."
See also pars 046-047: “ "In some embodiments, the process according to the present invention further comprises (d) determining the carbon footprint of the product taking into account the process data, the carbon footprint of each raw material and the energy data.
Determining the carbon footprint of the product comprises summation of the carbon footprints of each raw material used in a particular process step as contained in the process data from step (a). If a process step requires an intermediate from a different process step, the sum of the carbon footprint of the raw material for this earlier process step is determined and used as input for the later process step. It may be necessary to repeat this if the earlier process step again uses an intermediate of an even earlier process step. If one process step yields more than one intermediate, for example two or three, it is necessary to share the carbon footprint of the raw materials among these intermediates. The share for each intermediate should reflect the raw material usage for each intermediate. In some cases, two intermediates are formed at the same amount, so the carbon footprint of the raw materials can be equally shared among them. In other cases, significantly more of one intermediate is formed than the other, for example 90% of intermediate 1 and 10% of intermediate 2. The carbon footprint should be shared accordingly. Hence, preferably, in the method of the present invention determining the carbon footprint involves, in some embodiments, calculating the carbon footprint for an intermediate produced in a preceding process step and using the carbon footprint of the intermediate as input for the calculation of the carbon footprint of a subsequent process step. In particular, in interconnected production processes, the calculation of the carbon footprint can be facilitated by subdividing it into analogous calculation parts, one for each process step. “
Schoeneboom then teaches estimating, by the processor, an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time, based on the energy carbon footprint information in par 52: "Alternatively, preferably, the contribution of the energy for the product is determined for the product independent of the raw materials. To achieve this, the energy contribution for each process step is added according to the process data. If a process step yields more than one intermediate or the intermediate is used in more than one other process step, the contribution is shared among these, so only that part of the process step is taken into account which can be attributed to the product. For example, if one process step yields two intermediates at the same ratio and only one intermediate is used to produce the product, only half of the energy contribution of said process step is used for the determination of the energy contribution. "
See also pars 046-047: “ "In some embodiments, the process according to the present invention further comprises (d) determining the carbon footprint of the product taking into account the process data, the carbon footprint of each raw material and the energy data.
Determining the carbon footprint of the product comprises summation of the carbon footprints of each raw material used in a particular process step as contained in the process data from step (a). If a process step requires an intermediate from a different process step, the sum of the carbon footprint of the raw material for this earlier process step is determined and used as input for the later process step. It may be necessary to repeat this if the earlier process step again uses an intermediate of an even earlier process step. If one process step yields more than one intermediate, for example two or three, it is necessary to share the carbon footprint of the raw materials among these intermediates. The share for each intermediate should reflect the raw material usage for each intermediate. In some cases, two intermediates are formed at the same amount, so the carbon footprint of the raw materials can be equally shared among them. In other cases, significantly more of one intermediate is formed than the other, for example 90% of intermediate 1 and 10% of intermediate 2. The carbon footprint should be shared accordingly. Hence, preferably, in the method of the present invention determining the carbon footprint involves, in some embodiments, calculating the carbon footprint for an intermediate produced in a preceding process step and using the carbon footprint of the intermediate as input for the calculation of the carbon footprint of a subsequent process step. In particular, in interconnected production processes, the calculation of the carbon footprint can be facilitated by subdividing it into analogous calculation parts, one for each process step. “
Schoeneboom then teaches displaying, on a graphical user interface, a per-assembled-product carbon-footprint value derived from the real-time measurement data collected via the gateway in par 052: “To arrive at the total carbon footprint of the product, the contribution of the raw materials and the contribution of the energy is added. Hence, preferably determining the carbon footprint of the product comprises determining the contribution of the energy in each process step and add shares of it according to the process data.” Then per displaying on a graphical user interface, par 066: “In some embodiments, the system or apparatus according to the present invention comprises (c) an output or output unit configured to output the carbon footprint of the product, preferably the carbon footprint of the product and each contribution to it as obtained from the processor or processing unit. Preferably, the output or output unit has an interface to an ERP system or a computing system or apparatus, such as a centralized or decentralized computing system or apparatus including processing and storage. Preferably, the output or output unit comprises a user interface, in particular a graphical user interface. The user interface is preferably configured to display the carbon footprint of the product and each contribution, preferably comprising the contribution of the raw materials, the contribution of the energy, and the contribution of the direct emissions of each process step. Preferably, the user interface is configured to use graph technology. The user interface may be configured to provide an overview of each process step, its raw materials and energy required, the connection with other process steps. The user interface may also provide the carbon footprint for each process step, in particular it may be configured to display the carbon footprint originating from the raw materials, from the energy consumption, and from the direct greenhouse gas emissions separately and in aggregated form.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint teaching of Wollack with the energy calculations for carbon footprint teaching of Schoeneboom because Schoeneboom teaches in pars 005-006 that multiple sources of data have to be used for carbon footprint and were calculated manually which takes a long time, therefore one would be motivated to modify Wollack with Schoeneboom in order to calculate more quickly and efficiently, which would improve understanding of carbon footprints.
Per claim 2, Wollack and Schoeneboom, teach the limitations of claims 1, above. Wollack further teaches wherein the assembly unit is an assembly station, an assembly line comprising multiple assembly stations, or an assembly factory comprising multiple assembly lines in par 32: “As shown in FIG. 1B, vendor 130 may receive a materials order 132 or a resin order 146, requesting shipment of specified carbon-sequestering materials or resins. Upon receipt of an order, the vendor may combine polymers from polymer inventory 136, with optional materials from materials inventory 138, and with various chemicals 140 in accordance with a resin formula 142 or some other recipe. The combined materials may be passed through an extruder 144 to produce carbon-sequestering materials such as resins 148. The resin order 152 may then be fulfilled by shipping 154 the appropriate amount of resins to a customer.”
Per claim 6, Wollack and Schoeneboom teach the limitations of claim 1, above. Wollack further teaches the aggregated carbon footprint for all the assembled products in the period of time in par 080: “The amount of carbon credit associated with the batch of raw material may be determined based at least on (a) the amount of carbon prevented from entering the atmosphere when producing the batch of raw material and (b) the amount of power used in producing the batch of raw material. The receiving from the remote computing device of the first data packet may include receiving from the remote computing device the first data packet along with a digital signature generated with a private key of the remote computing device.”
Wollack does not teach upon determining the carbon footprint per assembled product, determining carbon footprint for all the assembled products in the period of time, and displaying, on the graphical user interface, carbon footprint information
Schoeneboom teaches upon determining the carbon footprint per assembled product, determining carbon footprint for all the assembled products in the period of time, and displaying, on the graphical user interface, carbon footprint information in pars 056-057: “"In some embodiments, the process according to the present invention further comprises (e) outputting the carbon footprint of the product obtained in step (d). Outputting can mean writing the carbon footprint on a non-transitory data storage medium, displaying it on a user interface, providing it to an interface for further processing or any combination thereof. It is also possible to provide the output through an interface to a customer, for example to the customers supply chain system or ERP system. It is also possible to provide the output through an interface to the EPR system of the producer itself from where it can be distributed to where this information is needed. When the carbon footprint and each contribution to it is output onto a user interface, the user interface preferably uses graph technology. In this way, it is possible to analyze the contributions along the production process in order to optimize the production process and thereby minimize the carbon footprint for the products. It is also possible to monitor changes of the carbon footprint upon changes in the production process. In addition, the output can be used to simulate effects of changes, for example by manually changing certain values and see its effect on the carbon footprint of the product. For example, the effect of replacing a particular raw material by one having lower carbon footprint for each product may be analyzed.
Preferably, the process further comprises outputting the carbon footprint for each process step as it contributes to the carbon footprint of a certain product. In this way, it is possible to analyze the contribution of each step, in particular the contribution of raw materials and energy in each step. This allows the identification of potential to reduce the carbon footprint of the product."
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint teaching of Wollack with the energy calculations for carbon footprint teaching of Schoeneboom because Schoeneboom teaches in pars 005-006 that multiple sources of data have to be used for carbon footprint and were calculated manually which takes a long time, therefore one would be motivated to modify Wollack with Schoeneboom in order to calculate more quickly and efficiently, which would improve understanding of carbon footprints.
Per claim 7, Wollack and Schoeneboom teach the limitations of claim 1, above. Wollack further teaches for each of multiple periods of time, performing the following steps upon a respective period of time has elapsed: determining a number of assembled products in the respective period of time, based on the measurement data generated by the at least one product counter sensor in par 053 and 055, see par 055: “At block 306, a blockchain node receives at least one second data packet detailing fabrication of a plurality of goods from the raw materials. The packet received in block 306 may be, as an example, a packet such as third packet 150c of FIG. 1C. The packet received in block 306 may include information such as a plurality of unique product identifiers, a product type, a number of units of goods produced, and a production date, as examples. In some embodiments, the packet received in block 306 and the associated entry stored in block 308 may detail fabrication of an intermediary good, rather than a final product. In embodiments with multiple stages of intermediary goods, blocks 306 and 308 may be repeated for each stage of fabrication. In these and other embodiments, a final iteration of blocks 306 and 308 may be performed for the fabrication of final goods from the final intermediary product. In this manner, the final goods (and any intermediary goods) can be traced back to an associated entry stored in block 304, thus facilitating tracking of carbon sequestered in the final goods (and any intermediary goods).”
Wollack does not teach
determining an amount of supplied energy in the respective period of time, based on the measurement data generated by the at least one energy supply sensor
estimating an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the respective period of time, based on the energy carbon footprint information
determining a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the respective period of time, based at least on the number of assembled products in the respective period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the respective period of time
and displaying, on the graphical user interface, the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the respective period of time.
Schoeneboom teaches determining an amount of supplied energy in the respective period of time, based on the measurement data generated by the at least one energy in par 042: “Often, a production plant has multiple sensors providing data about the energy consumption of a certain process step or certain equipment.”
Then, Schoeneboom teaches estimating an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the respective period of time, based on the energy carbon footprint information in par 052: “For example, if one process step yields two intermediates at the same ratio and only one intermediate is used to produce the product, only half of the energy contribution of said process step is used for the determination of the energy contribution. To arrive at the total carbon footprint of the product, the contribution of the raw materials and the contribution of the energy is added. Hence, preferably determining the carbon footprint of the product comprises determining the contribution of the energy in each process step and add shares of it according to the process data.”
Then, Schoeneboom teaches determining a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the respective period of time, based at least on the number of assembled products in the respective period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the respective period of time in par 056: “In some embodiments, the process according to the present invention further comprises (e) outputting the carbon footprint of the product obtained in step (d). Outputting can mean writing the carbon footprint on a non-transitory data storage medium, displaying it on a user interface, providing it to an interface for further processing or any combination thereof. It is also possible to provide the output through an interface to a customer, for example to the customers supply chain system or ERP system.”
Then, Schoeneboom teaches and displaying, on the graphical user interface, the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the respective period of time in par 056: “ It is also possible to provide the output through an interface to the EPR system of the producer itself from where it can be distributed to where this information is needed. When the carbon footprint and each contribution to it is output onto a user interface, the user interface preferably uses graph technology. In this way, it is possible to analyze the contributions along the production process in order to optimize the production process and thereby minimize the carbon footprint for the products.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint teaching of Wollack with the energy calculations for carbon footprint teaching of Schoeneboom because Schoeneboom teaches in pars 005-006 that multiple sources of data have to be used for carbon footprint and were calculated manually which takes a long time, therefore one would be motivated to modify Wollack with Schoeneboom in order to calculate more quickly and efficiently, which would improve understanding of carbon footprints.
Per claim 8, Wollack and Schoeneboom teach the limitations of claim 7, above. Wollack does not teach displaying, on the graphical user interface, a graph of the carbon footprints per assembled product and/or the aggregated carbon footprints for all the assembled products in the multiple periods of time.
Schoeneboom teaches displaying, on the graphical user interface, a graph of the carbon footprints per assembled product and/or the aggregated carbon footprints for all the assembled products in the multiple periods of time in par 066: “In some embodiments, the system or apparatus according to the present invention comprises (c) an output or output unit configured to output the carbon footprint of the product, preferably the carbon footprint of the product and each contribution to it as obtained from the processor or processing unit. Preferably, the output or output unit has an interface to an ERP system or a computing system or apparatus, such as a centralized or decentralized computing system or apparatus including processing and storage. Preferably, the output or output unit comprises a user interface, in particular a graphical user interface. The user interface is preferably configured to display the carbon footprint of the product and each contribution, preferably comprising the contribution of the raw materials, the contribution of the energy, and the contribution of the direct emissions of each process step. Preferably, the user interface is configured to use graph technology. The user interface may be configured to provide an overview of each process step, its raw materials and energy required, the connection with other process steps. The user interface may also provide the carbon footprint for each process step, in particular it may be configured to display the carbon footprint originating from the raw materials, from the energy consumption, and from the direct greenhouse gas emissions separately and in aggregated form. FIG. 5 shows schematically an example of how the user interface could be configured. The raw materials and the intermediates to the product are displayed according to the chain of interconnected process steps. The arrows represent process steps. Their width reflects the amount of greenhouse gases the respective process step contributes to the carbon footprint of the product. It may be possible to display further information when hovering over a box or an arrow with the mouse pointer, for example specifics about the raw material, intermediate or product or the exact value of the greenhouse gas emission. Preferably the carbon footprints are displayed in aggregated form showing the contributions of the raw materials, the energy usage and direct greenhouse gas emissions.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint teaching of Wollack with the energy calculations for carbon footprint teaching of Schoeneboom because Schoeneboom teaches in pars 005-006 that multiple sources of data have to be used for carbon footprint and were calculated manually which takes a long time, therefore one would be motivated to modify Wollack with Schoeneboom in order to calculate more quickly and efficiently, which would improve understanding of carbon footprints.
Per claim 19, Wollack and Schoeneboom teach the limitations of claim 1, above. Wollack further teaches wherein the at least one product counter sensor comprises at least one light sensor, photoelectric barrier, pressure sensor, flow sensor, temperature sensor, a scale, a displacement sensor, a vision system, a good part counter sensor configured to count a number of products that are successfully assembled, or a reject counter sensor configured to count a number of products that are not successfully assembled and a stage of assembly associated with each not successfully assembled product in par 030: “As yet more examples, the concentrator 116, treatment equipment 118, dryer 120, and/or scale 112 may include sensors for measuring relevant properties of the reaction products (e.g., the concentrator may record the weights of inputs and outputs and the scale 122 may record the weight of finished polymer). In at least some embodiments, the entirety (or nearly the entirety) of the production process is automatically monitored and relevant sensor readings automatically recorded.”
Per claim 21, Wollack and Schoeneboom teach the limitations of claim 1, above. Wollack further teaches detecting, by the at least one product counter sensor, the number of products assembled by the assembly unit in par 030: “As yet more examples, the concentrator 116, treatment equipment 118, dryer 120, and/or scale 112 may include sensors for measuring relevant properties of the reaction products (e.g., the concentrator may record the weights of inputs and outputs and the scale 122 may record the weight of finished polymer). In at least some embodiments, the entirety (or nearly the entirety) of the production process is automatically monitored and relevant sensor readings automatically recorded.”
Per claim 22, Wollack and Schoeneboom teach the limitations of claim 1, above. Wollack further teaches comprising measuring, with the at least one energy supply sensor, the amount of energy supplied to the assembly unit in par 40: “In some embodiments, the packet 150c may additionally include mileage, fuel consumed, and/or other data associated with shipment and other movement of the product and its component parts up to the shipment of the product 168.”
See also in par 20 “Various sensors and user input devices may monitor a production process and record production details such as the weight of material produced, the amount of greenhouse gas destroyed or sequestered, the amount of power used (e.g., electricity, fuel, or other resources consumed during production).”
Claim(s) 10, 11, 15-17, 23-26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wollack et al., US PGPUB 20220237628 A1 (“Wollack”), in view of Schoeneboom et al., US PGPUB 20220108327 A1 ("Schoeneboom"), further in view of Dey et al., “Carbon Emission and Waste Reduction of a Manufacturing-Remanufacturing System using Green Technology and Automated Inspection,” RAIRO-Oper Res (2022) 2801-2831, published online April, 2022, available at: < https://doi.org/10.1051/ro/2022138 > (“Dey”).
Per claim 10, Wollack teaches A monitoring system for determining carbon footprint for one or more products assembled by an assembly unit, the system comprising: a memory configured to store real-time measurement data collected by a gateway from physical sensors using a communication protocol; and at least one processor coupled to the memory and configured to: in par 020: “During production of the materials, greenhouse gases such as methane and/or carbon dioxide are destroyed (or sequestered) through the conversion of methane to carbon dioxide, carbon dioxide to oxygen, and other processes. Various sensors and user input devices may monitor a production process and record production details such as the weight of material produced, the amount of greenhouse gas destroyed or sequestered, the amount of power used (e.g., electricity, fuel, or other resources consumed during production), the amount of water used in production, working conditions (e.g., the average wages and average working hours of workers involved in production of the carbon-sequestering raw materials), other production inputs, an expected rate of decay of the carbon-sequestering matter, and batch information (e.g., identification information), as examples.”
Wollack then teaches collecting, via the gateway, real-time measurement data generated by at least one product counter sensor configured to detect a number of products assembled by the assembly unit over time in par 030: “As yet more examples, the concentrator 116, treatment equipment 118, dryer 120, and/or scale 112 may include sensors for measuring relevant properties of the reaction products (e.g., the concentrator may record the weights of inputs and outputs and the scale 122 may record the weight of finished polymer). In at least some embodiments, the entirety (or nearly the entirety) of the production process is automatically monitored and relevant sensor readings automatically recorded.”
Wollack then teaches wherein the at least one product counter sensor comprises at least one of the physical sensors n par 030: “As yet more examples, the concentrator 116, treatment equipment 118, dryer 120, and/or scale 112 may include sensors for measuring relevant properties of the reaction products (e.g., the concentrator may record the weights of inputs and outputs and the scale 122 may record the weight of finished polymer). In at least some embodiments, the entirety (or nearly the entirety) of the production process is automatically monitored and relevant sensor readings automatically recorded.”
Wollack then teaches determining, by the processor, a number of assembled products in a period of time, based on the measurement data generated by the at least one product counter sensor in par 33: “In at least some embodiments, vendor 130 may send a materials packet such as second 150b. Second packet 150b may include any desired information including, but not limited to, the identity of the vendor (sometimes referred to as a fabricator), a unit count, an indication of the amount of polymer used, an indication of the amount of resins products, a production date, a ship date, a type of carbon-sequestering material or resin produced, and an amount of power consumed by the vendor during processing of the polymer.” Sensors which provide this information are taught in pars 65, 66, 68, 79.
Wollack then teaches collecting, via the gateway, real-time measurement data generated by at least one energy supply sensor configured to measure an amount of energy being supplied to the assembly unit over time in par 40: “In some embodiments, the packet 150c may additionally include mileage, fuel consumed, and/or other data associated with shipment and other movement of the product and its component parts up to the shipment of the product 168.” See also par 020 for the energy sensor and energy used in the production process, ie real time.
Wollack then teaches wherein the at least one energy supply sensor comprises at least one of the physical sensors in par 20 “Various sensors and user input devices may monitor a production process and record production details such as the weight of material produced, the amount of greenhouse gas destroyed or sequestered, the amount of power used (e.g., electricity, fuel, or other resources consumed during production),”
Wollack then teaches storing, by the monitoring system, the collected real-time measurement data generated by the at least one product counter sensor and the at least one energy supply sensor in a database using a database protocol in par 074 and references to storing in a blockchain in Wollack (see 54-69 but not limited to this) as blockchain teaches a database as it is a decentralized ledger.
Wollack then teaches determining, by the processor, an amount of supplied energy in the period of time, based on the measurement data collected via the gateway from the at least one energy supply sensor and stored in the database in par 20 “Various sensors and user input devices may monitor a production process and record production details such as the weight of material produced, the amount of greenhouse gas destroyed or sequestered, the amount of power used (e.g., electricity, fuel, or other resources consumed during production),”
Wollack then teaches determining, by the processor, a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the period of time, based at least on the number of assembled products in the period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time in par 53: “Another method for tracking carbon credits on a per-unit basis is shown in FIG. 3, which is a flow diagram of an illustrative method 300. The illustrative method 300 begins at block 302, where a blockchain node receives at least one data packet detailing carbon sequestered during production of raw materials such as a polymer or one or more proteins. The packet received in block 302 may be, as an example, a packet such as first packet 150a of FIG. 1A. The packet received in block 302 may include information such as a finished weight of raw materials, an amount of carbon-dioxide (or other greenhouse gas) consumed (e.g., destroyed or otherwise sequestered), an amount of power used, an amount of greenhouse gases produced as a result of the production, and identification information such as information identifying a batch of raw materials or identifying the producer of the raw materials, as examples (though not each is required in every embodiment).”
Wollack does not teach obtaining, by the processor, energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit
estimating, by the processor, an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time, based on the energy carbon footprint information;
displaying, on a graphical user interface, a per-assembled-product carbon-footprint value derived from the real-time measurement data collected via the gateway.
Schoeneboom teaches a method for determining a carbon footprint of a product. See abstract.
Schoeneboom teaches obtaining, by the processor, energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit in par 40: " The energy data is usually transformed into carbon footprints by taking into account the energy sources and their specific greenhouse gas emissions."
See also pars 046-047: “ "In some embodiments, the process according to the present invention further comprises (d) determining the carbon footprint of the product taking into account the process data, the carbon footprint of each raw material and the energy data.
Determining the carbon footprint of the product comprises summation of the carbon footprints of each raw material used in a particular process step as contained in the process data from step (a). If a process step requires an intermediate from a different process step, the sum of the carbon footprint of the raw material for this earlier process step is determined and used as input for the later process step. It may be necessary to repeat this if the earlier process step again uses an intermediate of an even earlier process step. If one process step yields more than one intermediate, for example two or three, it is necessary to share the carbon footprint of the raw materials among these intermediates. The share for each intermediate should reflect the raw material usage for each intermediate. In some cases, two intermediates are formed at the same amount, so the carbon footprint of the raw materials can be equally shared among them. In other cases, significantly more of one intermediate is formed than the other, for example 90% of intermediate 1 and 10% of intermediate 2. The carbon footprint should be shared accordingly. Hence, preferably, in the method of the present invention determining the carbon footprint involves, in some embodiments, calculating the carbon footprint for an intermediate produced in a preceding process step and using the carbon footprint of the intermediate as input for the calculation of the carbon footprint of a subsequent process step. In particular, in interconnected production processes, the calculation of the carbon footprint can be facilitated by subdividing it into analogous calculation parts, one for each process step. “
Schoeneboom then teaches estimating, by the processor, an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the period of time, based on the energy carbon footprint information in par 52: "Alternatively, preferably, the contribution of the energy for the product is determined for the product independent of the raw materials. To achieve this, the energy contribution for each process step is added according to the process data. If a process step yields more than one intermediate or the intermediate is used in more than one other process step, the contribution is shared among these, so only that part of the process step is taken into account which can be attributed to the product. For example, if one process step yields two intermediates at the same ratio and only one intermediate is used to produce the product, only half of the energy contribution of said process step is used for the determination of the energy contribution. "
See also pars 046-047: “ "In some embodiments, the process according to the present invention further comprises (d) determining the carbon footprint of the product taking into account the process data, the carbon footprint of each raw material and the energy data.
Determining the carbon footprint of the product comprises summation of the carbon footprints of each raw material used in a particular process step as contained in the process data from step (a). If a process step requires an intermediate from a different process step, the sum of the carbon footprint of the raw material for this earlier process step is determined and used as input for the later process step. It may be necessary to repeat this if the earlier process step again uses an intermediate of an even earlier process step. If one process step yields more than one intermediate, for example two or three, it is necessary to share the carbon footprint of the raw materials among these intermediates. The share for each intermediate should reflect the raw material usage for each intermediate. In some cases, two intermediates are formed at the same amount, so the carbon footprint of the raw materials can be equally shared among them. In other cases, significantly more of one intermediate is formed than the other, for example 90% of intermediate 1 and 10% of intermediate 2. The carbon footprint should be shared accordingly. Hence, preferably, in the method of the present invention determining the carbon footprint involves, in some embodiments, calculating the carbon footprint for an intermediate produced in a preceding process step and using the carbon footprint of the intermediate as input for the calculation of the carbon footprint of a subsequent process step. In particular, in interconnected production processes, the calculation of the carbon footprint can be facilitated by subdividing it into analogous calculation parts, one for each process step. “
Schoeneboom then teaches displaying, on a graphical user interface, a per-assembled-product carbon-footprint value derived from the real-time measurement data collected via the gateway in par 052: “To arrive at the total carbon footprint of the product, the contribution of the raw materials and the contribution of the energy is added. Hence, preferably determining the carbon footprint of the product comprises determining the contribution of the energy in each process step and add shares of it according to the process data.” Then per displaying on a graphical user interface, par 066: “In some embodiments, the system or apparatus according to the present invention comprises (c) an output or output unit configured to output the carbon footprint of the product, preferably the carbon footprint of the product and each contribution to it as obtained from the processor or processing unit. Preferably, the output or output unit has an interface to an ERP system or a computing system or apparatus, such as a centralized or decentralized computing system or apparatus including processing and storage. Preferably, the output or output unit comprises a user interface, in particular a graphical user interface. The user interface is preferably configured to display the carbon footprint of the product and each contribution, preferably comprising the contribution of the raw materials, the contribution of the energy, and the contribution of the direct emissions of each process step. Preferably, the user interface is configured to use graph technology. The user interface may be configured to provide an overview of each process step, its raw materials and energy required, the connection with other process steps. The user interface may also provide the carbon footprint for each process step, in particular it may be configured to display the carbon footprint originating from the raw materials, from the energy consumption, and from the direct greenhouse gas emissions separately and in aggregated form.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint teaching of Wollack with the energy calculations for carbon footprint teaching of Schoeneboom because Schoeneboom teaches in pars 005-006 that multiple sources of data have to be used for carbon footprint and were calculated manually which takes a long time, therefore one would be motivated to modify Wollack with Schoeneboom in order to calculate more quickly and efficiently, which would improve understanding of carbon footprints.
Wollack does not teach and obtaining, by the processor, reject product information associated with a number of rejected products over time, wherein the determination of the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the period of time is further based on component carbon footprint information associated with components in the rejected products.
Dey teaches a method for calculating manufacturing-remanufacturing emissions. See page 2801 (page 1 of PDF).
Dey teaches and obtaining, by the processor, reject product information associated with a number of rejected products over time, wherein the determination of the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the period of time is further based on component carbon footprint information associated with components in the rejected products in page 2813: Carbon emission cost for remanufacturing, where the T_3 and T variables teach time, teaching "over time." See also diagram on page 2809, and definitions on pages 2807-2808.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the emissions calculation and storage of information teaching of Wollack with the obtaining reject product and determination of carbon footprint of reject product teaching of Dey because Dey teaches on page 2805 where manufacturing systems are normally evaluated as perfect manufacturing systems which does not comport with reality (Examiner takes official notice that no manufacturing system is perfect) and Dey’s teaching further evaluates these elements with imperfect manufacturing, which enables carbon/emission/greenhouse gas calculations that are more realistic. As more realistic calculations better reflect reality, one would be motivated to combine Wollack with Dey.
Per claim 11, Wollack, Schoeneboom, and Dey teach the limitations of claim 10, above. Wollack further teaches wherein the assembly unit is an assembly station, an assembly line comprising multiple assembly stations, or an assembly factory comprising multiple assembly lines in par 32: “As shown in FIG. 1B, vendor 130 may receive a materials order 132 or a resin order 146, requesting shipment of specified carbon-sequestering materials or resins. Upon receipt of an order, the vendor may combine polymers from polymer inventory 136, with optional materials from materials inventory 138, and with various chemicals 140 in accordance with a resin formula 142 or some other recipe. The combined materials may be passed through an extruder 144 to produce carbon-sequestering materials such as resins 148. The resin order 152 may then be fulfilled by shipping 154 the appropriate amount of resins to a customer.”
Per claim 15, Wollack, Schoeneboom, and Dey teach the limitations of claim 10, above. Wollack further teaches the aggregated carbon footprint for all the assembled products in the period of time in par 080: “The amount of carbon credit associated with the batch of raw material may be determined based at least on (a) the amount of carbon prevented from entering the atmosphere when producing the batch of raw material and (b) the amount of power used in producing the batch of raw material. The receiving from the remote computing device of the first data packet may include receiving from the remote computing device the first data packet along with a digital signature generated with a private key of the remote computing device.”
Wollack does not teach upon determining the carbon footprint per assembled product, determining carbon footprint for all the assembled products in the period of time, and displaying, on the graphical user interface, carbon footprint information
Schoeneboom teaches upon determining the carbon footprint per assembled product, determining carbon footprint for all the assembled products in the period of time, and displaying, on the graphical user interface, carbon footprint information in pars 056-057: “"In some embodiments, the process according to the present invention further comprises (e) outputting the carbon footprint of the product obtained in step (d). Outputting can mean writing the carbon footprint on a non-transitory data storage medium, displaying it on a user interface, providing it to an interface for further processing or any combination thereof. It is also possible to provide the output through an interface to a customer, for example to the customers supply chain system or ERP system. It is also possible to provide the output through an interface to the EPR system of the producer itself from where it can be distributed to where this information is needed. When the carbon footprint and each contribution to it is output onto a user interface, the user interface preferably uses graph technology. In this way, it is possible to analyze the contributions along the production process in order to optimize the production process and thereby minimize the carbon footprint for the products. It is also possible to monitor changes of the carbon footprint upon changes in the production process. In addition, the output can be used to simulate effects of changes, for example by manually changing certain values and see its effect on the carbon footprint of the product. For example, the effect of replacing a particular raw material by one having lower carbon footprint for each product may be analyzed.
Preferably, the process further comprises outputting the carbon footprint for each process step as it contributes to the carbon footprint of a certain product. In this way, it is possible to analyze the contribution of each step, in particular the contribution of raw materials and energy in each step. This allows the identification of potential to reduce the carbon footprint of the product."
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint teaching of Wollack with the energy calculations for carbon footprint teaching of Schoeneboom because Schoeneboom teaches in pars 005-006 that multiple sources of data have to be used for carbon footprint and were calculated manually which takes a long time, therefore one would be motivated to modify Wollack with Schoeneboom in order to calculate more quickly and efficiently, which would improve understanding of carbon footprints.
Per claim 16, Wollack, Schoeneboom, and Dey teach the limitations of claim 10, above. Wollack further teaches for each of multiple periods of time, performing the following steps upon a respective period of time has elapsed: determining a number of assembled products in the respective period of time, based on the measurement data generated by the at least one product counter sensor in par 053 and 055, see par 055: “At block 306, a blockchain node receives at least one second data packet detailing fabrication of a plurality of goods from the raw materials. The packet received in block 306 may be, as an example, a packet such as third packet 150c of FIG. 1C. The packet received in block 306 may include information such as a plurality of unique product identifiers, a product type, a number of units of goods produced, and a production date, as examples. In some embodiments, the packet received in block 306 and the associated entry stored in block 308 may detail fabrication of an intermediary good, rather than a final product. In embodiments with multiple stages of intermediary goods, blocks 306 and 308 may be repeated for each stage of fabrication. In these and other embodiments, a final iteration of blocks 306 and 308 may be performed for the fabrication of final goods from the final intermediary product. In this manner, the final goods (and any intermediary goods) can be traced back to an associated entry stored in block 304, thus facilitating tracking of carbon sequestered in the final goods (and any intermediary goods).”
Wollack does not teach
determining an amount of supplied energy in the respective period of time, based on the measurement data generated by the at least one energy supply sensor
estimating an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the respective period of time, based on the energy carbon footprint information
determining a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the respective period of time, based at least on the number of assembled products in the respective period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the respective period of time
and displaying, on the graphical user interface, the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the respective period of time.
Schoeneboom teaches determining an amount of supplied energy in the respective period of time, based on the measurement data generated by the at least one energy in par 042: “Often, a production plant has multiple sensors providing data about the energy consumption of a certain process step or certain equipment.”
Then, Schoeneboom teaches estimating an amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the respective period of time, based on the energy carbon footprint information in par 052: “For example, if one process step yields two intermediates at the same ratio and only one intermediate is used to produce the product, only half of the energy contribution of said process step is used for the determination of the energy contribution. To arrive at the total carbon footprint of the product, the contribution of the raw materials and the contribution of the energy is added. Hence, preferably determining the carbon footprint of the product comprises determining the contribution of the energy in each process step and add shares of it according to the process data.”
Then, Schoeneboom teaches determining a carbon footprint per assembled product and/or an aggregated carbon footprint for all the assembled products in the respective period of time, based at least on the number of assembled products in the respective period of time and on the amount of greenhouse gas released into the atmosphere for generating the amount of supplied energy in the respective period of time in par 056: “In some embodiments, the process according to the present invention further comprises (e) outputting the carbon footprint of the product obtained in step (d). Outputting can mean writing the carbon footprint on a non-transitory data storage medium, displaying it on a user interface, providing it to an interface for further processing or any combination thereof. It is also possible to provide the output through an interface to a customer, for example to the customers supply chain system or ERP system.”
Then, Schoeneboom teaches and displaying, on the graphical user interface, the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the respective period of time in par 056: “ It is also possible to provide the output through an interface to the EPR system of the producer itself from where it can be distributed to where this information is needed. When the carbon footprint and each contribution to it is output onto a user interface, the user interface preferably uses graph technology. In this way, it is possible to analyze the contributions along the production process in order to optimize the production process and thereby minimize the carbon footprint for the products.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint teaching of Wollack with the energy calculations for carbon footprint teaching of Schoeneboom because Schoeneboom teaches in pars 005-006 that multiple sources of data have to be used for carbon footprint and were calculated manually which takes a long time, therefore one would be motivated to modify Wollack with Schoeneboom in order to calculate more quickly and efficiently, which would improve understanding of carbon footprints.
Per claim 17, Wollack, Schoeneboom, and Dey teach the limitations of claim 16, above. Wollack does not teach displaying, on the graphical user interface, a graph of the carbon footprints per assembled product and/or the aggregated carbon footprints for all the assembled products in the multiple periods of time.
Schoeneboom teaches displaying, on the graphical user interface, a graph of the carbon footprints per assembled product and/or the aggregated carbon footprints for all the assembled products in the multiple periods of time in par 066: “In some embodiments, the system or apparatus according to the present invention comprises (c) an output or output unit configured to output the carbon footprint of the product, preferably the carbon footprint of the product and each contribution to it as obtained from the processor or processing unit. Preferably, the output or output unit has an interface to an ERP system or a computing system or apparatus, such as a centralized or decentralized computing system or apparatus including processing and storage. Preferably, the output or output unit comprises a user interface, in particular a graphical user interface. The user interface is preferably configured to display the carbon footprint of the product and each contribution, preferably comprising the contribution of the raw materials, the contribution of the energy, and the contribution of the direct emissions of each process step. Preferably, the user interface is configured to use graph technology. The user interface may be configured to provide an overview of each process step, its raw materials and energy required, the connection with other process steps. The user interface may also provide the carbon footprint for each process step, in particular it may be configured to display the carbon footprint originating from the raw materials, from the energy consumption, and from the direct greenhouse gas emissions separately and in aggregated form. FIG. 5 shows schematically an example of how the user interface could be configured. The raw materials and the intermediates to the product are displayed according to the chain of interconnected process steps. The arrows represent process steps. Their width reflects the amount of greenhouse gases the respective process step contributes to the carbon footprint of the product. It may be possible to display further information when hovering over a box or an arrow with the mouse pointer, for example specifics about the raw material, intermediate or product or the exact value of the greenhouse gas emission. Preferably the carbon footprints are displayed in aggregated form showing the contributions of the raw materials, the energy usage and direct greenhouse gas emissions.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint teaching of Wollack with the energy calculations for carbon footprint teaching of Schoeneboom because Schoeneboom teaches in pars 005-006 that multiple sources of data have to be used for carbon footprint and were calculated manually which takes a long time, therefore one would be motivated to modify Wollack with Schoeneboom in order to calculate more quickly and efficiently, which would improve understanding of carbon footprints.
Per claims 23-26, which are similar in scope, Wollack and Schoeneboom teach the limitations of claims 1, 9, and 18, above, and Wollack, Schoeneboom, and Dey teach the limitations of claim 10, above. Wollack does not teach obtaining, by the processor, reject product information associated with a number of rejected products over time; and obtaining, by the processor, component-carbon footprint information associated with components of rejected products, wherein the determination of the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the period of time is further based on component carbon footprint information associated with components in the rejected products.
Dey teaches obtaining, by the processor, reject product information associated with a number of rejected products over time; and obtaining, by the processor, component-carbon footprint information associated with components of rejected products, wherein the determination of the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the period of time is further based on component carbon footprint information associated with components in the rejected products in page 2813: Carbon emission cost for remanufacturing, where the T_3 and T variables teach time, teaching "over time." See also diagram on page 2809, and definitions on pages 2807-2808.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the emissions calculation and storage of information teaching of Wollack with the obtaining reject product and determination of carbon footprint of reject product teaching of Dey because Dey teaches on page 2805 where manufacturing systems are normally evaluated as perfect manufacturing systems which does not comport with reality (Examiner takes official notice that no manufacturing system is perfect) and Dey’s teaching further evaluates these elements with imperfect manufacturing, which enables carbon/emission/greenhouse gas calculations that are more realistic. As more realistic calculations better reflect reality, one would be motivated to combine Wollack with Dey.
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wollack et al., US PGPUB 20220237628 A1 (“Wollack”), in view of Schoeneboom et al., US PGPUB 20220108327 A1 ("Schoeneboom"), further in view of Kienzle et al., US PGPUB 20130151303 A1 (“Kienzle”).
Per claim 20, Wollack and Schoeneboom teach the limitations of claim 19, above. Wollack further teaches (i) energy consumption in par 028: “energy monitors may cryptographically sign data blocks indicating the amount of power consumed,”
Wollack further teaches (ii) a per- product carbon-footprint value in par 068: “an amount of carbon-credits associated with the produced products (e.g., an aggregate amount that can later be divided by a unit count or a per-product amount)”
Wollack does not teach displaying, on the graphical user interface; (iii) a breakdown of carbon contributions based on energy consumption and component carbon footprint information, based on the real-time measurement data collected by the gateway and the component carbon-footprint information.
Schoeneboom teaches displaying, on the graphical user interface in par 066. Schoeneboom then teaches (iii) a breakdown of carbon contributions based on energy consumption and component carbon footprint information, based on the real-time measurement data collected by the gateway and the component carbon-footprint information in par 066: “Their width reflects the amount of greenhouse gases the respective process step contributes to the carbon footprint of the product. It may be possible to display further information when hovering over a box or an arrow with the mouse pointer, for example specifics about the raw material, intermediate or product or the exact value of the greenhouse gas emission. Preferably the carbon footprints are displayed in aggregated form showing the contributions of the raw materials, the energy usage and direct greenhouse gas emissions.” Based on real-time measurement data is taught in par 067: “Preferably, the system is adapted to receive updated data at any time and can update the output or carbon footprint and/or its contributions in real time, which usually means within less than a few minutes, preferably within less than a minute, for example within 1 to 30 seconds.”
Wollack does not teach (i) a time-series representation [carbon footprint] for the period of time
Kienzle teaches carbon footprint computation. See abstract.
Kienzle teaches (i) a time-series representation [carbon footprint] for the period of time in Fig 3 and par 040: “The average carbon footprint computation module 208 determines an average carbon footprint value based on the carbon footprint values of manufacturing processes over a limited period of time. For example, a manufacturing process based on a same order may generate different levels of carbon footprint over a period of time due to a multitude of manufacturing factors. The different levels of carbon footprints over a time interval 302 are illustrated in a chart 300 in FIG. 3. The horizontal axis 304 represents orders 302 or tasks placed in the time interval 302. The vertical axis 306 represents the amount of carbon footprint associated with each order. The average carbon footprint 308 per order within the interval 203 is represented by the horizontal line across the chart 300.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the carbon footprint determination system of Wollack, as modified by the display and graph teaching of Schoeneboom, with the time series representation demonstration of Kienzle because Kienzle teaches in par 002 that: “Also, the carbon footprint value may not be consistent throughout the flow of logistic processes because different combinations of materials and different processes produce different carbon footprint emissions. Further, common manufacturing processes do not have the means to track in real time how much carbon is generated during a manufacturing process. As such, common manufacturing planning processes cannot optimize their manufacturing processes in terms of carbon emission restrictions and other restrictions because this information is missing from their logistic planning process.” As Kienzle teaches the problem is determining the amount of carbon footprint emissions during manufacturing, Kienzle would motivate one ordinarily skilled to modify Wollack in view of Schoeneboom with Kienzle to better track in real time carbon generated during manufacturing.
Therefore, claims 1, 2, 6-11, and 15-26 are rejected under 35 USC 103.
Response to Remarks:
35 USC 101
Applicant starts by summarizing USPTO guidance which was followed by Examiner above. No substantive argument present. Then Applicant recites a memo from August 4 which was also followed by Examiner, also no substantive argument.
Applicant states:
“As discussed below, Applicant's recitation of real-time physical sensors, gateway
communication, and industrial monitoring reflects a meaningful integration of sensor data within an automated assembly environment, rather than an abstract idea. Applicant has further amended claim 1 to recite, among other things, that (1) the at least one product counter sensor that generates real-time measurement data comprises at least one of the physical sensors from which the gateway receives measurement data using a communication protocol, (2) the at least one energy supply sensor is configured to measure an amount of energy supplied to the assembly unit, and also comprises at least one of the physical sensors from which the gateway receives measurement data using a communication protocol, and (3) the processor displays, on a graphical user interface, a per-assembled-product carbon-footprint value (derived from the real-time measurement data collected via the gateway).
Using physical sensors to measure energy supplied to, and detect products assembled by, the assembly unit, receiving this real-time measurement data via a gateway using a communication protocol, processing the measurement data, and displaying a per-assembled- product carbon-footprint value on a graphical user interface derived from the real-time measurement data is not a mental process that can be done in the mind. Instead, it constitutes a practical application of measurement data within an automated industrial monitoring system. It reflects industrial monitoring operations using an assembly system that uses production and energy measurements to provide carbon footprint visualization in real time to a user/operator.”
Examiner disagrees. These are basic counting steps (1, 2, 3, … and so on) and analysis steps (averaging, dividing, etc) and the data comes from the sensors and are passed through or processed, without technical detail in the claims, by generic computing components. Examiner met the burden of showing that Applicant’s additional elements are generic and Applicant has not provided sufficiently persuasive evidence otherwise. Applicant’s argument is that “sensor data” (1, 2, 3, or # of kWh) is “integrated,” but this is an attempt to patent data or information which was properly identified as the abstract idea. There is no legal support for an integration of data to be an exception to the abstract idea identification. A human mind can readily take sensor data (1, 2, 3, for counting, or a quantity of kWh, for energy) and perform math on it. Graphical interface is just a computer screen, seen on all generic computing devices. Therefore this argument is unpersuasive.
Applicant remarks: “Additionally, new dependent claims 19 and 20 recite the particular types of the at least one product counter sensor (at least one light sensor, photoelectric barrier, pressure sensor, flow sensor, temperature sensor, a scale, a displacement sensor, a vision system, a good part counter sensor configured to count a number of products that are successfully assembled, or a reject counter sensor configured to count a number of products that are not successfully assembled and a stage of assembly associated with each not successfully assembled product), as well as additional graphical user interface detail (a time-series representation of energy consumption for the period of time, a per-product carbon-footprint value, and a breakdown of carbon contributions based on energy consumption and component carbon footprint information), based on the real-time measurement data collected by the gateway and the component carbon-footprint information.”
Examiner replies: These are interpreted in their broadest reasonable interpretation in light of the specification which per the sensor, is operating in its ordinary capacity and is therefore apply it, and the graphical user interface showing outputs that could be performed by pen and paper.
Applicant remarks: “New dependent claims 21-22 specify that the at least one product counter sensor and the at least one energy supply sensor respectively detect and measure the number of products assembled by the assembly unit and the amount of energy supplied to the assembly unit.”
Examiner replies: This is a similar limitation to what is in the independent claims, where here “detecting” is simply the sensor operating in its ordinary capacity and therefore is an apply it limitation.
Applicant remarks: “New dependent claim 23 recites features cancelled from previously recited claim 1, namely "obtaining, by the processor, reject product information associated with a number of rejected products over time; and obtaining, by the processor, component-carbon footprint information associated with components of rejected products, wherein the determination of the carbon footprint per assembled product and/or the aggregated carbon footprint for all the assembled products in the period of time is further based on component carbon footprint information associated with components in the rejected products." New dependent claims 24-26 recite these same features, and respectively depend from independent claims 9, 10, and 18.”
Examiner replies: Rejected for the same reason was rejected in the final rejection.
Applicant remarks: “It is respectfully submitted that the above-mentioned structural features, configurations, and processes integrate any purported judicial exception into a practical application (by using real-time physical sensor measurements from an automated assembly environment as inputs to an industrial monitoring process) to determine per-product carbon footprint values that reflect actual production and rejected component data.”
Examiner replies: The combination of generic elements recited by Applicant “physical sensors” and computing devices have been evaluated and are not a practical application as in combination they are sensors combined with a computer where the sensors operate in their ordinary capacity (nothing is claimed otherwise) to output what it is they sense (“counting”, “energy”) to the computer, which takes the data, analyzes it, and outputs the result, similar to Electric Power Group. Therefore there is no practical application.
Applicant remarks: “The claimed invention cannot be performed in the mind, enables carbon footprint visibility and energy use optimization to reduce greenhouse gas emissions (see paragraphs [0022]-[0023] and [0035]-[0036] of published application), and thus is an advancement and improvement over prior technology.”
Examiner replies: Nothing in the specification overcomes the showing by Examiner that the claimed steps are basic receiving, analyzing, and outputting the results of the data. The paragraphs were reviewed and essentially say, this is performed by a system, but logically speaking, just because steps are performed by a “system” does not exclude them from also being steps that one could perform mentally. Therefore this is not persuasive. Further, Applicant recites par 036 as an example but using a ‘parameter’ to convert ‘energy’ in kWh to CO2 is essentially saying A*x= y, where A is the parameter, x is energy, and y is CO2. A, would be a ratio, where the top part of the ratio is units of CO2, and bottom part is kWh. CO2 to KWh. This can be done mentally because it is multiplication.
As the arguments were not persuasive, the 101 rejection is maintained.
35 USC 103
Applicant remarks: “The Final Action admits that Wallack does not teach obtaining energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy supplied to the assembly unit, nor estimating an amount of
greenhouse gas released based on the energy carbon footprint information, but asserts that Schoeneboom teaches these features (Final Action, p. 11).
However, the Examiner's reliance on Schoeneboom does not cure the deficiencies of
Wollack with respect to amended claim 1. While Schoeneboom generally relates to determining a carbon footprint of products within a production plant, Schoeneboom does not disclose or suggest deriving an assembled product carbon footprint by explicitly time-correlating real-time product counter sensor data and real-time energy supply sensor data from the same assembly unit during the same period of time to compute a per-assembled-product footprint and/or an aggregated carbon footprint for all the assembled products in the manner claimed.”
Examiner replies: The combination of Wollack and Schoeneboom were shown to teach specific references, Applicant is attempting to argue one reference, then the other, but not the combination. The argument that “explicitly time-correlating real-time product counter sensor data and real-time energy supply sensor data from the same assembly unit” is not taught, is not addressed as this was explicitly not claimed. Rather the specific limitations above were addressed.
Applicant argues: “More particularly, even if Schoeneboom is assumed to teach converting energy to a carbon footprint, neither Wollack nor Schoeneboom teaches or suggests the combination of:
* collecting real-time production counts from physical product counter sensors on an assembly unit; (collecting, via the gateway, real-time measurement data generated by at least one energy supply sensor configured to measure an amount of energy supplied to the assembly unit over time, wherein the at least one energy supply sensor comprises at least one of the physical sensors)”
Examiner replies: As shown above, Wollack teaches this in par 030.
* correlating those production counts with real-time measured energy consumption
Examiner replies, As shown above, Wollack teaches this in par 040 and 020.
* determining per-assembled-product carbon footprint values derived from measured energy and production data (determining, by the processor, a carbon footprint per assembled product and or an aggregated carbon footprint for all the assembled products in the period of time).
Examiner replies, Wollack teaches this in par 20 “Various sensors and user input devices may monitor a production process and record production details such as the weight of material produced, the amount of greenhouse gas destroyed or sequestered, the amount of power used (e.g., electricity, fuel, or other resources consumed during production),”
Applicant remarks: “In Schoeneboom, energy and emission values are allocated to products based on production processes, models, or parameters associated with the production workflow, rather than derived from time-correlated physical sensor measurements of energy supplied to, and products assembled by, a specific assembly unit. Wollack similarly relies on tracking and reporting carbon-related information, but does not disclose sensor-based detection of assembled products over time that are time-correlated with measured energy supplied to an assembly unit.”
Examiner replies: it is the combination that teaches the limitations. The characterization of Wollack ignores the rejection where it is pointed out that sensors during production processes are recording this information see par 020. “Various sensors and user input devices may monitor and record, via one or more additional blockchain entries in the blockchain ledger, details of subsequent fabrication of products from the materials.” This refutes Applicant’s characterization that “tracking and reporting carbon-related information, but does not disclose sensor-based detection of assembled products over time that are time-correlated with measured energy supplied to an assembly unit” Note the word sensor in Wollack. Wollack further teaches sensors in
Par 028-30, 033, 040, 046, 081, 082, 085. Information from sensors taught in pars 065, 066, 068.
The combination of Wollack (teaching sensors) and data analysis, and Schoeneboom of further analysis, teaches the claims. Therefore this is unpersuasive and the rejection in essence is maintained.
Applicant remarks: “Dey discloses a mathematical optimization and modeling framework for manufacturing systems using assumed defect rates. Dey's analysis is predictive and model-based, not measurement-driven. Dey does not teach or suggest a real-time per-assembled-product footprint calculation derived from physical sensor measurements collected during operation of an assembly unit. In particular, Dey does not cure the deficiencies of Wollack and Schoeneboom as it does not teach or suggest:
collecting, via a gateway, real-time measurement data generated by at least one energy supply sensor configured to measure an amount of energy supplied to the assembly unit over time, wherein the at least one energy supply sensor comprises at least one of the physical sensors;
collecting, via the gateway, real-time measurement data generated by at least one energy supply sensor configured to measure an amount of energy supplied to the assembly unit over time; and determining, by the processor, a carbon footprint per assembled product and or an aggregated carbon footprint for all the assembled products... as recited by amended claim 1.”
Examiner remarks: Dey in combination with the other limitations teaches measuring “rejects” which is a data collection and analysis extension of the limitations of the independent claims like claim 10. It is not asserted to teach this limitation as Wollack in view of Schoeneboom teaches this.
Applicant argues: “Furthermore, the Final Action's 35 U.S.C. §103 rejections identify individual claim features across different references, but do not establish that the cited art teaches or suggests the claimed features as an integrated, measurement-driven, real-time monitoring system and methodology. As amended, the claims recite a specific technical combination of real-time sensor-based detection of assembled products at an assembly unit, real-time sensor-based measurement of energy supplied to the assembly unit, determination of per-assembled product carbon footprint values based on time-correlated physical measurements, and display of the resulting per-assembled-product carbon footprint values on a graphical user interface.”
Examiner replies: This argument doesn’t state a legal or guidance basis. But, if what Applicant is trying to say is that the combination does not work, Examiner disagrees, as plainly speaking Wollack teaches a majority of the independent claim, both by gathering data through sensors during production (real time), then processing that data to determine CO2 output during production. Further details of calculating are taught by Schoeneboom which one would be motivated to combine for the reasons above. There is nothing that prevents further analysis of data to be done, nor that it would not be integrated by one ordinarily skilled in the art. Therefore, this is not persuasive.
Applicant argues: “Dey does not teach collecting reject product information from an operating assembly unit via physical sensors over time, associating rejected products with specific physical components, and obtaining component-carbon footprint information associated with components of rejected products, let alone integrating reject-specific component carbon footprint information into a real-time per-assembled-product footprint calculation derived from physical sensor measurements of an assembly unit. New claims 24-26 recite the same features as claim 23, respectively depend from independent claims 9, 10, and 18, and thus are also patentable over Wollack, Schoeneboom, Dey, and Kienzle, individually and in combination, for at least the same reasons as claims 9, 10, and 18, and for reciting these additional features, which are not disclosed or suggested by Wollack, Schoeneboom, Dey, and Kienzle.”
Examiner replies: As shown in the previous and current rejections, Dey teaches determining CO2 emissions for remanufactured (rejected) items, and as this is a data collection and analysis add on (plainly speaking, more data collection and analysis steps, no new sensors or new generic computing components claimed) this would be combinable with Wollack and Schoeneboom for the motivation above. Therefore this is unpersuasive.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICHARD W. CRANDALL whose telephone number is (313)446-6562. The examiner can normally be reached M - F, 8:00 AM - 5:00 PM.
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, Anita Coupe can be reached at (571) 270-3614. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/RICHARD W. CRANDALL/ Primary Examiner, Art Unit 3619