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 .
Applicant’s Response
In Applicant’s response dated 08/07/2026, Applicant amended Claims 1, 4 – 9, 11, 12 and 14 – 16; canceled Claims 2, 3, and 13; and argued against all objections and rejections previously set forth in the Office Action dated 06/09/2026.
In light of Applicant’s amendments and remarks, the previously set forth objection to the Drawings is withdrawn.
In light of Applicant’s amendments and remarks, the previously set forth objections to the Claims are withdrawn.
In light of Applicant’s amendments and remarks, the claims are no longer interpreted under 35 U.S.C. 112(f).
Status of the Claims
Claim 11 is rejected under 35 U.S.C. 102(a)(2) and Claims 12 and 14 – 17 are rejected under 35 U.S.C. 103.
Examiner Note
The Examiner cites particular columns, line numbers and/or paragraph numbers in the references as applied to the claims below for the convenience of the Applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the Applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim 11 is rejected under 35 U.S.C. 102(a)(1)/102(a)(2) as being anticipated by Kaufman et al. (US 2010/0274377) (hereinafter, Kaufman).
Regarding Claim 11, Kaufman teaches a method of energy-saving management for a manufacturing machine (See Kaufman’s Abstract and par 0040), including steps of:
measuring an energy usage of the manufacturing machine (Kaufman in par 0021 and Fig. 1, teaches that the system 100 includes a plurality of discrete monitors 110 that are stationed throughout an industrial system or process and are employed to collect data from various sustainability factor sources 120. An energy manager or processor 140 collects the tagged data and links the tagged data with a manufacturing model 150 to produce a model or specification 160 that includes the discrete or batch process components that have been associated with the respective sustainability factors or source data 120. By associating energy or other sustainability factors with the manufacturing model or specification at 160, various efficiencies can be provided for and managed within the factory since each item's energy/sustainability factor component can now be accounted for and traced as a component of the respective discrete or batch process. Kaufman in par 0033, further teaches that energy monitoring on the production floor can be tied to an energy tracking software package and correlate production output to the energy consumed. Energy could be metered and the empirical results could be added to the production Bill of Material (BOM));
detecting, in real-time, a quantity of products being concurrently processed by the manufacturing machine per unit of time (Kaufman in par 0009, teaches that as the respective processes are monitored, sources associated with sustainability-factor data such as energy that is collected is tagged to indicate which portion of the discrete or batch process that the source contributed to. The source data that is associated with the BOM can now be analyzed in real-time or via offline modeling to optimize and mitigate energy usage. For example, portions of a process may be rearranged to minimize overall energy usage. Kaufman in par 0031 and Fig. 3, further teaches that the product itself may be associated with a factor as illustrated in FIG. 3, where various products outlined in an example bill of material 300 in a left column 310 are associated with example sustainability factors such as electrical usage 320, peak demand 330, carbon dioxide 340, nitrogen oxide 350, and sulfur dioxide 360. Kaufman in par 0035 – 0036, further teaches that production tools for material forecasting can be used for energy forecasting when energy is added to the bill of material (BOM) 300. Manufacturing can forecast demands on infrastructure such as compressed air, steam, electricity, natural gas, and water, for example. A manufacturing execution system (MES) is a control system for managing and monitoring work-in-process on a factory floor. An MES tracks manufacturing information in real time, receiving up-to-the-minute data from robots, machine monitors and employees);
calculating energy consumption data per unit of time (Kaufman in par 0025, teaches that the system 100 allows extracting energy or other consumption data from the plant floor or other sources of sustainability factor data and correlating it to production output. Kaufman in par 0031 and Fig. 3, further teaches that the product itself may be associated with a factor as illustrated in FIG. 3, where various products outlined in an example bill of material 300 in a left column 310 are associated with example sustainability factors such as electrical usage 320. Kaufman in par 0034, further teaches that production process simulations performed to analyze labor could be adjusted to analyze energy consumption just by exchanging KWh for minutes, for example. Empirical energy data could be used to optimize energy consumed against products per hour);
generating energy consumption data per unit of product and carbon emission data per unit of product by utilizing a carbon emission factor and according to the energy consumption data and the quantity of products processed per unit of time (Kaufman in par 0025, teaches that the system 100 allows extracting energy or other consumption data from the plant floor or other sources of sustainability factor data and correlating it to production output. This enables applying standard production modeling tools for production energy and emission forecasting and optimization. Kaufman in par 0031 and Fig. 3, further teaches that the product itself may be associated with a factor as illustrated in FIG. 3, where various products outlined in an example bill of material 300 in a left column 310 are associated with example sustainability factors such as electrical usage 320, peak demand 330, carbon dioxide 340, nitrogen oxide 350, and sulfur dioxide 360. Kaufman in par 0035, further teaches that production emission rates can be calculated and applied to the BOM 300. Again, allowing standard production forecasting tools to forecast emission against Cap and Trade regulations, for example. Energy information on the BOM 300 can aid in prioritizing production schedules to load level demand. Adjusting schedules based on peak demand times can reduce the overall cost of energy consumed); and
displaying the energy consumption data per unit of product and the carbon emission data per unit of product (Kaufman in par 0031 and Fig. 3, further teaches that the product itself may be associated with a factor as illustrated in FIG. 3, where various products outlined in an example bill of material 300 in a left column 310 are associated with example sustainability factors such as electrical usage 320, peak demand 330, carbon dioxide 340, nitrogen oxide 350, and sulfur dioxide 360. Kaufman in par 0033, further teaches that energy monitoring on the production floor can be tied to an energy tracking software package and correlate production output to the energy consumed. Energy could be metered and the empirical results could be added to the production Bill of Material (BOM). FIG. 3 shows an example of electricity data at 310 and 320 extracted from the BOM 300).
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.
Claims 12 and 14 – 16 are rejected under 35 U.S.C. 103 as being unpatentable over Kaufman in view of Ly Seymour et al. (US 2025/0103043) (hereinafter, Seymour).
Regarding Claim 12, Kaufman teaches the limitations contained in parent Claim 11.
However, Kaufman does not specifically disclose further comprising determining whether the energy consumption data per unit of product or the carbon emission data per unit of product exceeds a preset value; and displaying an alert message when the energy consumption data per unit of product or the carbon emission data per unit of product exceeds the preset value.
Seymour teaches a system and method for monitoring and controlling production of batches of products in an industrial process (See Seymour’s Abstract). Seymour in par 0011, further teaches that if the key performance indicators (KPIs) are above one or more pre-determined thresholds, taking a corrective action in response to the key performance indicators being above the one or more pre-determined thresholds. Seymour in par 0165, further teaches that there may be pre-determined thresholds which set a limit for energy costs, energy demand, energy consumption, and emission levels. Key performance indicators (KPIs) generated at step 2806 are above these pre-determined thresholds, then the energy management system 2700 may take a corrective action to address these KPIs being above the predetermined threshold at step 2812. The corrective action may including highlighting and displaying unexpected energy usage such as when equipment is unnecessarily kept in operation. The corrective action may include generating a notification alert which is sent to users when a target energy consumption amount is about to exceed a threshold so that the operation personnel can proactively reduce usage in order to avoid peak usage cost penalties.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Seymour with the teachings as in Kaufman to display to the user of Kaufman a notification alert when exceeding a threshold as disclosed in Seymour. The motivation for doing so would have been to effectively notify the user that the consumption amount is about to exceed a threshold so that the user can proactively reduce usage in order to avoid peak usage cost penalties (See Seymour’s par 0165).
Regarding Claim 14, Kaufman in view of Seymour teaches the limitations contained in parent Claim 12. Seymour further teaches:
further comprising a step of activating an energy-saving mode of the manufacturing machine when the energy consumption data per unit of product or the carbon emission data per unit of product exceeds the preset value (Seymour in par 0122, Based on the corrective action, the baseline for one or more KPIs may automatically be adjusted. Seymour in par 0165, further teaches that there may be pre-determined thresholds which set a limit for energy costs, energy demand, energy consumption, and emission levels. Key performance indicators (KPIs) generated at step 2806 are above these pre-determined thresholds, then the energy management system 2700 may take a corrective action to address these KPIs being above the predetermined threshold at step 2812. The corrective action may including highlighting and displaying unexpected energy usage such as when equipment is unnecessarily kept in operation. The corrective action may include generating a notification alert which is sent to users when a target energy consumption amount is about to exceed a threshold so that the operation personnel can proactively reduce usage in order to avoid peak usage cost penalties).
Regarding Claim 15, Kaufman teaches the limitations contained in parent Claim 11.
However, Kaufman does not specifically disclose further comprising a step of sending the energy consumption data per unit of product and the carbon emission data per unit of product to a cloud server.
Seymour in par 0060, teaches that the asset intelligence application is a cloud-based Software as a Service (SAAS) offering that contextualizes data by using pre-built industry specific asset models, surfaced in dashboards with alert notification management and the ability to configure by persona and user. Seymour in par 0141, further teaches that the extracted data 2602 may be sent to the cloud computing system 2403 where the data is processed. The cloud computing system 2403 also stores the batch analytics models 2414 and the extracted data 2602 in data storage (e.g., raw and inference data storage 2426). The data stored in the cloud computing system 2403 may be sent to the SAAS application 2405).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Seymour with the teachings as in Kaufman to utilize cloud services in Kaufman as disclosed in Seymour. The motivation for doing so would have been to effectively improve the reliability and availability of physical assets while minimizing risk and operating costs within an industrial plant (See Seymour’s par 0060).
Regarding Claim 16, Kaufman in view of Seymour teaches the limitations contained in parent Claim 12. Seymour further teaches:
further comprising a step of activating an indicator light when the energy consumption data per unit of product or the carbon emission data per unit of product exceeds the preset value (Seymour in par 0038 and Fig. 29A, teaches a user interface implemented by the energy management system. Seymour in par 0060, that the asset intelligence application is a cloud-based Software as a Service (SAAS) offering that contextualizes data by using pre-built industry specific asset models, surfaced in dashboards with alert notification management and the ability to configure by persona and user. Seymour in par 0069 and Fig. 10, further teaches that the health advisory user interface portion 1004 may display the relative number of active advisories based on their severity level (e.g., warning, alert, and critical). Seymour in par 0165, further teaches there may be pre-determined thresholds which set a limit for energy costs, energy demand, energy consumption, and emission levels. If the KPIs generated at step 2806 are above these pre-determined thresholds, then the energy management system 2700 may take a corrective action to address these KPIs being above the predetermined threshold at step 2812. The corrective action may include generating a notification alert which is sent to users when a target energy consumption amount is about to exceed a threshold so that the operation personnel can proactively reduce usage in order to avoid peak usage cost penalties).
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Kaufman in view of Pokorny et al. (US 2003/0154144) (hereinafter, Pokorny).
Regarding Claim 17, Kaufman teaches the limitations contained in parent Claim 11.
However. Kaufman does not specifically disclose further comprising a step of identifying bar codes on products when calculating the quantity of the products being processed.
Pokorny teaches a method of tracking production information, a method of analyzing event-based production information to provide financial reports, a method of adapting an online production documentation system to provide financial report data, and a production documentation system (see Pokorny’s Abstract). Pokorny in par 0084, further teaches that prior to loading a raw material onto the converting machine, material label information is transferred to the raw materials database (such as from label bar codes using bar code scanners). This includes material label information such as part number, lot number, and quantity. The converting line keeps a product counter that resets at a fixed preset. This product counter is a reference number that is transferred to the database on certain machine events. Pokorny in par 0151, further teaches handling raw materials in the production of an article, a label with one or more bar codes is typically applied to a container or to the material itself to provide information about the source and properties of the material. Those using the material in manufacturing scan the bar code to extract information. Multiple scans are often needed to extract information from multiple bar codes on a label, such as bar codes for manufacturer item number, vendor lot number, and quantity.
Therefore, it would have been obvious to one of ordinary in the art before the effective filing date to utilize the teachings as in Pokorny with the teachings as in Kaufman to include a barcode in the products of Kaufman as disclosed in Pokorny. The motivation for doing so would have been to effectively track and count the manufactured pieces (See Pokorny’s par 0151).
Allowable Subject Matter
Claims 1, 4 – 10 are allowed.
Reasons for Allowance
The following is a statement of reasons for the indication of allowable subject matter:
Based on the broadest reasonable interpretation (BRI) and in light of the Specification, the Examiner finds the claimed invention as recited in Claims 1 and 4 – 10 patentably distinct from the prior art of record.
The closest prior art of record Kawaguchi et al. (US 2025/0104166) (continuation of PCT/JP2022/030035 filed on August 5, 2022)(hereinafter, Kawaguchi), Kaufman et al. (US 2010/0274377) (hereinafter, Kaufman), Ly Seymour et al. (US 2025/0103043) (hereinafter, Seymour) and Pokorny et al. (US 2003/0154144) (hereinafter, Pokorny) fail to teach or suggest the invention as recited in independent Claim 1.
Due to at least their dependency upon Claim 1, the prior art of record also fails to disclose Claims 4 – 10 as claimed.
Response to Arguments
Applicant’s arguments, see remarks pages 1 – 7, filed 08/07/2026, with respect to Claims 1 and 4 – 10 have been fully considered and are persuasive. The rejection of claims 1 and 4 – 10 has been withdrawn.
Applicant’s arguments, see remarks pages 8 – 10, filed 08/07/2026, with respect to the rejection(s) of claim(s) 11, 12 and 14 – 17 under 35 U.S.C. 102 (a)(2) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Kaufman et al. (See the above rejections).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARIEL MERCADO VARGAS whose telephone number is (571)270-1701. The examiner can normally be reached M-F 8:00am - 4:00pm.
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/ARIEL MERCADO-VARGAS/ Primary Examiner, Art Unit 2118
