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 . This action is made final.
Claims 1, 3, 5, 7, 9, 12, and 15-17 filed on 12/01/2025 have been reviewed and considered by this office action.
Claims 1, 3, 5, 7, 9, 12, 13, 15, and 16 have been amended.
Claims 2, 4, 6, 8, 10, 11, and 14 have been cancelled.
Claim 17 has been newly added.
Drawings
The drawings filed on 12/01/2025 have been reviewed and are considered acceptable.
Specification
The specification filed on 12/01/2025 has been reviewed and is considered acceptable.
Claim Objections
Claim 17 is objected to because of the following informalities:
In claim 17, “wherein control of the linear component is addressed through tilt control, the quadratic component addressed through bend control, and a residual effort regulated through nozzle control” should read “wherein control of the linear component is addressed through tilt control, the quadratic component is addressed through bend control, and a residual effort is regulated through nozzle control”
Appropriate correction is required.
Claim Interpretation
The term “bump test” in claims 4, 8, and 16 has no specific meaning in the art. For the purpose of examination, Examiner interprets this to mean a procedure whereby an operating parameter is altered and changes of certain dependent variables resulting therefrom are measured and recorded after the system has reached steady state operation, per Page 9, Lines 20-23 of Applicant’s specification.
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
means of determining the thickness of the sheet metal exiting the roll stand in claim 9, which is interpreted as a thickness sensor or equivalent thereof performing the claimed function, as supported in Fig. 1 and Page 4, Lines 15-16 of Applicant’s Specification
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 15 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 15 depends on cancelled claim 14. For the purpose of examination, claim 15 will be interpreted as depending on independent claim 9.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3, 5, 7, 9, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Jelali et al. (WO 2005/072886 A1), in view of Fairlie et al. (US 2017/0259313 A1), and in view of Cuznar et al. (K. Cuznar and M. Glavan, “Optimization of cold rolling process recipes based on historical data,” 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), Palermo, Italy, 2022, pp. 1-6, doi: 10.1109/MELECON53508.2022.9843127), herein Cuznar.
Regarding claim 1, Jelali teaches a controller for controlling thickness and flatness of sheet metal in a mill exiting a roll stand comprising a first work roll and a second work roll respectively positioned between a first back up roll and a second back up roll, the controller comprising:
receive an input comprising a first measurement of the thickness and the flatness of the sheet metal exiting the roll stand (Page 7, Lines 12-13: “the flatness deviation is determined using a flatness measuring system at the exit of the stand”; Page 3, Lines 8-15: “the control method according to the invention generates input variables for the controller depending on the measured values of the measuring systems. These input variables are used by the controller to generate at least one control signal for at least one control variable of the rolling stand based on an integrated, model-predictive thickness, tension and flatness control. Preferably, separate measuring systems are provided for the thickness, flatness and tension of the strip. However, within the scope of this invention, measuring systems can also be used that determine several variables, such as thickness and flatness, simultaneously”);
generate a predictive model of the roll stand, (Page 3, Lines 20-22: “The controller uses a prediction model to predict the future system behavior. The controller is preferably an MPC (Model Predictive Control) controller embedded in an IMC (Internal Model Control) structure” to model the roll stand; Page 4, Lines 35-36: “The controller preferably uses an explicit, linear or non-linear online-capable profile and flatness model that takes into account the essential variables and actuators involved in the rolling process”; Page 6, Lines 34-36: “The coupling between thickness, tension and flatness is taken into account by a decoupling matrix, which can be calculated from the inverse of the total transfer matrix of the thickness and flatness control system”);
calculate a second measurement of the thickness and the flatness of the sheet metal based on the current state (Page 7, Lines 24-26: “The multivariable controller consists of an online-capable model and a dynamic optimization taking into account manipulated variable constraints and predicted controlled variable characteristics,” where an online model calculates a second measurement);
predict a future measurement of the thickness and the flatness of the sheet metal using the predictive model and a difference between the first measurement and the second measurement of the thickness and the flatness of the sheet metal (Page 2, Lines 18-23: “The invention is based on the basic idea of controlling thickness, tension and flatness with a single controller within the framework of an integrated, model-predictive thickness, tension and flatness control. The integrated control system takes into account the influence that the adjustment of control variables has on the thickness, the tension as well as the flatness of the rolled strip and can optimize the change of the control variables in such a way that a selected quality of the thickness control and the flatness control is achieved,” which means that thickness and flatness are controlled variables; Page 4, Line 26: “the prediction of the controlled variable is included in the dynamic optimization”; Page 7, Lines 15-23: “The flatness profile (flatness distribution) is estimated directly based on the individual measurement results. The estimated flatness curve is decomposed into orthogonal (independent) components… The orthogonal components thus determined are compared with values provided by an online model of the system. The resulting difference is used as a controlled variable and fed to the multi-variable controller 3”);
dynamically generate a signal for adjusting one or more actuators for controlling one or more of: (Page 2, Lines 18-20: “The invention is based on the basic idea of controlling thickness, tension and flatness with a single controller within the framework of an integrated, model-predictive thickness, tension and flatness control”; Page 7, Lines 27-29: “From the input variable, the controller determines control signals for roll bending, roll swiveling, axial displacement of the rolls as well as for multi-zone cooling and, if necessary, a change in the support roll shape”).
Fairlie teaches dynamically generate a signal for adjusting one or more actuators for controlling one or more of: a roll force, a mill speed and/or ([0055]: “The fast loop controller 668 may adjust one or more rolling mill control mechanisms to influence the roll gap geometry. For example, the rolling mill may include rolling mill control mechanisms such as, but not limited to, work roll heating 684, work roll cooling 686, work roll bending 688, CVC roll positioning 690, deformable backup roll pressure 692, roll tilting 694, roll crossing and/or pair crossing 696, differential strip cooling 697, work roll position 698, differential rolling load 700, rolling speed 702, speed difference between rolling stands 704, roll torque 706 and/or rolling load 708,” where roll torque corresponds to a roll force and rolling speed corresponds to a mill speed).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the controller of Jelali to incorporate the teachings of Fairlie so as to include a controller output coupled to control a roll gap between the first work roll and the second a work roll, a roll force, and/or a mill speed to produce the sheet metal. Doing so would allow parameters to be used for feedback control of a rolling mill with the aim of improving product quality and minimizing waste (Fairlie, [0020]: “Interstand measurement of the thickness profile and/or other properties or parameters of the metal sheet or plate, often referred to as the strip, along with measurement of roll thermal camber, roll gap geometry and/or monitoring of other rolling mill process parameters, provides information about the current operating conditions of the hot rolling mill and allows an operator or control system to compensate for constant or dynamic variances or irregularities. Interstand measurements of the metal strip thickness profile and/or other properties or parameters such as roll thermal camber and roll gap geometry and/or mill process parameter measurements may be used to more accurately control the rolling mill, to determine which rolling stand may be causing excessive variance, and to replace or support setup tables and mathematical models with direct measurement and feedback loop and/or other, more advanced controls. Improved control over the rolling mill and individual rolling stands allows for production of higher quality products and reduced waste because the rolling mill and rolling stands may react faster to out of specification sheet to minimize the amount of unacceptable product and/or adjust subsequent rolling stands to compensate with no or reduced loss of material”).
While Jelali teaches online controller adaptation (Page 8, Lines 4-8: “In order to compensate for changes in the dynamic behavior, which can be caused, for example, by wear, the replacement of components of the rolling stand and changes in the material properties of the rolling stand, the models are adapted online during the rolling of a single strip”), Jelali and Fairlie do not explicitly teach “a memory storing executable code, for implementing a model--based multi-variable predictive control, and one or more processors” and “wherein the predictive model is derived from a bump test.”
Cuznar further teaches a memory storing executable code, for implementing a model--based multi-variable predictive control, and one or more processors (Page 5, Section V: “two main graphical user interfaces (GUIs) were developed: Optimizer and Simulator, which contain identified models and optimization/simulation algorithms. Since the GUI is intended to be accessible to multiple users simultaneously through a web browser, the ‘Flask’ platform is used to enable web page creation”) and
wherein the predictive model is derived from a bump test (Page 2, Section III: “In order to develop a suitable feature extraction algorithm, we must first define the purpose of the models. The objectives pursued are to advise optimal recipe parameters: 1) before initial rolling, 2) before next rolling pass, 3) in real-time during the rolling. From an identification point of view, each of the objectives differs in the amount of information available at a given time that can be used to predict the quality indicator… The cold rolling process is usually operating in a steady-state. Therefore, the analysis focuses on the sections where steady-state operation is present”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the controller of Jelali in view of Fairlie to incorporate the teachings of Cuznar so as to include the model being identified by employing a bump test of the roll stand. Doing so would allow for model parameter identification with the aim of optimizing production performance (Cuznar, Page 6, Section VI: “The model predictions can be used to check the suitability of the recipes already in use and to optimize the recipe settings based on the information available at a given time. The presented approach is based on the analysis of historical data to identify new knowledge and use this knowledge to optimize production performance”).
Regarding claim 3, Jelali in view of Fairlie teaches the controller of claim 1.
While Jelali teaches the model comprising tension, tilt control, and bending control (Page 3, Lines 2-4: “The rolling forces also depend on the strip tension. This results in a strong coupling between tension, thickness and flatness control. According to the invention, these are taken into account by the model used by the controller in one controller”; Page 3, Lines 17-19: “The control variables of the rolling process are understood to include, in particular, roll bending, roll pivoting, roll shifting, roll cooling, in particular selective multi-zone cooling, and also the change of the support roll shape”), Jelali does not explicitly teach “wherein the predictive model is further based on one or more of: roll gap, roll force, entry tension, mill speed, spray parameters, tilt control, and bending control.”
Fairlie further teaches wherein the predictive model is further based on one or more of: roll gap, roll force, entry tension, mill speed, spray parameters, tilt control, and bending control ([0018]: “setup or production parameters may include, but are not limited to, thickness reduction, work roll position, differential rolling load, rolling speed, speed differences between individual stands of the rolling mill, roll torque, and/or differential strip cooling,” where roll torque corresponds to a roll force and rolling speed corresponds to a mill speed;
[0029]: “To ensure that the flatness targets are met, a flatness roll 130, or any other flatness measurement sensing device, such as the use of one or more of the metal strip property and position sensors 132, 134, 138 measuring the position and angles of the metal strip 136 in the rolling and lateral directions, may be added after the last rolling stand 108 or any of the other rolling stands 102, 104, 106 so that flatness errors may be fed back to the control system to adjust work roll 112, 116 heating, cooling, bending, roll tilting, and/or any other control mechanisms available to the rolling mill 100 that may influence the roll gap geometry of the rolling stands 102, 104, 106, 108”;
[0051]: “ the control system may read in measured or sensed values for the… work roll camber at block 606, … strip angles in the rolling direction into the stand at block 624, strip angles in the rolling direction out of the stand at block 626, strip angles in the lateral direction into the stand at block 628, strip angles in the lateral direction out of the stand at block 630, strip total tension into the stand at block 632, strip total tension out of the stand at block 634, strip differential tension into the stand at block 636 and/or strip differential tension out of the stand at block 638. These measured or sensed values 602-638 may then be sent to a fast loop controller 668,” where tension into the stand corresponds to entry tension;
[0047]: “The thermal camber controller 542 may then adjust one or more of the rolling mill control mechanisms, such as, but not limited to, upper and lower sprays 520, 522, for its rolling stand 502, 504, 506, 508. These changes may be directed at achieving a specified roll gap geometry, specific properties or parameters of the metal strip 536, or both,” where the control adjusting mechanisms such as the sprays corresponds to the model comprising spray parameters).
Regarding claim 5, Jelali teaches a method of programming a controller for automatically controlling thickness and flatness of sheet metal produced by a roll stand, the method comprising:
receiving an input comprising a first measurement of the thickness and the flatness of the sheet metal exiting the roll stand (Page 7, Lines 12-13: “the flatness deviation is determined using a flatness measuring system at the exit of the stand”; Page 3, Lines 8-15: “the control method according to the invention generates input variables for the controller depending on the measured values of the measuring systems. These input variables are used by the controller to generate at least one control signal for at least one control variable of the rolling stand based on an integrated, model-predictive thickness, tension and flatness control. Preferably, separate measuring systems are provided for the thickness, flatness and tension of the strip. However, within the scope of this invention, measuring systems can also be used that determine several variables, such as thickness and flatness, simultaneously”);
generating a predictive model of the roll stand, (Page 3, Lines 20-22: “The controller uses a prediction model to predict the future system behavior. The controller is preferably an MPC (Model Predictive Control) controller embedded in an IMC (Internal Model Control) structure” to model the roll stand; Page 4, Lines 35-36: “The controller preferably uses an explicit, linear or non-linear online-capable profile and flatness model that takes into account the essential variables and actuators involved in the rolling process”; Page 6, Lines 34-36: “The coupling between thickness, tension and flatness is taken into account by a decoupling matrix, which can be calculated from the inverse of the total transfer matrix of the thickness and flatness control system”);
calculating a second measurement of the thickness and the flatness of the sheet metal based on the current state (Page 7, Lines 24-26: “The multivariable controller consists of an online-capable model and a dynamic optimization taking into account manipulated variable constraints and predicted controlled variable characteristics,” where an online model calculates a second measurement);
predicting a future measurement of the thickness and the flatness of the sheet metal using the predictive model and a difference between the first measurement and the second measurement of the thickness and the flatness of the sheet metal (Page 2, Lines 18-23: “The invention is based on the basic idea of controlling thickness, tension and flatness with a single controller within the framework of an integrated, model-predictive thickness, tension and flatness control. The integrated control system takes into account the influence that the adjustment of control variables has on the thickness, the tension as well as the flatness of the rolled strip and can optimize the change of the control variables in such a way that a selected quality of the thickness control and the flatness control is achieved,” which means that thickness and flatness are controlled variables; Page 4, Line 26: “the prediction of the controlled variable is included in the dynamic optimization”; Page 7, Lines 15-23: “The flatness profile (flatness distribution) is estimated directly based on the individual measurement results. The estimated flatness curve is decomposed into orthogonal (independent) components… The orthogonal components thus determined are compared with values provided by an online model of the system. The resulting difference is used as a controlled variable and fed to the multi-variable controller 3”);
dynamically generating a signal for adjusting one or more actuators for controlling one or more of: (Page 2, Lines 18-20: “The invention is based on the basic idea of controlling thickness, tension and flatness with a single controller within the framework of an integrated, model-predictive thickness, tension and flatness control”; Page 7, Lines 27-29: “From the input variable, the controller determines control signals for roll bending, roll swiveling, axial displacement of the rolls as well as for multi-zone cooling and, if necessary, a change in the support roll shape”).
Fairlie teaches dynamically generating a signal for adjusting one or more actuators for controlling one or more of: a roll force, a mill speed and/or ([0055]: “The fast loop controller 668 may adjust one or more rolling mill control mechanisms to influence the roll gap geometry. For example, the rolling mill may include rolling mill control mechanisms such as, but not limited to, work roll heating 684, work roll cooling 686, work roll bending 688, CVC roll positioning 690, deformable backup roll pressure 692, roll tilting 694, roll crossing and/or pair crossing 696, differential strip cooling 697, work roll position 698, differential rolling load 700, rolling speed 702, speed difference between rolling stands 704, roll torque 706 and/or rolling load 708,” where roll torque corresponds to a roll force and rolling speed corresponds to a mill speed).
The reasons to combine Fairlie into Jelali are the same as articulated in claim 1 above.
While Jelali teaches online controller adaptation (Page 8, Lines 4-8: “In order to compensate for changes in the dynamic behavior, which can be caused, for example, by wear, the replacement of components of the rolling stand and changes in the material properties of the rolling stand, the models are adapted online during the rolling of a single strip”), Jelali and Fairlie do not explicitly teach “wherein the predictive model is derived from a bump test.”
Cuznar further teaches wherein the predictive model is derived from a bump test (Page 2, Section III: “In order to develop a suitable feature extraction algorithm, we must first define the purpose of the models. The objectives pursued are to advise optimal recipe parameters: 1) before initial rolling, 2) before next rolling pass, 3) in real-time during the rolling. From an identification point of view, each of the objectives differs in the amount of information available at a given time that can be used to predict the quality indicator… The cold rolling process is usually operating in a steady-state. Therefore, the analysis focuses on the sections where steady-state operation is present”).
The reasons to combine Cuznar into Jelali in view of Fairlie are the same as articulated in claim 1 above.
Regarding claim 7, Jelali teaches the method of claim 5.
While Jelali teaches the model comprising tension, tilt control, and bending control (Page 3, Lines 2-4: “The rolling forces also depend on the strip tension. This results in a strong coupling between tension, thickness and flatness control. According to the invention, these are taken into account by the model used by the controller in one controller”; Page 3, Lines 17-19: “The control variables of the rolling process are understood to include, in particular, roll bending, roll pivoting, roll shifting, roll cooling, in particular selective multi-zone cooling, and also the change of the support roll shape”), Jelali does not explicitly teach “wherein the predictive model is further based on one or more of: roll gap, roll force, entry tension, mill speed, spray parameters, tilt control, and bending control.”
Fairlie further teaches wherein the predictive model is further based on one or more of: roll gap, roll force, entry tension, mill speed, spray parameters, tilt control, and bending control ([0018]: “setup or production parameters may include, but are not limited to, thickness reduction, work roll position, differential rolling load, rolling speed, speed differences between individual stands of the rolling mill, roll torque, and/or differential strip cooling,” where roll torque corresponds to a roll force and rolling speed corresponds to a mill speed;
[0029]: “To ensure that the flatness targets are met, a flatness roll 130, or any other flatness measurement sensing device, such as the use of one or more of the metal strip property and position sensors 132, 134, 138 measuring the position and angles of the metal strip 136 in the rolling and lateral directions, may be added after the last rolling stand 108 or any of the other rolling stands 102, 104, 106 so that flatness errors may be fed back to the control system to adjust work roll 112, 116 heating, cooling, bending, roll tilting, and/or any other control mechanisms available to the rolling mill 100 that may influence the roll gap geometry of the rolling stands 102, 104, 106, 108”;
[0051]: “ the control system may read in measured or sensed values for the… work roll camber at block 606, … strip angles in the rolling direction into the stand at block 624, strip angles in the rolling direction out of the stand at block 626, strip angles in the lateral direction into the stand at block 628, strip angles in the lateral direction out of the stand at block 630, strip total tension into the stand at block 632, strip total tension out of the stand at block 634, strip differential tension into the stand at block 636 and/or strip differential tension out of the stand at block 638. These measured or sensed values 602-638 may then be sent to a fast loop controller 668,” where tension into the stand corresponds to entry tension;
[0047]: “The thermal camber controller 542 may then adjust one or more of the rolling mill control mechanisms, such as, but not limited to, upper and lower sprays 520, 522, for its rolling stand 502, 504, 506, 508. These changes may be directed at achieving a specified roll gap geometry, specific properties or parameters of the metal strip 536, or both,” where the control adjusting mechanisms such as the sprays corresponds to the model comprising spray parameters).
Regarding claim 9, Jelali teaches a controller for controlling thickness and flatness of sheet metal exiting a roll stand having a first work roll and a second work roll comprising:
means of determining the thickness of the sheet metal exiting the roll stand (Page 3, Lines 12-13: “Preferably, separate measuring systems are provided for the thickness, flatness and tension of the strip”);
a flatness sensor for determining the flatness of the sheet metal exiting the roll stand (Page 6, Lines 21-24: “Sensors are arranged on the flatness measuring roller distributed over the radius and width. These provide information about the flatness of the strip at the respective location at the respective time of measurement, offset in time from one another and with regard to the width position”);
receive an input comprising a first measurement of the thickness and the flatness of the sheet metal exiting the roll stand (Page 7, Lines 12-13: “the flatness deviation is determined using a flatness measuring system at the exit of the stand”; Page 3, Lines 8-15: “the control method according to the invention generates input variables for the controller depending on the measured values of the measuring systems. These input variables are used by the controller to generate at least one control signal for at least one control variable of the rolling stand based on an integrated, model-predictive thickness, tension and flatness control. Preferably, separate measuring systems are provided for the thickness, flatness and tension of the strip. However, within the scope of this invention, measuring systems can also be used that determine several variables, such as thickness and flatness, simultaneously”);
generate a predictive model of the roll stand, (Page 3, Lines 20-22: “The controller uses a prediction model to predict the future system behavior. The controller is preferably an MPC (Model Predictive Control) controller embedded in an IMC (Internal Model Control) structure” to model the roll stand; Page 4, Lines 35-36: “The controller preferably uses an explicit, linear or non-linear online-capable profile and flatness model that takes into account the essential variables and actuators involved in the rolling process”; Page 6, Lines 34-36: “The coupling between thickness, tension and flatness is taken into account by a decoupling matrix, which can be calculated from the inverse of the total transfer matrix of the thickness and flatness control system”);
calculate a second measurement of the thickness and the flatness of the sheet metal based on the current state (Page 7, Lines 24-26: “The multivariable controller consists of an online-capable model and a dynamic optimization taking into account manipulated variable constraints and predicted controlled variable characteristics,” where an online model calculates a second measurement);
predict a future measurement of the thickness and the flatness of the sheet metal using the predictive model and a difference between the first measurement and the second measurement of the thickness and the flatness of the sheet metal (Page 2, Lines 18-23: “The invention is based on the basic idea of controlling thickness, tension and flatness with a single controller within the framework of an integrated, model-predictive thickness, tension and flatness control. The integrated control system takes into account the influence that the adjustment of control variables has on the thickness, the tension as well as the flatness of the rolled strip and can optimize the change of the control variables in such a way that a selected quality of the thickness control and the flatness control is achieved,” which means that thickness and flatness are controlled variables; Page 4, Line 26: “the prediction of the controlled variable is included in the dynamic optimization”; Page 7, Lines 15-23: “The flatness profile (flatness distribution) is estimated directly based on the individual measurement results. The estimated flatness curve is decomposed into orthogonal (independent) components… The orthogonal components thus determined are compared with values provided by an online model of the system. The resulting difference is used as a controlled variable and fed to the multi-variable controller 3”);
dynamically generate a signal for adjusting one or more actuators for controlling one or more of: (Page 2, Lines 18-20: “The invention is based on the basic idea of controlling thickness, tension and flatness with a single controller within the framework of an integrated, model-predictive thickness, tension and flatness control”; Page 7, Lines 27-29: “From the input variable, the controller determines control signals for roll bending, roll swiveling, axial displacement of the rolls as well as for multi-zone cooling and, if necessary, a change in the support roll shape”).
Fairlie teaches dynamically generate a signal for adjusting one or more actuators for controlling one or more of: a roll force, a mill speed and/or ([0055]: “The fast loop controller 668 may adjust one or more rolling mill control mechanisms to influence the roll gap geometry. For example, the rolling mill may include rolling mill control mechanisms such as, but not limited to, work roll heating 684, work roll cooling 686, work roll bending 688, CVC roll positioning 690, deformable backup roll pressure 692, roll tilting 694, roll crossing and/or pair crossing 696, differential strip cooling 697, work roll position 698, differential rolling load 700, rolling speed 702, speed difference between rolling stands 704, roll torque 706 and/or rolling load 708,” where roll torque corresponds to a roll force and rolling speed corresponds to a mill speed).
The reasons to combine Fairlie into Jelali are the same as articulated in claim 1 above.
While Jelali teaches online controller adaptation (Page 8, Lines 4-8: “In order to compensate for changes in the dynamic behavior, which can be caused, for example, by wear, the replacement of components of the rolling stand and changes in the material properties of the rolling stand, the models are adapted online during the rolling of a single strip”), Jelali and Fairlie do not explicitly teach “a memory storing executable code, for implementing a model--based multi-variable predictive control, and one or more processors” and “wherein the predictive model is derived from a bump test.”
Cuznar further teaches a processor; (Page 5, Section V: “two main graphical user interfaces (GUIs) were developed: Optimizer and Simulator, which contain identified models and optimization/simulation algorithms. Since the GUI is intended to be accessible to multiple users simultaneously through a web browser, the ‘Flask’ platform is used to enable web page creation”) and
wherein the predictive model is derived from a bump test (Page 2, Section III: “In order to develop a suitable feature extraction algorithm, we must first define the purpose of the models. The objectives pursued are to advise optimal recipe parameters: 1) before initial rolling, 2) before next rolling pass, 3) in real-time during the rolling. From an identification point of view, each of the objectives differs in the amount of information available at a given time that can be used to predict the quality indicator… The cold rolling process is usually operating in a steady-state. Therefore, the analysis focuses on the sections where steady-state operation is present”).
The reasons to combine Cuznar into Jelali in view of Fairlie are the same as articulated in claim 1 above.
Regarding claim 16, Jelali in view of Fairlie and Cuznar teaches the controller of claim 9.
While Jelali teaches online controller adaptation (Page 8, Lines 4-8: “In order to compensate for changes in the dynamic behavior, which can be caused, for example, by wear, the replacement of components of the rolling stand and changes in the material properties of the rolling stand, the models are adapted online during the rolling of a single strip”), Jelali and Fairlie do not explicitly teach “wherein the input comprises bump test data collected over a length of time.”
Cuznar further teaches wherein the input comprises bump test data collected over a length of time (Page 2, Section III: “In order to develop a suitable feature extraction algorithm, we must first define the purpose of the models. The objectives pursued are to advise optimal recipe parameters: 1) before initial rolling, 2) before next rolling pass, 3) in real-time during the rolling. From an identification point of view, each of the objectives differs in the amount of information available at a given time that can be used to predict the quality indicator… The data extracted from the database is sampled with a time interval of 0.01 s… The cold rolling process is usually operating in a steady-state. Therefore, the analysis focuses on the sections where steady-state operation is present”).
Claims 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Jelali et al. (WO 2005/072886 A1), in view of Fairlie et al. (US 2017/0259313 A1), Cuznar, and De Mol et al. (US 4,700,557 A).
Regarding claim 12, Jelali in view of Fairlie and Cuznar teaches the controller of claim 9.
While Jelali teaches multi-zone cooling and determination of a change in shape (Page 7, Lines 27-30: “From the input variable, the controller determines control signals for roll bending, roll swiveling, axial displacement of the rolls as well as for multi-zone cooling and, if necessary, a change in the support roll shape”), Jelali, Fairlie, and Cuznar do not explicitly teach “wherein the controller is configured to control a plurality of spray nozzles in different rotors/zones in a shapemeter to provide zone selective cooling along length of the first work roll and the second work roll.”
De Mol further teaches wherein the controller is configured to control a plurality of spray nozzles in different rotors/zones in a shapemeter to provide zone selective cooling along length of the first work roll and the second work roll (Abstract: “The process includes measuring the shape of the strip, spraying cooling fluid on the rolls, and controlling the spraying of cooling fluid according to a duty cycle”; FIG. 1 and Col. 2, Lines 16-42: “A shapemeter 22 is mounted to contact the strip 20 after the strip leaves the work rolls 12… The control unit 24 includes a computer to receive the signals and perform computations thereupon. Two spray bars 26 are located adjacent the two work rolls 12. Each shape bar 26 extends the length of the adjacent work roll 12 and includes a plurality of spray nozzles, as illustrated in FIG. 2… The spray bars 26 include valves, not shown, coupled one to each nozzle 30 and 32 and controllable by signals from the control unit 24.”; Col. 2, Lines 51-56: “For each zone across the width of the strip the shape is measured by the shapemeter 22. When it is desired to increase or decrease the spacing between the rolls 12 in a particular zone the corresponding spray nozzles are opened or closed as necessary”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the controller of Jelali in view of Fairlie and Cuznar to incorporate the teachings of De Mol so as to include the controller being coupled to spray nozzles in different rotors/zones in a shapemeter. Doing so would allow for sprayed fluid to be provided with the aim of minimizing variations from the target diameter (De Mol, Col. 3, Lines 4-28: “We have found some special advantages in controlling the sprays according to duty cycles. By means of duty cycling, it is possible to provide any desired quantity of sprayed fluid over a continuous range. That is, one is not restricted to providing e.g. only 33% or 66% of total flow… our use of a duty cycle time of about 10 seconds insures that the roll responds only slightly, to turning the sprays on and off, and the diameter remains very near the target diameter with only slight, if any, variations through time”).
Regarding claim 13, Jelali, Fairlie, Cuznar, and De Mol teaches the controller of claim 12.
Jelali, Fairlie, Cuznar do not explicitly teach “further configured to control a variable duty cycle of each of the plurality of spray nozzles.”
De Mol further teaches further configured to control a variable duty cycle of each of the plurality of spray nozzles (Col. 2, Lines 56-67: “The sprays are operated in cycles with each cycle being initiated a predetermined time after the initiation of the immediately preceding cycle. During each cycle a spray is on for a controllable period of time and off for the remainder of the cycle. This is called duty cycling. For example, if the cycle time is about ten seconds, which is a cycle time we have found preferable in many circumstances, and it is desired to apply 10% cooling to a zone, then the small nozzle 30 is opened 3.3 seconds (i.e. one-third of the duty cycle) and thereafter closed 6.7 seconds and then opened 3.3 seconds and so forth”).
Claims 15 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Jelali et al. (WO 2005/072886 A1), in view of Fairlie et al. (US 2017/0259313 A1), Cuznar, and Li et al. (CN 111482465 A).
Regarding claim 15, Jelali in view of Fairlie and Cuznar teaches the controller of claim 9.
Jelali, Fairlie, and Cuznar do not explicitly teach “comprising a desired or target shape entered in terms of linear and quadratic components.”
Li further teaches wherein a desired or target shape of the sheet metal is entered in terms of linear and quadratic components ([0037-0038]: “Determining the tilt control correction amount according to the linear component of the first-order term of the preset mathematical model; Determining the positive and negative curvature correction amounts according to the linear component of the quadratic term of the preset mathematical model,” where the preset mathematical model corresponds to a target shape of the sheet metal).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the controller of Jelali in view of Fairlie and Cuznar to incorporate the teachings of Li so as to include a desired or target shape of the sheet metal entered in terms of linear and quadratic components. Doing so would allow control parameters to be adjusted online with the aim of improving control efficiency (Li, [0006]: “In the existing technology, the control of plate shape is generally carried out through plate shape control devices such as bending rollers. It is impossible to detect the plate shape improvement of the plate and strip after adjustment online, and the plate shape improvement can only be checked by visual inspection. This control method is highly dependent on the operator's experience level and working status, which limits the further improvement of control efficiency”).
Regarding claim 17, Jelali in view of Fairlie, Cuznar, and Li teaches the controller of claim 15.
While Jelali teaches tilt, bend, and cooling control components (Page 7, Lines 27-30: “From the input variable, the controller determines control signals for roll bending, roll swiveling, axial displacement of the rolls as well as for multi-zone cooling and, if necessary, a change in the support roll shape”), Jelali, Fairlie, and Cuznar do not explicitly teach “a linear component control addressed through tilt control, a quadratic component control addressed through bend control, and a residual effort regulated through nozzle control.”
Li further teaches wherein control of the linear component is addressed through tilt control ([0037]: “Determining the tilt control correction amount according to the linear component of the first-order term of the preset mathematical model”), the quadratic component addressed through bend control ([0038]: “Determining the positive and negative curvature correction amounts according to the linear component of the quadratic term of the preset mathematical model), and a residual effort regulated through nozzle control ([0040]: “The spray correction amount is determined according to the residual component of the preset mathematical model.”).
Response to Arguments
Applicant’s amended claims, filed 12/01/2025, have overcome the rejections under 35 U.S.C. § 101 and 35 U.S.C. § 102.
Applicant's arguments regarding the rejections under 35 U.S.C. § 103 have been fully considered but they are not persuasive. Regarding claims 1, 5, and 9, applicant argues that Jelali and Fairlie do not teach or suggest predicting a future measurement of the thickness and flatness of the sheet metal. Examiner respectfully disagrees. Jelali teaches that thickness and flatness are controlled variables and a predictive model of the controlled variables is generated, as described in the rejection above. Specifically, see Jelali page 2, lines 18-23, page 4, line 26, and page 7, lines 15-23.
Accordingly, applicant’s arguments are not persuasive since the cited prior art describe the limitations in these claims. For at least these reasons, the rejection is still deemed proper and has been maintained.
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 Magdalena Kossek whose telephone number is (571)272-5603. The examiner can normally be reached Mon-Fri 9:00-5:00 EST.
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, Robert Fennema can be reached on (571)272-2748. 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.
/M.I.K./Examiner, Art Unit 2117
/ROBERT E FENNEMA/Supervisory Patent Examiner, Art Unit 2117