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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy of the priority document has been received.
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on 12/05/2023 and 08/01/2024 are being considered 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(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.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by International Publication No. WO 2020/240039 to Financiera Maderera, S.A. (“Financiera”).
Regarding claim 1, Financiera discloses:
A method comprising (Financiera discloses “a moisture content control system and method for controlling a fibre moisture content in a fibreboard manufacturing process.” See, e.g., Financiera at Abstract):
controlling processing of wood particles into engineered wood products (Financiera discloses that a “first aspect of the invention relates to a moisture content control system for controlling a fibre moisture content in a fibreboard manufacturing process”(“controlling processing of wood particles into engineered wood products”). See, e.g., Financiera at p. 5, lines 10-15.)
by sensing interaction information associated with interaction between a plurality of steps in manufacturing the engineered wood products (Financiera discloses that a “first aspect of the invention relates to a moisture content control system for controlling a fibre moisture content in a fibreboard manufacturing process” (“manufacturing the engineered wood products”). See, e.g., Financiera at p. 5, lines 10-15. Financiera also discloses that [s]uch moisture control system comprises a plurality of sensors where each sensor is configured to monitor a respective parameter [(“interaction information”)] of the fibreboard manufacturing process … [and that] the sensors may be deployed in different points of the fibreboard production line to monitor the corresponding parameters” (“by sensing interaction information associated with interaction between a plurality of steps”). See, e.g., Financiera at p. 5, lines 10-15. Thus, Financiera discloses “controlling processing of wood particles into engineered wood products by sensing interaction information associated with interaction between a plurality of steps in manufacturing the engineered wood products.”) or
or [by sensing] interaction between a plurality of properties associated with materials used to make the engineered wood products (Financiera discloses that the “moisture control unit is also configured to compare the estimate or prediction generated with the pre-defined setpoint for the fibre moisture content [(“properties associated with materials”)] at the output of the drying stage and to modify at least one setpoint associated to a corresponding input drying temperature [(“properties associated with materials”)] of a respective drying unit of the fibreboard manufacturing process based on the result of the comparison.” See, e.g., Financiera at p. 5, line 35 to p. 6, line 2. Thus, Financiera discloses “controlling processing of wood particles into engineered wood products by sensing … interaction between a plurality of properties associated with materials used to make the engineered wood products).),
or [by sensing] interaction between said plurality of steps and said plurality of properties (Financiera disclose that “[d]epending on the number of drying units in the fibreboard production line, the moisture control unit may modify one or more of the setpoints associated to the input drying temperatures of the different drying units in the fibreboard production line.” See, e.g., Financiera at p. 6, lines 3-5. In addition, Financiera discloses that a neural network model “the fibre production manufacturing process from debarking to the last step of drying [(“plurality of steps”)] … from collected data [(“plurality of properties”)], and later, this model can be used to control and adjust the fibre drying process. Following this approach, the drying process can be adjusted taking into account any manufacturing process parameter variation. See, e.g., Financiera at p. 4, lines 27-30. Thus, Financiera discloses “controlling processing of wood particles into engineered wood products by sensing … interaction between a plurality of properties associated with materials used to make the engineered wood products”). ),
or [by sensing] interaction between said plurality of steps or said plurality of properties and an additional external factor which is external to said plurality of steps or said plurality of properties (See above for an analysis of the features “said plurality of steps or said plurality of properties.” Financiera also discloses that “the moisture control unit may consider an additional parameter, such a pre-established energy distribution between the drying units [(“an additional external factor which is external to said plurality of steps or said plurality of properties”)], and based on said additional parameter the moisture control unit may select the appropriate combinations of modified input drying temperatures for the drying units.” See, e.g., Financiera at p. 13, line 35 to p. 14, line 2. Thus, Financiera discloses “controlling processing of wood particles into engineered wood products by sensing … interaction between said plurality of steps or said plurality of properties and an additional external factor which is external to said plurality of steps or said plurality of properties”).),
processing the interaction information with machine learning and deriving from the machine learning improvement information associated with improving properties or yields or profitability of the engineered wood products (Financiera discloses that a “moisture control unit 403 receives a plurality of inputs corresponding to parameters related to the fibreboard manufacturing process… [and that] the moisture control unit 403, us[es] a neural network 411 [(“processing the interaction information with machine learning”)] that comprises at least one neural network layer, generates 408 [(“deriving from the machine learning”)] a prediction of the fibre moisture content at the output of the drying stage that is based on the received inputs” [(“improvement information associated with improving properties or yields or profitability of the engineered wood products”)]. See, e.g., Financiera at p. 17, lines 10-24. Financiera also discloses that “all the above-mentioned problems can be addressed using a neural network approach, where the fibre production manufacturing process from debarking to the last step of drying can be modelled from collected data [(“processing the interaction information with machine learning”)], and later, this model can be used to control and adjust the fibre drying process” (“improvement information associated with improving properties or yields or profitability of the engineered wood products”). See, e.g., Financiera at p. 4, lines 27-32. Financiera further discloses that the “moisture control unit may determine several combinations [(“processing the interaction information with machine learning”)] of modified input drying temperatures and select the combination of modified input drying temperatures [(“deriving from the machine learning”)] that, being within the pre-defined ranges of the respective input drying temperatures, optimizes the result” (“improving properties or yields or profitability of the engineered wood products”). See, e.g., Financiera at p. 13, lines 32-35. Thus, Financiera discloses the claimed “processing the interaction information with machine learning and deriving from the machine learning improvement information associated with improving properties or yields or profitability of the engineered wood products.”), and
implementing the improvement information back in the processing of the wood particles to achieve engineered wood products with improved properties or yields or profitability (“The moisture control unit 403 further compares 409 the prediction generated with the pre defined setpoint of the fibre moisture content at the output of the drying stage, and modifies 410 at least one setpoint [(“implementing the improvement information back in the processing of the wood particles”)] associated to a corresponding input drying temperature of a respective drying unit of the fibreboard manufacturing process based on the result of the comparison.” See, e.g., Financiera at p. 17, lines 10-24. Financiera also discloses that the “moisture control unit may determine several combinations of modified input drying temperatures and select the combination of modified input drying temperatures [(“implementing the improvement information back in the processing of the wood particles”)] that, being within the pre-defined ranges of the respective input drying temperatures, optimizes the result” (“to achieve engineered wood products with improved properties or yields or profitability”). See, e.g., Financiera at p. 13, lines 32-35. Financiera further discloses that “the system executes in real time an optimization of some of the parameters of the fibreboard manufacturing process to adjust the current values of said parameters [(“implementing the improvement information back in the processing of the wood particles”)], for example, the input temperatures of the dryers, in order to get an output fibre moisture content close to the reference value.” See, e.g., Financiera at p. 5, lines 6-9. Financiera further discloses that “any deviation of the percentage of moisture content in the fibre with respect to the setpoint can be anticipated and consequently, the input temperatures of the dryers can be automatically optimized and modified” (“to achieve engineered wood products with improved properties or yields or profitability”). See, e.g., Financiera at p. 14, lines 3-5.).
Regarding claim 2, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a log yard (The background section of Financiera discloses that a “fibreboard manufacturing process may comprise a first stage (chipping stage) [(“one of the steps in manufacturing the engineered wood products”)] in which the trunks are debarked and stripped in a chipper drum which reduces the logs into evenly shaped chips” (“processing at a log yard”). See, e.g., Financiera at p. 1, lines 27-29.).
Regarding claim 3, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a cutting station (The background section of Financiera discloses that a “fibreboard manufacturing process may comprise a first stage (chipping stage) [(“one of the steps in manufacturing the engineered wood products”)] in which the trunks are debarked and stripped in a chipper drum which reduces the logs into evenly shaped chips” (“processing at a cutting station”). See, e.g., Financiera at p. 1, lines 27-29.).
Regarding claim 4, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a dryer (Financiera discloses that at “a fourth stage (drying stage) of the fibreboard manufacturing process, the glued fibre is dried” (“dryer”). See, e.g., Financiera at p. 2, lines 19-33.).
Regarding claim 5, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a blender (Financiera discloses that at “a third stage (mixing or gluing stage) of the fibreboard manufacturing process, the resulting fibre may pass at very high speed and very high temperature through the blowline where it is mixed [(“blender”)] with resin or glue, among other products, that is introduced in a nebulized form.” See, e.g., Financiera at p. 2, lines 13-18.).
Regarding claim 6, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a forming or pressing station (Financiera discloses that at “ a sixth stage (forming stage) of the fibreboard manufacturing process, the fibre may be conveyed to the fibreboard forming system. The fibreboard forming system may transform the fibre pulp into a fibre mat [(“forming or pressing station”)] that is rolled through a series of equipment which produces a fibre mat with controlled weight.” See, e.g., Financiera at p. 3, lines 1-4.).
Regarding claim 7, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a sawing station (Financiera discloses that a “set of edge trimming saws [(“sawing station”)] may trim the edges of the fibre mat to give the desired width to the board.” See, e.g., Financiera at p. 3, lines 4-8.).
Regarding claim 8, Financiera discloses:
wherein the plurality of properties comprises at least two of temperature, torque, force, pressure, flow, moisture content, rotating speed, energy consumption, strand size or geometry, density, material physical properties, material chemical properties and constituent content (Financiera discloses that “the sensors may be volumetric sensors, temperature sensors [(“temperature”)], pressure sensors [(“pressure”)], speed sensors [(“speed”)]… [and that the] parameters collected by the plurality of sensors may be humidity [(“moisture content”)]of the chips; the position of the rotating disc, power of the motors involved in the process, and opening of the valve of the defibrator; speed [(“speed”)] of the endless screws, level of fibre, residence time and pressure [(“pressure”)] inside the digestor; amount of glue and other additives added at and vapour pressure inside the blowline; inlet and outlet temperatures [(“temperature”)], gas and air flows [(“flow”)] in the driers; external air humidity and temperature, etc.” See, e.g., Financiera at p. 12, line 30, to p. 13, line 5.).
Regarding claim 9, Financiera discloses:
wherein the external factor comprises at least one of season, time of day, ambient temperature, parameters from tree growing locations, machine wellness parameters, energy consumption, vibration, sound, reflection, particular labor or labor shift that performs an activity, worker behavior, data related to workers material prices, markets conditions, currency rates, storage capacity or supply chain data (Financiera discloses that the “parameters collected by the plurality of sensors may be … external air humidity and temperature [(“ambient temperature”)], etc.” See, e.g., Financiera at p. 12, line 30, to p. 13, line 5. Financiera also discloses that “the moisture control unit may consider an additional parameter, such a pre-established energy distribution [(“energy consumption”)] between the drying units, and based on said additional parameter the moisture control unit may select the appropriate combinations of modified input drying temperatures for the drying units.” See, e.g., Financiera at p. 13, line 35 to p. 14, line 2.).
Regarding claim 10, Financiera discloses:
wherein at least one of production yield or capacity, cost, profitability, and product quality is improved to a controlled level, while the rest of production yield or capacity, cost, profitability, and product quality are not affected within a controlled tolerance level or are purposely degraded to a controlled level (Financiera discloses “[t]o optimize the at least one setpoint, the moisture control unit may minimize the distance (or other defined cost function [(“cost is improved to a controlled level”)] which includes at least the distance as one term) between the moisture setpoint and the moisture prediction [(“product quality is improved to a controlled level”)], finding one value associated to the corresponding input drying temperature within the pre-defined range, considering a maximum variation, e.g., +-3°C, of the input temperature with respect to the current measurements of the input drying temperature[(“within a controlled tolerance level”)] , and considering that other current measurements of sensors used in the neural network model do not change [(“while the rest of production yield or capacity, cost, profitability, and product quality are not affected”)], which makes this said distance minimum..” See, e.g., Financiera at p. 6, lines 11-18.).
Regarding claim 11, Financiera discloses:
Apparatus comprising (Financiera discloses “a moisture content control system and method for controlling a fibre moisture content in a fibreboard manufacturing process.” See, e.g., Financiera at Abstract):
a controller in operative communication with sensors (Financiera discloses a moisture control unit 403 (“controller”) that is connected to sensor1 to sensor (“sensors”). See, e.g., Financiera at p. 16, line 25 to p. 17, line 5.),
said controller being configured to control processing of wood particles into engineered wood products by processing interaction information, sensed by said sensors, associated with interaction between a plurality of steps in manufacturing the engineered wood products or interaction between a plurality of properties associated with materials used to make the engineered wood products, or interaction between said plurality of steps and said plurality of properties, or interaction between said plurality of steps or said plurality of properties and an additional external factor which is external to said plurality of steps or said plurality of properties, said controller being configured to process the interaction information with machine learning and deriving from the machine learning improvement information associated with improving properties or yields or profitability of the engineered wood products, and implementing the improvement information back in the processing of the wood particles to achieve engineered wood products with improved properties or yields or profitability (The remaining features of claim 11 are substantially the same as those recited in claim 1 and thus are disclosed by Financiera for the reasons given above with respect to claim 1.).
Regarding claim 12, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a log yard (This feature is the same as that recited in claim 2 and thus is disclosed by Financiera for the reasons given above with respect to claim 2.).
Regarding claim 13, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a cutting station (This feature is the same as that recited in claim 3 and thus is disclosed by Financiera for the reasons given above with respect to claim 3.).
Regarding claim 14, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a dryer (This feature is the same as that recited in claim 4 and thus is disclosed by Financiera for the reasons given above with respect to claim 4.).
Regarding claim 15, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a blender (This feature is the same as that recited in claim 5 and thus is disclosed by Financiera for the reasons given above with respect to claim 5.).
Regarding claim 16, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a forming or pressing station (This feature is the same as that recited in claim 6 and thus is disclosed by Financiera for the reasons given above with respect to claim 6.).
Regarding claim 17, Financiera discloses:
wherein one of the steps in manufacturing the engineered wood products comprises processing at a sawing station (This feature is the same as that recited in claim 7 and thus is disclosed by Financiera for the reasons given above with respect to claim 7.).
Regarding claim 18, Financiera discloses:
wherein the plurality of properties comprises at least two of temperature, torque, force, pressure, flow, moisture content, rotating speed, energy consumption, strand size or geometry, density, material physical properties, material chemical properties and constituent content (This feature is the same as that recited in claim 8 and thus is disclosed by Financiera for the reasons given above with respect to claim 8.).
Regarding claim 19, Financiera discloses:
wherein the external factor comprises at least one of season, time of day, ambient temperature, parameters from tree growing locations, machine wellness parameters, energy consumption, vibration, sound, reflection, particular labor or labor shift that performs an activity, worker behavior, data related to workers material prices, markets conditions, currency rates, storage capacity or supply chain data (This feature is the same as that recited in claim 9 and thus is disclosed by Financiera for the reasons given above with respect to claim 9.).
Regarding claim 20, Financiera discloses:
wherein at least one of production yield or capacity, cost, profitability, and product quality is improved to a controlled level, while the rest of production yield or capacity, cost, profitability, and product quality are not affected within a controlled tolerance level or are purposely degraded to a controlled level (This feature is the same as that recited in claim 10 and thus is disclosed by Financiera for the reasons given above with respect to claim 10.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chinese Publication No. CN 109711611A to DING, LEI discloses using a neural network to optimize cutting wood panels to improve output.
Chinese Publication No. CN 109789658A to DROGE, P discloses using a neural network to adjust temperature in manufacturing material boards.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BHASKAR KAKARLA whose telephone number is (571)272-8221. The examiner can normally be reached Mon-Fri.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kenneth M. Lo can be reached at 571-272-9774. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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.
/B.K./Examiner, Art Unit 2116
/KENNETH M LO/Supervisory Patent Examiner, Art Unit 2116