DETAILED ACTION
This is the final Office action and is responsive to the papers filed 10/23/2025. The amendments filed on 10/23/2025 have been entered and considered by the examiner. Claims 1-7, 9-10, 12 and 14-24 are currently pending and examined below. Claims 1, 10, 15, 19 and 24 have been amended.
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 .
Response to Arguments
Applicant's arguments, see page 9, filed 10/23/2025, with respect to claims 1-7, 9-10, 12 and 14-24 have been fully considered but they are partially persuasive.
The relationship between the pieces of equipment and output units/aircraft bodies is still unclear. See below for further detail.
Applicant’s arguments, see pages 9-12, filed 10/23/2025, with respect to the rejection(s) of claim(s) 1-7, 9-10, 12 and 14-24 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Ethington et al. (US 20170166328 A1; hereinafter Ethington).
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.
Claims 15, 18-19 and 22-24 are 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.
In claim 15, the recitation “wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load exerted on each of the plurality of output units differs by the regions where the pieces of equipment are respectively operated, wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop” is unclear. First, it is unclear because there is no previous mentioning of pieces of equipment when the claim refers to “the” pieces of equipment. Next, it is unclear where and how pieces of equipment are related to the output units. Why are we swapping regions on the pieces of equipment when the load (or stress) is exerted on the output units? What does it mean by “when a load exerted on each of the plurality of output units differs by the regions where the pieces of equipment are respectively operated”? Is it a load on region where output units are located? Or region of the pieces of equipment are located?
In claim 19 and 24, the recitation “wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load exerted on each of the plurality of aircraft bodies differs by the regions where the pieces of equipment are respectively operated, wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop” is unclear. First, it is unclear because there is no previous mentioning of pieces of equipment when the claim refers to “the” pieces of equipment. Next, it is unclear where and how pieces of equipment are related to the aircraft bodies. Why are we swapping regions on the pieces of equipment when the load (or stress) is exerted on the aircraft bodies? What does it mean by “when a load exerted on each of the plurality of aircraft bodies differs by the regions where the pieces of equipment are respectively operated”? Is it a load on region where aircraft bodies are located? Or region of the pieces of equipment are located?
Claims 18 and 22-23 are rejected as they depend upon rejected claims 15 and 19.
Appropriate corrections are required.
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 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 1-7, 9-10, 12 and 14-23 are rejected under 35 U.S.C. 103 as being unpatentable over Ethington et al. (US 20170166328 A1; hereinafter Ethington) in view of Hessling von Heimendahl (US 20160076722 A1) and in view of Pang (US 20170097860 A1).
Regarding claim 1, Ethington discloses:
A fatigue level calculating device (Fig. 1: predictive maintenance systems 10), comprising:
an environment information acquiring unit (Fig. 1, [0022] sensors 26 and/or controllers 50 are configured to collect data during flight of the aircraft 20) that acquires environment information pertaining to an environment in surroundings of pieces of equipment ([0020] sensors 26 may measure and/or monitor the environmental condition, the condition of one or more components 24, and/or the inputs and/or outputs of the subsystem 22, [0022] The data collected are referred to as flight data. Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)); and
a fatigue level calculating unit (Fig. 1: predictive maintenance systems 10) that calculates a relationship between an operation condition of each of the pieces of equipment and a fatigue level of the pieces of equipment that progresses as a load exerted on each of the pieces of equipment accumulates, based on the environment information ([0047] The flight data and the extracted feature data may relate to the performance of the aircraft, the subsystem that includes the selected component, and/or the selected component. The flight data may be collected during a single flight or a series of flights. Using flight data from a series of flights may provide a more reliable prediction of component performance because of the greater amount of flight data and/or because the aircraft, the subsystem, and/or the component are more likely to be subjected to a greater range of conditions and/or particular stress conditions),
wherein the fatigue level calculating unit manages an operation of each of the pieces of equipment based on the fatigue level calculated from the relationship calculated ([0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component),
wherein a relationship between a number of flights and the fatigue level of respective actuators of the pieces of equipment corresponding to the respective operated regions is calculated by analyzing the number of the flights of the pieces of equipment operated in the regions and data on the frequency of failures ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)), [0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component, [0041] Classifiers 66 of the ensemble of related classifiers each provide a category (e.g., a likelihood of component non-performance) relating to a different given number of flights (hence, the ensemble also may be referred to as an ensemble of different time horizon classifiers).
Ethington does not specifically disclose:
pieces of equipment operated in different operation patterns;
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load exerted on each of the pieces of equipment differs by the regions where the pieces of equipment are respectively operated,
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop.
However, Hessling von Heimendahl discloses:
pieces of equipment (a plurality of the LEDs; [0020]) operated in different operation patterns (applying/switching different operating modes of different intensities of a plurality of the LEDs; [0020]);
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load (thermal stress on the dynamic aircraft headlight; [0020]) exerted on each of the pieces of equipment differs by the regions where the pieces of equipment are respectively operated (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and the operating temperature of the dynamic aircraft headlight below a threshold level and thus for limiting the thermal stress on the electronic components; [0020]),
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and to limit the thermal stress on the dynamic aircraft headlight; [0020]).
Ethington and Hessling von Heimendahl are considered to be analogous to the claimed invention because they are in the same field of fatigue/material testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
Ethington as modified does not specifically disclose:
wherein the environment information acquiring unit acquires the environment information as an operator inputs the environment information based on a service record or a failure record.
However, Pang discloses:
wherein the information acquiring unit acquires the information as an operator inputs the information based on a service record or a failure record (a user also may manually input the component failure symptoms into the computer via a user interface, such as web-based user interface 302 in FIG. 3).
Pang is analogous to the claimed invention because it pertains to the same field of diagnostic testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’ testing as currently modified to further incorporate Pang’s testing for the advantage of user inputting relevant information to the testing which results in a more comprehensive data collection for test evaluation.
Regarding claim 2, Ethington discloses:
wherein the environment information acquiring unit acquires the environment information during operation of the equipment ([0047] flight data collected during a flight of the aircraft).
Regarding claim 3, Ethington discloses:
wherein the environment information acquiring unit acquires the environment information before operation of the equipment ([0052] each classifier 66 of an ensemble of two classifiers that estimates the future component performance within 1 flight and 2 flights may be supplied feature data relating to three previous flights).
Regarding claim 4, Ethington discloses:
wherein the environment information acquiring unit acquires the environment information after operation of the equipment ([0052] each classifier 66 of an ensemble of two classifiers that estimates the future component performance within 1 flight and 2 flights may be supplied feature data relating to three previous flights).
Regarding claim 5, Ethington discloses:
wherein the environment information includes at least one of a temperature, a humidity, an amount of dust, a surge voltage, a concentration of a chemical substance, and a radiation exposure dose ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)).
Regarding claim 6, Ethington discloses:
wherein the environment information acquiring unit includes a sensor provided in the surroundings of the equipment ([0020] sensors 26 may measure and/or monitor the environmental condition, the condition of one or more components 24, and/or the inputs and/or outputs of the subsystem 22).
Regarding claim 7, Ethington discloses:
wherein the environment information acquiring unit acquires the environment information based on weather information ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity)).
Regarding claim 9, Ethington discloses:
wherein the equipment is transportation equipment or a device constituting a portion of the transportation equipment (Fig. 1: aircraft 20 may be used for transportation).
Regarding claim 10, Ethington discloses:
A fatigue level calculating method, comprising:
an environment information acquiring step (Fig. 1, [0022] sensors 26 and/or controllers 50 are configured to collect data during flight of the aircraft 20) of acquiring environment information pertaining to an environment in surroundings of pieces of equipment ([0020] sensors 26 may measure and/or monitor the environmental condition, the condition of one or more components 24, and/or the inputs and/or outputs of the subsystem 22, [0022] The data collected are referred to as flight data. Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)); and
a fatigue level calculating step (Fig. 1: predictive maintenance systems 10) of calculating a relationship between an operation condition of each of the pieces of equipment and a fatigue level of the pieces of equipment that progresses as a load exerted on each of the pieces of equipment accumulates, based on the environment information ([0047] The flight data and the extracted feature data may relate to the performance of the aircraft, the subsystem that includes the selected component, and/or the selected component. The flight data may be collected during a single flight or a series of flights. Using flight data from a series of flights may provide a more reliable prediction of component performance because of the greater amount of flight data and/or because the aircraft, the subsystem, and/or the component are more likely to be subjected to a greater range of conditions and/or particular stress conditions),
a management step of managing an operation of each of the pieces of equipment based on the fatigue level calculated from the relationship calculated in the fatigue level calculating step ([0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component),
a relationship between a number of flights and the fatigue level of respective actuators of the pieces of equipment corresponding to the respective operated regions is calculated by analyzing the number of the flights of the pieces of equipment operated in the regions and data on the frequency of failures ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)), [0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component, [0041] Classifiers 66 of the ensemble of related classifiers each provide a category (e.g., a likelihood of component non-performance) relating to a different given number of flights (hence, the ensemble also may be referred to as an ensemble of different time horizon classifiers).
Ethington does not specifically disclose:
pieces of equipment operated in different operation patterns;
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load exerted on each of the pieces of equipment differs by the regions where the pieces of equipment are respectively operated,
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop.
However, Hessling von Heimendahl discloses:
pieces of equipment (a plurality of the LEDs; [0020]) operated in different operation patterns (applying/switching different operating modes of different intensities of a plurality of the LEDs; [0020]);
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load (thermal stress on the dynamic aircraft headlight; [0020]) exerted on each of the pieces of equipment differs by the regions where the pieces of equipment are respectively operated (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and the operating temperature of the dynamic aircraft headlight below a threshold level and thus for limiting the thermal stress on the electronic components; [0020]),
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and to limit the thermal stress on the dynamic aircraft headlight; [0020]).
Ethington and Hessling von Heimendahl are considered to be analogous to the claimed invention because they are in the same field of fatigue/material testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
Ethington as modified does not specifically disclose:
wherein the environment information is acquired as an operator inputs the environment information based on a service record or a failure record.
However, Pang discloses:
wherein the information is acquired as an operator inputs the information based on a service record or a failure record (a user also may manually input the component failure symptoms into the computer via a user interface, such as web-based user interface 302 in FIG. 3).
Pang is analogous to the claimed invention because it pertains to the same field of diagnostic testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’ testing as currently modified to further incorporate Pang’s testing for the advantage of user inputting relevant information to the testing which results in a more comprehensive data collection for test evaluation.
Regarding claim 12, Ethington discloses:
further comprising: an evaluating step of comparing the fatigue level calculated from the relationship calculated in the fatigue level calculating step against a predetermined threshold for an evaluation ([0039] the outputs of the (related) classifiers 66 (also referred to as the classifier indicators) may include a probability metric (e.g., a number representing the likelihood of component non-performance), a “good” state (indicating a likelihood of component performance above a predetermined threshold and/or indicating a likelihood of component non-performance below a predetermined threshold), an “impending non-performance” state (indicating a likelihood of component non-performance above a predetermined threshold and/or indicating a likelihood of component performance below a predetermined threshold), and/or an “abstain” state (indicating the classifier did not reliably establish another state and/or metric)).
Regarding claim 14, Ethington discloses:
wherein the equipment is transportation equipment or a device constituting a portion of the transportation equipment (Fig. 1: aircraft 20 may be used for transportation).
Regarding claim 15, Ethington discloses:
An actuator (Fig. 1: aircraft 20 may be used for transportation), comprising:
an environment information acquiring unit (Fig. 1, [0022] sensors 26 and/or controllers 50 are configured to collect data during flight of the aircraft 20) that acquires environment information pertaining to an environment in surroundings of the plurality of output units ([0020] sensors 26 may measure and/or monitor the environmental condition, the condition of one or more components 24, and/or the inputs and/or outputs of the subsystem 22, [0022] The data collected are referred to as flight data. Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)); and
a fatigue level calculating unit (Fig. 1: predictive maintenance systems 10) that calculates a relationship between an operation condition of each of the plurality of output units and a fatigue level of the plurality of output units that progresses as a load exerted on each of the plurality of output units accumulates, based on the environment information acquired by the environment information acquiring unit ([0047] The flight data and the extracted feature data may relate to the performance of the aircraft, the subsystem that includes the selected component, and/or the selected component. The flight data may be collected during a single flight or a series of flights. Using flight data from a series of flights may provide a more reliable prediction of component performance because of the greater amount of flight data and/or because the aircraft, the subsystem, and/or the component are more likely to be subjected to a greater range of conditions and/or particular stress conditions),
wherein the fatigue level calculating unit manages an operation of each of the plurality of output units based on the fatigue level calculated from the relationship calculated ([0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component),
wherein the environment information acquiring unit acquires the environment information as an operator inputs the environment information based on a service record or a failure record, and
a relationship between a number of flights and the fatigue level of respective actuators of the pieces of equipment corresponding to the respective operated regions is calculated by analyzing the number of the flights of the pieces of equipment operated in the regions and data on the frequency of failures ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)), [0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component, [0041] Classifiers 66 of the ensemble of related classifiers each provide a category (e.g., a likelihood of component non-performance) relating to a different given number of flights (hence, the ensemble also may be referred to as an ensemble of different time horizon classifiers).
Ethington does not specifically disclose:
a plurality of output units that output a power and that are operated in different operation patterns;
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load exerted on each of the plurality of output units differs by the regions where the pieces of equipment are respectively operated,
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop.
However, Hessling von Heimendahl discloses:
a plurality of output units (a plurality of the LEDs; [0020]) that output a power and that are operated in different operation patterns (applying/switching different operating modes of different intensities of a plurality of the LEDs; [0020]);
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load (thermal stress on the dynamic aircraft headlight; [0020]) exerted on each of the plurality of output units differs by the regions where the pieces of equipment are respectively operated (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and the operating temperature of the dynamic aircraft headlight below a threshold level and thus for limiting the thermal stress on the electronic components; [0020]),
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and the operating temperature of the dynamic aircraft headlight below a threshold level and thus for limiting the thermal stress on the electronic components; [0020]).
Ethington and Hessling von Heimendahl are considered to be analogous to the claimed invention because they are in the same field of fatigue/material testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
Ethington as modified does not specifically disclose:
wherein the environment information acquiring unit acquires the environment information as an operator inputs the environment information based on a service record or a failure record.
However, Pang discloses:
wherein the information acquiring unit acquires the information as an operator inputs the information based on a service record or a failure record (a user also may manually input the component failure symptoms into the computer via a user interface, such as web-based user interface 302 in FIG. 3).
Pang is analogous to the claimed invention because it pertains to the same field of diagnostic testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’ testing as currently modified to further incorporate Pang’s testing for the advantage of user inputting relevant information to the testing which results in a more comprehensive data collection for test evaluation.
Regarding claim 16, Ethington discloses:
wherein the relationship between an operation condition of the equipment and a fatigue level of the equipment is the relationship between a frequency of use of the equipment and a fatigue level of the equipment ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)), [0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component, [0041] Classifiers 66 of the ensemble of related classifiers each provide a category (e.g., a likelihood of component non-performance) relating to a different given number of flights (hence, the ensemble also may be referred to as an ensemble of different time horizon classifiers).
Regarding claim 17, Ethington discloses:
wherein the relationship between an operation condition of the equipment and a fatigue level of the equipment is the relationship between a frequency of use of the equipment and a fatigue level of the equipment ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)), [0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component, [0041] Classifiers 66 of the ensemble of related classifiers each provide a category (e.g., a likelihood of component non-performance) relating to a different given number of flights (hence, the ensemble also may be referred to as an ensemble of different time horizon classifiers).
Regarding claim 18, Ethington discloses:
wherein the relationship between an operation condition of the output unit and a fatigue level of the output unit is the relationship between a frequency of use of the output unit and a fatigue level of the output unit ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)), [0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component, [0041] Classifiers 66 of the ensemble of related classifiers each provide a category (e.g., a likelihood of component non-performance) relating to a different given number of flights (hence, the ensemble also may be referred to as an ensemble of different time horizon classifiers).
Regarding claim 19, Ethington discloses:
An aircraft system (Fig. 1: predictive maintenance systems 10) comprising:
a plurality of aircraft bodies ([0017] a plurality of aircraft 20 (e.g., a fleet of aircraft 20)) capable of flying, the aircraft body including a plurality of devices (Fig. 1: components 34);
an environment information acquiring unit (Fig. 1, [0022] sensors 26 and/or controllers 50 are configured to collect data during flight of the aircraft 20) that acquires environment information pertaining to an environment in surroundings of at least one of the plurality of devices or the aircraft body ([0020] sensors 26 may measure and/or monitor the environmental condition, the condition of one or more components 24, and/or the inputs and/or outputs of the subsystem 22, [0022] The data collected are referred to as flight data. Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)); and
a fatigue level calculating unit (Fig. 1: predictive maintenance systems 10) that calculates a relationship between a respective operation condition of at least one of the plurality of devices or the aircraft body and a fatigue level of at least one of the plurality of devices or the aircraft body that progresses as a load exerted on each of the plurality of aircraft bodies accumulates, based on the environment information ([0047] The flight data and the extracted feature data may relate to the performance of the aircraft, the subsystem that includes the selected component, and/or the selected component. The flight data may be collected during a single flight or a series of flights. Using flight data from a series of flights may provide a more reliable prediction of component performance because of the greater amount of flight data and/or because the aircraft, the subsystem, and/or the component are more likely to be subjected to a greater range of conditions and/or particular stress conditions),
wherein the fatigue level calculating unit manages an operation of each of the plurality of aircraft bodies based on the fatigue level calculated from the relationship calculated ([0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component),
a relationship between a number of flights and the fatigue level of respective actuators of the aircraft bodies corresponding to the respective operated regions is calculated by analyzing the number of the flights of the aircraft bodies operated in the regions and data on the frequency of failures ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)), [0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component, [0041] Classifiers 66 of the ensemble of related classifiers each provide a category (e.g., a likelihood of component non-performance) relating to a different given number of flights (hence, the ensemble also may be referred to as an ensemble of different time horizon classifiers).
Ethington does not specifically disclose:
the aircraft body including a plurality of devices and operated in different operation patterns;
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load exerted on each of the plurality of aircraft bodies differs by the regions where the pieces of equipment are respectively operated,
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop.
However, Hessling von Heimendahl discloses:
the aircraft body (aircraft; [0020]) including a plurality of devices (a plurality of the LEDs; [0020]) and operated in different operation patterns (applying/switching different operating modes of different intensities of a plurality of the LEDs; [0020]);
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load (thermal stress on the dynamic aircraft headlight; [0020]) exerted on each of the plurality of aircraft bodies differs by the regions where the pieces of equipment are respectively operated (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and the operating temperature of the dynamic aircraft headlight below a threshold level and thus for limiting the thermal stress on the electronic components; [0020]),
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different from each other and the operated regions for the pieces of equipment are swapped in a loop (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and the operating temperature of the dynamic aircraft headlight below a threshold level and thus for limiting the thermal stress on the electronic components; [0020]).
Ethington and Hessling von Heimendahl are considered to be analogous to the claimed invention because they are in the same field of fatigue/material testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
Ethington as modified does not specifically disclose:
wherein the environment information acquiring unit acquires the environment information as an operator inputs the environment information based on a service record or a failure record.
However, Pang discloses:
wherein the information acquiring unit acquires the information as an operator inputs the information based on a service record or a failure record (a user also may manually input the component failure symptoms into the computer via a user interface, such as web-based user interface 302 in FIG. 3).
Pang is analogous to the claimed invention because it pertains to the same field of diagnostic testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’ testing as currently modified to further incorporate Pang’s testing for the advantage of user inputting relevant information to the testing which results in a more comprehensive data collection for test evaluation.
Regarding claim 20, Ethington does not specifically disclose:
wherein the fatigue level is leveled among the pieces of the equipment.
However, Hessling von Heimendahl discloses:
wherein the fatigue level is leveled among the pieces of the equipment (limiting the thermal stress on the electronic components; [0020]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
Regarding claim 21, Ethington does not specifically disclose:
wherein the fatigue level is leveled among the pieces of the equipment.
However, Hessling von Heimendahl discloses:
wherein the fatigue level is leveled among the pieces of the equipment (limiting the thermal stress on the electronic components; [0020]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
Regarding claim 22, Ethington does not specifically disclose:
wherein the fatigue level is leveled among the pieces of the equipment.
However, Hessling von Heimendahl discloses:
wherein the fatigue level is leveled among the pieces of the equipment (limiting the thermal stress on the electronic components; [0020]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
Regarding claim 23, Ethington does not specifically disclose:
wherein the fatigue level is leveled among the pieces of the equipment.
However, Hessling von Heimendahl discloses:
wherein the fatigue level is leveled among the pieces of the equipment (limiting the thermal stress on the electronic components; [0020]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
Claim 24 is rejected under 35 U.S.C. 103 as being unpatentable over Ethington in view of Hessling von Heimendahl.
Regarding claim 24, Ethington discloses:
An aircraft system (Fig. 1: predictive maintenance systems 10) comprising:
a plurality of aircraft bodies ([0017] a plurality of aircraft 20 (e.g., a fleet of aircraft 20)) capable of flying, the aircraft body including a plurality of devices (Fig. 1: components 24);
an environment information acquiring unit (Fig. 1, [0022] sensors 26 and/or controllers 50 are configured to collect data during flight of the aircraft 20) that acquires environment information pertaining to an environment in surroundings of at least one of the plurality of devices or the aircraft body ([0020] sensors 26 may measure and/or monitor the environmental condition, the condition of one or more components 24, and/or the inputs and/or outputs of the subsystem 22, [0022] The data collected are referred to as flight data. Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation));
a fatigue level calculating unit (Fig. 1: predictive maintenance systems 10) that calculates a relationship between a respective operation condition of at least one of the plurality of devices or the aircraft body and a fatigue level of at least one of the plurality of devices or the aircraft body that progresses as a load exerted on each of the plurality of aircraft bodies accumulates, based on the environment information ([0047] The flight data and the extracted feature data may relate to the performance of the aircraft, the subsystem that includes the selected component, and/or the selected component. The flight data may be collected during a single flight or a series of flights. Using flight data from a series of flights may provide a more reliable prediction of component performance because of the greater amount of flight data and/or because the aircraft, the subsystem, and/or the component are more likely to be subjected to a greater range of conditions and/or particular stress conditions), and
a database in which the environment information is accumulated each time the equipment is operated ([0022] Controller 50 may be configured to store flight data and may be referred to as a flight data storage system),
wherein the fatigue level calculating unit manages an operation of each of the plurality of aircraft bodies based on the fatigue level calculated from the relationship calculated ([0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component),
wherein data are uploaded to the environment information acquiring unit from the database at a prescribed timing ([0049] Flight data may be collected systematically, e.g., consistently on substantially every flight, consistently in substantially every aircraft, and/or on a consistent basis (e.g., periodically)…Flight data relating to the same sensor generally forms a time series (e.g., periodic, quasi-periodic, or aperiodic)), and
a relationship between a number of flights and the fatigue level of respective actuators of the aircraft bodies corresponding to the respective operated regions is calculated by analyzing the number of the flights of the aircraft bodies operated in the regions and data on the frequency of failures ([0022] Data may include records of environmental conditions (e.g., temperature, pressure, humidity), aircraft operation (e.g., airspeed, altitude, ground location, angle of attack), subsystem operation (actual operation), subsystem command status (expected operation), component operation (actual operation), and/or component command status (expected operation)), [0036] The predictive maintenance system 10 utilizes data analytics in the form of machine learning classifiers 66 to identify conditions which may indicate future performance (e.g., impending non-performance event) of a component, [0041] Classifiers 66 of the ensemble of related classifiers each provide a category (e.g., a likelihood of component non-performance) relating to a different given number of flights (hence, the ensemble also may be referred to as an ensemble of different time horizon classifiers).
Ethington does not specifically disclose:
the aircraft body including a plurality of devices and operated in different operation patterns;
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load exerted on each of the plurality of aircraft bodies differs by the regions where the pieces of equipment are respectively operated,
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different each other and the operated regions for the pieces of equipment are swapped in a loop.
However, Hessling von Heimendahl discloses:
the aircraft body including a plurality of devices (a plurality of the LEDs; [0020]) and operated in different operation patterns (applying/switching different operating modes of different intensities of a plurality of the LEDs; [0020]);
wherein, in managing the operation, regions where the pieces of equipment are respectively operated are swapped in a loop when a load (thermal stress on the dynamic aircraft headlight; [0020]) exerted on each of the plurality of aircraft bodies differs by the regions where the pieces of equipment are respectively operated (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and the operating temperature of the dynamic aircraft headlight below a threshold level and thus for limiting the thermal stress on the electronic components; [0020]),
wherein the pieces of equipment are operated in the respective regions of which respective temperatures are different each other and the operated regions for the pieces of equipment are swapped in a loop (Hessling von Heimendahl may switch on less than 40-60% of the plurality of LED in one region for operating mode 1, then switch on less than 40-60% of the plurality of LED in another region for operating mode 2, then switch on less than 40-60% of the plurality of LED in yet another region for operating mode 3 for different output light intensity distributions and the operating temperature of the dynamic aircraft headlight below a threshold level and thus for limiting the thermal stress on the electronic components; [0020]).
Ethington and Hessling von Heimendahl are considered to be analogous to the claimed invention because they are in the same field of fatigue/material testing. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ethington’s fatigue testing to further incorporate Hessling von Heimendahl’s fatigue testing for the advantage of operating modes for environment control which results in limiting/balancing the fatigue load on the aircraft components (Hessling von Heimendahl’s [0020]).
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.
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/PAYSUN WU/Examiner, Art Unit 3665
/DONALD J WALLACE/Primary Examiner, Art Unit 3665