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 .
Specification
The substitute Specification of 11/28/2023 is hereby accepted and entered.
Claim Objections
Claim 10 is objected to because of the following informalities:
Claim 10 – Please change the phrase “a base estimator configured to utilized” to “a base estimator configured to utilize.”
Appropriate correction is required.
Claim Interpretation
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 limitation(s) is/are:
The base estimator, machine estimator, and calculation unit in claims 10-14 and 16-19. One having ordinary skill in the art would have understood corresponding structure to be disclosed in the form of at least computer programming to perform the recited functionality.
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 § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the abstract idea of a mathematical algorithm for determining the health of a machine (Claim 9 recites specific equations for use).
This judicial exception is not integrated into a practical application because the recited machine is generic and no improvement to the performance of the underlying machine is realized through the implementation of the algorithm.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recited computer elements and the recited display of the algorithm results amount to the recitation of a general-purpose computer for the implementation of the abstract idea and do not serve to amount to significantly more than the recitation of the abstract idea itself (See Alice Corp. v. CLS Bank International, 573 U.S. 208 (2014)). The ascertaining of insurance rates (i.e., per instant Claim 8) amounts to the recitation of a furtherance of the abstract idea in the form of another abstract idea (Organizing human activity, see MPEP 2106.04(a)(2) – “fundamental economic principles or practices (including hedging, insurance, mitigating risk)”); A combination of abstract ideas is an abstract idea [See 2106.05(I) – "Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"].
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 9 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 9 recites the functions h(t)=1-d-exp(atb) and (hi) = A*K1 + B*K2 + C*K3 +D* Σ f(t), subcomponents. None of the parameters for these functions are defined, nor does the instant Specification define the parameters. The function f(t) is not defined, nor does the instant Specification define the function f(t). This leaves the scope of the claims unclear. Further, the word “subcomponents” recited at the end of the claim has an unclear impact on the rest of the claim and leaves the scope of the claim unclear.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 7, 10, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”] and Nair et al. (US 20220214680 A1)[hereinafter “Nair”].
Regarding Claim 1, Jarrell discloses a method for ascertaining a health characteristic variable of a machine [Title – “Methods And Systems For Analyzing The Degradation And Failure Of Mechanical Systems”] at a current time of consideration and for future times of consideration, the health characteristic variable representing a state of the machine at the current time of consideration in dependence on an operating time for which purpose a base function is used [See Figs. 2 and 3 and Paragraph [0011], the tracking of performance parameter 30 and predictive analysis to project residual machine life.Paragraph [0011] – “FIG. 2 (a prior art illustration) shows a performance parameter 30 that starts to decline from its normal operating band (NOB), reaches an alert level, and is subsequently analyzed to try and understand a reasonable projection for residual life. Failure is defined as the point 32 at which the equipment no longer is capable of supporting the function for which it was designed.”Application of the technique relative to the machine profiles depicted by Figs. 2 and 3 for another machine being relative to a “reference machine.”].
Jarrell fails to disclose that the base function maps a first time profile of a base characteristic variable over the operating time, the first time profile of the base characteristic variable representing a state of a reference machine at the time of consideration in dependence on the operating time and which is ascertained from one of (i) historical observations of a group consisting of a plurality of machines of the same type or (ii) knowledge-based expectations based on at least three consecutive data points, and the base characteristic variable representing a state of the reference machine at the time of consideration in dependence on an operating time.
However, Nair discloses the use of a base function that maps a first time profile of a base characteristic variable over the operating time, the first time profile of the base characteristic variable representing a state of a reference machine at the time of consideration in dependence on the operating time and which is ascertained from one of (i) historical observations of a group consisting of a plurality of machines of the same type or (ii) knowledge-based expectations based on at least three consecutive data points, and the base characteristic variable representing a state of the reference machine at the time of consideration in dependence on an operating time [See Baseline 602 of Fig. 6 to model expected failure rate/time.The baseline lifetime is determined from historical observations and/or knowledge-based expectations (Paragraph [0066] – “The baseline lifetime model, in some embodiments, is a lifetime model provided by a manufacturer of the component or is derived from information from the manufacturer.”) inherently based on at least three consecutive data points to produce curve 602.].
It would have been obvious to use such a base function to produce the first time profile and to display it alongside the expected failure charts of Jarrell because doing so would have been useful to a user in determining the expected behavior for the machine.
Jarrell, as modified, would further disclose calculating an actual characteristic variable which varies over the operating time via an individual function [See Fig. 5 and Paragraph [0054] – “At process block 56, the physical degradation rate of the machinery is represented as a function of the intensity of the stressor. In other words, a function Fn that correlates the degradation rate to the stressor intensity is determined.”Physical degradation rate reading on the “actual characteristic variable.”], an input variable fed to the individual function being a performance characteristic variable of the machine [See Fig. 3 and Paragraph [0039] – “As shown in FIG. 3, by accurately measuring and trending the stressor 38, the cone of uncertainty between the maximum slope 34 and the minimum slope 36 that defines the expected performance of the machinery can be narrowed substantially in comparison to the cone of uncertainty shown in FIG. 2.”Stressor 38 reading on the “input variable.”], which is one of detected periodically via a machine data detection unit or predicted for future operating times [See Fig. 5 and Paragraph [0052] – “At process block 52, the intensity of the stressor is measured. The stressor may be measured in any suitable manner, such as by using a measurement system specifically designed to detect and measure the stressor.”Paragraph [0053] – “At process block 54, the intensity of the stressor is represented as a function of time. In other words, the measurements obtained at process block 52 are analyzed to correlate the intensity of the stressor with time. This representation may be based on the measurements taken at process block 52 and may be substantially continuously updated so that changes made to the stressor intensity are quickly taken into account.”]; and
displaying the health characteristic variable as a second time profile by adding the ascertained actual characteristic variable or the predicted actual characteristic variable [See Figs. 2 and 3 and Paragraph [0011], the tracking of performance parameter 30 and predictive analysis to project residual machine life.] to the first time profile [As displayed per Nair].
Regarding Claim 7, Jarrell, as modified, would disclose that in a screen view for a health estimation of the machine, in addition to the first time profile [See Figs. 2 and 3 and Paragraph [0011], the tracking of performance parameter 30 and predictive analysis to project residual machine life] and the second time profile [As displayed per Nair], a third time profile and a fourth time profile are displayed [Fig. 2 and 3, the upper and lower bounds of the “Cone of Uncertainty.”];
wherein the third time profile is a lower limit for a permissible range of the health characteristic variable [See Figs. 2 and 3, “minimum slope 36”] and the fourth time profile is an upper limit for a permissible range of the health characteristic variable [See Figs. 2 and 3, “maximum slope 34”];
wherein a 3-stage evaluation is performed for the health estimation of the machine [See Figs. 2 and 3, NOB, ALERT, and ALARM].
Jarrell fails to disclose that, in an event of the health characteristic variable having a value above the first time profile, a first state (gn) is assigned to a state value; and
that, in the event of the health characteristic variable having a value below the first time profile but still above the third time profile, a second state is assigned to the state value and, in the event of the health characteristic variable having a value below the third time profile, a third state is assigned to the state value.
However, Nair discloses the use of the recited first time profile [See Baseline 602 of Fig. 6 to model expected failure rate/time.]. It would have been obvious to recognize health characteristic data that is better than (i.e., above) baseline reference health characteristic data as indicating that the machine is in a better-than-expected state.
Jarrell discloses the third time profile [See Figs. 2 and 3, “minimum slope 36” of the “Cone of Uncertainty”]. The Cone of Uncertainty would naturally surround the baseline profile, in view of Figs. 2 and 3 of Jarrell where the Cone of Uncertainty surrounds the actual health characteristic measurement curve for the machine. It would have been obvious to recognize that health characteristic data that is near to but better than (i.e., above) minimum slope 36, but below the profile established per Nair, as indicating that the machine is in a somewhat degraded state because minimum slope 36 sets a lower bound for predicted lifetime while the profile of Nair establishes a typical expected degradation rate. It would have been obvious to recognize that health characteristic data that is worse than (i.e., lower) minimum slope 36 as indicating that the machine is in a highly degraded state because this would amount to the situation where the machine is degrading even faster than minimum slope 36 would suggest would be fastest predicted degradation.
Regarding Claim 10, Jarrell discloses a computer system [Paragraph [0050] – “The method may be implemented using a suitable measurement system connected to a computer-based analysis system.”] which ascertains a health characteristic variable of a machine [Title – “Methods And Systems For Analyzing The Degradation And Failure Of Mechanical Systems”] at a current time of consideration and for future times of consideration, the health characteristic variable representing a state of the machine at the time of consideration in dependence on an operating time [See Figs. 2 and 3 and Paragraph [0011], the tracking of performance parameter 30 and predictive analysis to project residual machine life.Paragraph [0011] – “FIG. 2 (a prior art illustration) shows a performance parameter 30 that starts to decline from its normal operating band (NOB), reaches an alert level, and is subsequently analyzed to try and understand a reasonable projection for residual life. Failure is defined as the point 32 at which the equipment no longer is capable of supporting the function for which it was designed.”Application of the technique relative to the machine profiles depicted by Figs. 2 and 3 for another machine being relative to a “reference machine.”], the computer system comprising:
a health model [See Figs. 2 and 3] comprising:
a base estimator [Inherent computer programming].
Jarrell fails to disclose that the base estimator is configured to utilized a base function to map a first time profile of a base characteristic variable over the operating time on a screen view, the first time profile of the base characteristic variable representing a state of a reference machine at the time of consideration in dependence on the operating time and being ascertained one of from (i) a database with historical observations of a group consisting of a plurality of machines of the same type or (ii) a knowledge database with knowledge-based expectations based on at least three consecutive data points, the base characteristic variable representing a state of the reference machine at the time of consideration in dependence on an operating time.
However, Nair discloses the use of a base function to map a first time profile of a base characteristic variable over the operating time on a screen view, the first time profile of the base characteristic variable representing a state of a reference machine at the time of consideration in dependence on the operating time and being ascertained one of from (i) a database with historical observations of a group consisting of a plurality of machines of the same type or (ii) a knowledge database with knowledge-based expectations based on at least three consecutive data points, the base characteristic variable representing a state of the reference machine at the time of consideration in dependence on an operating time [See Baseline 602 of Fig. 6 to model expected failure rate/time.The baseline lifetime is determined from historical observations and/or knowledge-based expectations (Paragraph [0066] – “The baseline lifetime model, in some embodiments, is a lifetime model provided by a manufacturer of the component or is derived from information from the manufacturer.”) inherently based on at least three consecutive data points to produce curve 602.].
It would have been obvious to use such a base function to produce the first time profile and to display it alongside the expected failure charts of Jarrell because doing so would have been useful to a user in determining the expected behavior for the machine.
Jarrell, as modified, would further disclose a machine estimator [Inherent computer programming], which is configured to calculate an actual characteristic variable which varies over the operating time via an individual function [See Fig. 5 and Paragraph [0054] – “At process block 56, the physical degradation rate of the machinery is represented as a function of the intensity of the stressor. In other words, a function Fn that correlates the degradation rate to the stressor intensity is determined.”Physical degradation rate reading on the “actual characteristic variable.”], an input variable fed to the individual function being a performance characteristic variable of the machine [See Fig. 3 and Paragraph [0039] – “As shown in FIG. 3, by accurately measuring and trending the stressor 38, the cone of uncertainty between the maximum slope 34 and the minimum slope 36 that defines the expected performance of the machinery can be narrowed substantially in comparison to the cone of uncertainty shown in FIG. 2.”Stressor 38 reading on the “input variable.”], which is periodically detected via a machine data detection unit and which is retrievable in a memory for performance characteristic variable data or is predictable for future operating times via a predictor [See Fig. 5 and Paragraph [0052] – “At process block 52, the intensity of the stressor is measured. The stressor may be measured in any suitable manner, such as by using a measurement system specifically designed to detect and measure the stressor.”Paragraph [0053] – “At process block 54, the intensity of the stressor is represented as a function of time. In other words, the measurements obtained at process block 52 are analyzed to correlate the intensity of the stressor with time. This representation may be based on the measurements taken at process block 52 and may be substantially continuously updated so that changes made to the stressor intensity are quickly taken into account.”]; and
a calculation unit [Inherent computer programming] configured to provide a second time profile as a health characteristic variable by adding the ascertained actual characteristic variable (hi) or the predicted actual characteristic variable (hi) [See Figs. 2 and 3 and Paragraph [0011], the tracking of performance parameter 30 and predictive analysis to project residual machine life.] to the first time profile [As displayed per Nair].
Regarding Claim 18, Jarrell, as modified, would disclose that the computer system is configured, in addition to the first time profile [See Figs. 2 and 3 and Paragraph [0011], the tracking of performance parameter 30 and predictive analysis to project residual machine life] and the second time profile [As displayed per Nair], to display a third time profile and a fourth time profile in the screen view for the health estimation of the machine [Fig. 2 and 3, the upper and lower bounds of the “Cone of Uncertainty.”];
wherein the third time profile is formed as a lower limit for a permissible range of the health characteristic variable [See Figs. 2 and 3, “minimum slope 36”] and the fourth time profile is formed as an upper limit for a permissible range of the health characteristic variable [See Figs. 2 and 3, “maximum slope 34”];
wherein an estimator configured to perform a 3-stage evaluation is provided for the health estimation of the machine [See Figs. 2 and 3, NOB, ALERT, and ALARM].
Jarrell fails to disclose that, in an event of the health characteristic variable having a value above the first time profile, a first state is assigned to a state value; and
wherein in an event of the health characteristic variable having a value below the first time profile but still above the third time profile, a second state is assigned to the state value; and wherein in an event of the health characteristic variable having a value below the third time profile, a third state is assigned to the state value.
However, Nair discloses the use of the recited first time profile [See Baseline 602 of Fig. 6 to model expected failure rate/time.]. It would have been obvious to recognize health characteristic data that is better than (i.e., above) baseline reference health characteristic data as indicating that the machine is in a better-than-expected state.
Jarrell discloses the third time profile [See Figs. 2 and 3, “minimum slope 36” of the “Cone of Uncertainty”]. The Cone of Uncertainty would naturally surround the baseline profile, in view of Figs. 2 and 3 of Jarrell where the Cone of Uncertainty surrounds the actual health characteristic measurement curve for the machine. It would have been obvious to recognize that health characteristic data that is near to but better than (i.e., above) minimum slope 36, but below the profile established per Nair, as indicating that the machine is in a somewhat degraded state because minimum slope 36 sets a lower bound for predicted lifetime while the profile of Nair establishes a typical expected degradation rate. It would have been obvious to recognize that health characteristic data that is worse than (i.e., lower) minimum slope 36 as indicating that the machine is in a highly degraded state because this would amount to the situation where the machine is degrading even faster than minimum slope 36 would suggest would be fastest predicted degradation.
Claim(s) 2 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”], Nair et al. (US 20220214680 A1)[hereinafter “Nair”], and Franklin et al. (US 20080126040 A1)[hereinafter “Franklin”].
Regarding Claims 2 and 11, Jarrell fails to disclose that, for the historical observations for the base characteristic variable, a quantity of manufactured units per time unit of the reference machine is defined as an observation parameter;
wherein, for the periodically detected performance characteristic variable, a quantity of manufactured units per time unit of the machine is also selected; and
wherein a deviation between the quantity of the reference machine and the quantity of the machine is provided as a factor and is utilized in the individual function as a correction factor for the calculation of the actual characteristic variable, such that a result of the health characteristic variable is optimized and the second time profile is influenced such that it is more informative.
However, Franklin discloses tracking machine lifetime assessment based on a quantity of manufactured units per time unit [See Fig. 6, x-axis is “cuts.”Paragraph [0028] – “The term "cuts" is intended to refer to measures of production regardless of whether production is measured in weight, length or time. In a specific example such as a MIMO or SIMO manufacturing system, the number of cuts correlates directly to the number of products produced. For a MISO manufacturing system, cuts may refer to a measure of production such as amount of material produced in a given measure such as time.”]. It would have been obvious to track machine lifetime assessment based on a quantity of manufactured units per time unit because an increase production rate would amount to a stressor that impacts machine lifetime.
Franklin uses a change in the production amount to adjust the lifetime assessment for the machine [See the equation for NEW HDONE in Fig. 6]. It would have been obvious to use the difference in production caused by a change in production rate from a reference production rate [per the use of a reference curve as taught by Nair] because doing so would have been useful in determining changes to the lifetime of the machine.
Claim(s) 4 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”], Nair et al. (US 20220214680 A1)[hereinafter “Nair”], Franklin et al. (US 20080126040 A1)[hereinafter “Franklin”], and Horstemeyer et al. (US 20160247128 A1)[hereinafter “Horstemeyer”].
Regarding Claim 4, Jarrell fails to disclose that a further input variable fed to the individual function comprises an installation site of the machine with which environmental factors describing the environmental influences on the machine at the installation site of the machine are ascertained; and
wherein, in the individual function, at least one environmental factor is utilized as at least one further correction factor for the calculation of the actual characteristic variable which influences the health characteristic variable and thus the second time profile.
However, Horstemeyer discloses the use of machine location and environment in assessing the longevity of a machine [See Paragraphs [0080]-[0081]]. It would have been obvious to use machine location and environment in assessing the longevity of the machine because such parameters would have been reflective of potential stressors or lack thereof to the machine.
Regarding Claim 13, Jarrell fails to disclose that the machine data detection unit contains infrastructure data and the individual function is configured to evaluate, as a further input variable, an installation site of the machine and is furthermore configured to ascertain therefrom environmental factors describing the environmental influences on the machine at the installation site of the machine; and
wherein the individual function is configured to utilize at least one environmental factor as at least one further correction factor for the calculation of the actual characteristic variable.
However, Horstemeyer discloses the use of infrastructure data and machine location and environment in assessing the longevity of a machine [See Paragraphs [0080]-[0081]]. It would have been obvious to use machine location and environment in assessing the longevity of the machine because such parameters would have been reflective of potential stressors or lack thereof to the machine.
Claim(s) 5 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”], Nair et al. (US 20220214680 A1)[hereinafter “Nair”], and Sato et al. (US 20170178015 A1)[hereinafter “Sato”].
Regarding Claim 5, Jarrell fails to disclose that a further input variable fed to the individual function comprises a period between two successive maintenance operations forming the basic maintenance interval, and a remaining residual time to the next maintenance interval; and
wherein, in the individual function, the remaining residual time is utilized as a further correction factor for the calculation of the actual characteristic variable which influences the health characteristic variable and thus the second time profile.
However, Sato discloses the determination of and use of maintenance intervals in determining the expected lifetime of a machine [See Abstract]. It would have been obvious to factor the maintenance interval of a machine into its lifetime prediction because doing so would have improved the accuracy of the lifetime prediction (less maintenance amounting to a stressor).
Regarding Claim 14, Jarrell fails to disclose that the individual function is configured to evaluate a period between two successive maintenance operations forming the basic maintenance interval, and a remaining residual time to the next maintenance interval as a further input variable; and
wherein the individual function is configured to utilize the remaining residual time as a further correction factor for the calculation of the actual characteristic variable.
However, Sato discloses the determination of and use of maintenance intervals in determining the expected lifetime of a machine [See Abstract]. It would have been obvious to factor the maintenance interval of a machine into its lifetime prediction because doing so would have improved the accuracy of the lifetime prediction (less maintenance amounting to a stressor).
Claim(s) 6 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”], Nair et al. (US 20220214680 A1)[hereinafter “Nair”], Wu et al. (US 10387287 B1)[hereinafter “Wu”], and Lee et al., Predictive Maintenance of Machine Tool Systems Using Artificial Intelligence Techniques Applied to Machine Condition Data, Elsevier, 2019 [hereinafter “Lee”].
Regarding Claim 6, Jarrell fails to disclose that the machine is divided into subcomponents and a degradation profile is provided for each subcomponent;
wherein, in the individual function, the degradation profiles of the subcomponents are used for the calculation of the actual characteristic variable.
However, Wu discloses the consideration of the state of system subcomponents on the lifetime of the system [See Abstract, Fig. 2, and all of Column 9]. It would have been obvious to produce degradation profiles [per Jarrell] for the system subcomponents and to factor the resulting subcomponent states into the determination of the degradation of the total system because doing so would have improved the accuracy of the determination of the lifetime of the machine through consideration of the state of the parts of the machine.
Jarrell also fails to disclose that, when a subcomponent has been replaced by a replacement part, the associated degradation profile is shifted in time for the calculation in the individual function such that the health characteristic variable is positively influenced.
However, Lee discloses that replacing a machine component positively influences machine lifetime [Abstract – “Scheduled maintenance replaces components”See the “Extended Life” resulting from maintenance in Fig. 1.]. It would have been obvious to extend the lifetime of the machine upon replacement of a part because Lee teaches that doing so extends the machine lifetime.
Regarding Claim 17, Jarrell fails to disclose that the individual function is configured to evaluate degradation profiles of subcomponents of the machine, a subcomponent library being provided for this purpose;
wherein the degradation profiles are allocated to subcomponents of the machine;
wherein the individual function is configured to utilize the degradation profiles of the subcomponents for the calculation of the actual characteristic variable and, as time progresses, to reduce the actual characteristic variable.
However, Wu discloses the consideration of the state of system subcomponents on the lifetime of the system [See Abstract, Fig. 2, and all of Column 9]. It would have been obvious to produce degradation profiles [per Jarrell] for the system subcomponents and to factor the resulting subcomponent states into the determination of the degradation of the total system because doing so would have improved the accuracy of the determination of the lifetime of the machine through consideration of the state of the parts of the machine.
Jarrell also fails to disclose that the health model is configured, when a subcomponent has been replaced by a replacement part, to shift the associated degradation profile for this replaced subcomponent in time for the calculation in the individual function and thus positively influence the health characteristic variable
However, Lee discloses that replacing a machine component positively influences machine lifetime [Abstract – “Scheduled maintenance replaces components”See the “Extended Life” resulting from maintenance in Fig. 1.]. It would have been obvious to shift the associated degradation profile for this replaced subcomponent in time upon replacement of a part because Lee teaches that doing so extends the machine lifetime.
Claim(s) 3, 8, 12, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”], Nair et al. (US 20220214680 A1)[hereinafter “Nair”], and Horstemeyer et al. (US 20160247128 A1)[hereinafter “Horstemeyer”].
Regarding Claim 3, Jarrell fails to disclose that a further input variable fed to the individual function comprises an installation site of the machine with which environmental factors describing the environmental influences on the machine at the installation site of the machine are ascertained; and
wherein, in the individual function, at least one environmental factor is utilized as at least one further correction factor for the calculation of the actual characteristic variable which influences the health characteristic variable and thus the second time profile.
However, Horstemeyer discloses the use of machine location and environment in assessing the longevity of a machine [See Paragraphs [0080]-[0081]]. It would have been obvious to use machine location and environment in assessing the longevity of the machine because such parameters would have been reflective of potential stressors or lack thereof to the machine.
Regarding Claim 8, Jarrell fails to disclose that online calculation of machine insurance is performed to ascertain insurance rates; and wherein the actual state and the deterioration of the machine is visually displayed to a machine operator and an insurer such that an insurance risk is determinable, the insurance rates being dynamically adjusted.
However, Horstemeyer discloses the use of a system that would allow for calculating machine insurance at different rates and doing so based on expected machine lifetime [See Fig. 5 and Paragraphs [0011] and [0077]]. It would have been obvious to use such a system to present a display of the predicted lifetime information of Jarrell to an insurance broker and machine operator so that the insurance broker could provide options for machine insurance rates and the machine operator can better understand them. It would have been obvious to provide the predicted lifetime information of Jarrell to an insurance broker as time goes on so that the insurance broker could appropriately adjust policy rates.
Regarding Claim 12, Jarrell fails to disclose that the machine data detection unit contains infrastructure data and the individual function is configured to evaluate, as a further input variable, an installation site of the machine and is furthermore configured to ascertain therefrom environmental factors describing the environmental influences on the machine at the installation site of the machine; and
wherein the individual function is configured to utilize at least one environmental factor as at least one further correction factor for the calculation of the actual characteristic variable.
However, Horstemeyer discloses the use of infrastructure data and machine location and environment in assessing the longevity of a machine [See Paragraphs [0080]-[0081]]. It would have been obvious to use machine location and environment in assessing the longevity of the machine because such parameters would have been reflective of potential stressors or lack thereof to the machine.
Regarding Claim 19, Jarrell fails to disclose that the computer system performs an online calculation of a machine insurance and ascertains insurance rates; wherein the actual state and deterioration of the machine is visually displayable to the machine operator and an insurer on the screen view such that an insurance risk is bilaterally determinable, insurance rates being dynamically adjustable.
However, Horstemeyer discloses the use of a system that would allow for calculating machine insurance at different rates and doing so based on expected machine lifetime [See Fig. 5 and Paragraphs [0011] and [0077]]. It would have been obvious to use such a system to present a display of the predicted lifetime information of Jarrell to an insurance broker and machine operator so that the insurance broker could provide options for machine insurance rates and the machine operator can better understand them. It would have been obvious to provide the predicted lifetime information of Jarrell to an insurance broker as time goes on so that the insurance broker could appropriately adjust policy rates.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”], Nair et al. (US 20220214680 A1)[hereinafter “Nair”], Franklin et al. (US 20080126040 A1)[hereinafter “Franklin”], Ohtsuka et al. (US 5608845 A)[hereinafter “Ohtsuka”] and Wu et al. (US 10387287 B1)[hereinafter “Wu”].
Regarding Claim 9, although Jarrell discloses that the degradation profile follows an exponential trend [See Figs. 2 and 3], Jarrell fails to disclose that an exponential function is utilized in the base function in accordance with the following relationship:
h(t)=1-d-exp(atb).
However, Ohtsuka discloses the use of such an exponential function for modelling lifetime [See Equation 2 at Column 7]. It would have been obvious to use such an exponential function to model the predicted lifetime of Jarrell because doing so would have been an effective manner of modelling the exponential trend of Jarrell’s degradation profile. It would have been obvious to select appropriate parameters for use in the model as doing so would have amounted to a design choice within ordinary skill in the art for one performing an exponential decay analysis.
Jarrell also fails to disclose that a function with the following subfunctions is utilized in the individual function, where the actual characteristic variable (hi) = A*K1 + B*K2 + C*K3 +D* Σ f(t), subcomponents.
However, Wu discloses the use of a weighted average for determining the health of a system based on weighted values for system subcomponents [See Abstract, Fig. 2, and all of Column 9 including the disclosed Equations]. It would have been obvious to take such an approach in assessing the health of the machine because this would have been an effective manner of doing so in configuration of machine subcomponents.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”], Nair et al. (US 20220214680 A1)[hereinafter “Nair”], Ohtsuka et al. (US 5608845 A)[hereinafter “Ohtsuka”], Wu et al. (US 10387287 B1)[hereinafter “Wu”], and Sato et al. (US 20170178015 A1)[hereinafter “Sato”].
Regarding Claim 15, Jarrell fails to disclose that the individual function is configured to evaluate a period between two successive maintenance operations forming the basic maintenance interval, and a remaining residual time to the next maintenance interval as a further input variable; and
wherein the individual function is configured to utilize the remaining residual time as a further correction factor for the calculation of the actual characteristic variable.
However, Sato discloses the determination of and use of maintenance intervals in determining the expected lifetime of a machine [See Abstract]. It would have been obvious to factor the maintenance interval of a machine into its lifetime prediction because doing so would have improved the accuracy of the lifetime prediction (less maintenance amounting to a stressor).
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarrell et al. (US 20040030524 A1)[hereinafter “Jarrell”], Nair et al. (US 20220214680 A1)[hereinafter “Nair”], Horstemeyer et al. (US 20160247128 A1)[hereinafter “Horstemeyer”], and Sato et al. (US 20170178015 A1)[hereinafter “Sato”].
Regarding Claim 16, Jarrell fails to disclose that the individual function is configured to evaluate a period between two successive maintenance operations forming the basic maintenance interval, and a remaining residual time to the next maintenance interval as a further input variable; and
wherein the individual function is configured to utilize the remaining residual time as a further correction factor for the calculation of the actual characteristic variable.
However, Sato discloses the determination of and use of maintenance intervals in determining the expected lifetime of a machine [See Abstract]. It would have been obvious to factor the maintenance interval of a machine into its lifetime prediction because doing so would have improved the accuracy of the lifetime prediction (less maintenance amounting to a stressor).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 20230049526 A1 – PREDICTIVE MODELING OF HEALTH OF A DRIVEN GEAR IN AN OPEN GEAR SET (See Fig. 15)
Ye et al., Reliability Analysis of Manufacturing Machine with Degradation and Low-quality Feedstocks, IEEE, 2020
Garcia et al., Maintenance Strategies for Industrial Multi-Stage Machines: The Study of a Thermoforming Machine, MDPI, 2021
US 20190226944 A1 – Prediction Of Remaining Useful Lifetime For Bearings
US 20030182014 A1 – Tool Wear Monitoring System
US 20200341459 A1 – PREDICTIVE MAINTENANCE METHOD FOR COMPONENT OF PRODUCTION TOOL AND COMPUTER PROGRAM PRODUCT THEREROF
US 20210374644 A1 – EQUIPMENT LIFETIME PREDICTION BASED ON THE TOTAL COST OF OWNERSHIP
US 20220198357 A1 – APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR MONITORING ASSET REMAINING USEFUL LIFETIME
US 20170323274 A1 – CONTROLLING AIRCRAFT OPERATIONS AND AIRCRAFT ENGINE COMPONENTS ASSIGNMENT
US 20230131828 A1 – PREDICTIVE MAINTENANCE SYSTEM AND METHOD FOR INTELLIGENT MANUFACTURING EQUIPMENT
US 20230400847 A1 – PREDICTIVE MAINTENANCE FOR SEMICONDUCTOR MANUFACTURING EQUIPMENT
US 20120283963 A1 – METHOD FOR PREDICTING A REMAINING USEFUL LIFE OF AN ENGINE AND COMPONENTS THEREOF
US 20160292652 A1 – PREDICTIVE ANALYTIC RELIABILITY TOOL SET FOR DETECTING EQUIPMENT FAILURES
US 20210080941 A1 – SCALABLE PREDICTIVE MAINTENANCE FOR INDUSTRIAL AUTOMATION EQUIPMENT
US 4707796 A – Reliability And Maintainability Indicator
US 5808919 A – Diagnostic System
US 7457785 B1 – Method And Apparatus To Predict The Remaining Service Life Of An Operating System
US 9218694 B1 – Recommendations For Time To Replace Parts On Machines
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KYLE ROBERT QUIGLEY whose telephone number is (313)446-4879. The examiner can normally be reached 9AM-5PM EST.
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/KYLE R QUIGLEY/Primary Examiner, Art Unit 2857