DETAILED ACTION
The present office action is responsive to the applicant’s filling the application on 8/18/2023.
The application has claims 1-13 present. All present claims have been examined.
The Information Disclosure Statements (IDS) and cited references filed 8/18/203 and 11/14/2023, have been reviewed by the examiner.
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 .
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
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 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more.
Claim 1 describes obtaining data in time series from an equipment (data from machine), compiling a data set and analyzing the obtained data to determine if a status of the equipment has change. The analysis looks at the data over a time series and calculates a mean value and a normalized value See par. 7-8 of the specification. Accordingly, claims 1 recites an abstract idea because the particular limitations, as briefly outlined above, fall into at least one of the groupings of abstract ideas (see MPEP 2106.04(a)).
Limitations under prong 1:
The specific limitations of
- “determining…change of status… from time series” (this is a mental process using the device as a tool to apply the abstract idea)
- “determining a mean value and standard deviation… and calculating a normalized value…” (these are mathematical concepts - see MPEP § 2106.04(a)(2)).
- “grouping pieces of data” (these are mathematical concepts - see MPEP § 2106.04(a)(2)).
Limitations under prong 2:
“diagnosis device…processor…” generally linking the use of the judicial exception to a particular technological environment or field of use,– see MPEP 2106.05(h).
“storing time series data…” is insignificant extra-solution activity to the judicial exception, as mere data gathering (See MPEP 2106.05(g)).
“Processing of outputting…” (gathering and presenting the calculated data) is insignificant extra-solution activity to the judicial exception, as mere data gathering (See MPEP 2106.05(g)).
Step 2B – not significant more.
Thus, the recited “Device” is an abstract idea in that it is not tied to a particular machine or apparatus. Furthermore, the additional element of using a computer, sensor as a tool to perform the recited steps amounts to no more than mere instructions to apply the abstract idea using a generic computer component. Mere instructions to apply a judicial exception using a generic computer component cannot provide an inventive concept.
Accordingly, the recited device is non-statutory subject matter.
Claim 2: “wherein the sensor is a vibration sensor, and the time series data is data of a vibration level of the equipment”. Abstract idea, fall under Step 2A, prong 2 as merely uses a computer and sensor as a tool to perform the abstract idea.
Claim 3. “wherein the processor divides the reference data into a predetermined number of pieces of the reference data and divides the comparison data into a predetermined number of pieces of the comparison data, and calculates the mean value and the standard deviation of the reference data and the normalized value of the comparison data from the mean value and the standard deviation of the reference data and a difference between a maximum value and a minimum value of the pieces of the data in each division period”. further describes the abstract idea and mathematical process previously identified in the independent claims. Thus, the claims recite an abstract idea and are not patent-eligible.
Claim 4. “for each of the reference data and the comparison data, processing of grouping in the order of the magnitude relationship between the pieces of data by grouping the plurality of sensors into a same group and a different group according to whether or not the pieces of data of the plurality of sensors fall within a range having a standard deviation in normal distribution as a reference” It further describes the abstract idea and mathematical process previously identified in the independent claims. Thus, the claims recite an abstract idea and are not patent-eligible.
Claim 5 describes a method for obtaining data in time series from an equipment (data from machine), compiling a data set and analyzing the obtained data to determine if a status of the equipment has change. The analysis looks at the data over a time series and calculates a mean value and a normalized value See par. 7-8 of the specification. Accordingly, claims 1 recites an abstract idea because the particular limitations, as briefly outlined above, fall into at least one of the groupings of abstract ideas (see MPEP 2106.04(a)).
Limitations under prong 1:
The specific limitations of
- “processing of determining a mean value and standard deviation… and calculating a normalized value…” (these are mathematical concepts - see MPEP § 2106.04(a)(2)).
- “processing of grouping pieces of data” (these are mathematical concepts - see MPEP § 2106.04(a)(2)).
Limitations under prong 2:
“Processing of outputting…” (gathering and presenting the calculated data) is insignificant extra-solution activity to the judicial exception, as mere data gathering (See MPEP 2106.05(g)).
Step 2B – not significant more.
Thus, the recited “Method” is an abstract idea in that it is not tied to a particular machine or apparatus. Furthermore, the additional element of using a computer, sensor as a tool to perform the recited steps amounts to no more than mere instructions to apply the abstract idea using a generic computer component. Mere instructions to apply a judicial exception using a generic computer component cannot provide an inventive concept.
Accordingly, the recited Method is non-statutory subject matter.
Claim 6 is rejected along the same rationale as claim 5, as is a computer readable medium with the instructions as provided in claim 5.
Claim 7 describes obtaining data in time series from an equipment (data from machine), divides the data from start to end in a time series and calculates a representative value indicative of a relative relationship of data See par. 16-17 of the specification. Accordingly, claims 7 recites an abstract idea because the particular limitations, as briefly outlined above, fall into at least one of the groupings of abstract ideas (see MPEP 2106.04(a)).
Limitations under prong 1:
The specific limitations of
- “determining…change of status… from time series” (this is a mental process using the device as a tool to apply the abstract idea)
- “calculation processing of dividing data from a start to an end of a specific operation cycle in the time series data for each of unit periods…” (these are mathematical concepts - see MPEP § 2106.04(a)(2)).
- “grouping processing of assigning a group number which is selected in order of magnitude of the representative value to the data in each of the unit periods” (these are mathematical concepts - see MPEP § 2106.04(a)(2)).
Limitations under prong 2:
“diagnosis device…processor…” generally linking the use of the judicial exception to a particular technological environment or field of use,– see MPEP 2106.05(h).
“storing time series data…” is insignificant extra-solution activity to the judicial exception, as mere data gathering (See MPEP 2106.05(g)).
“output processing of outputting a screen of a graph…” (gathering and presenting the calculated data) is insignificant extra-solution activity to the judicial exception, as mere data gathering (See MPEP 2106.05(g)).
Step 2B – not significant more.
Thus, the recited “Device” is an abstract idea in that it is not tied to a particular machine or apparatus. Furthermore, the additional element of using a computer, sensor as a tool to perform the recited steps amounts to no more than mere instructions to apply the abstract idea using a generic computer component. Mere instructions to apply a judicial exception using a generic computer component cannot provide an inventive concept.
Accordingly, the recited device is non-statutory subject matter.
Claim 8 “wherein the processor calculates a value obtained by squaring a normalized value indicative of magnitude of a degree of dispersion of the data in each of the unit periods and totalizing the value obtained by the squaring which corresponds to the plurality of sensors as the representative value for each of the unit periods in the calculation processing” It further describes the abstract idea and mathematical process previously identified in the independent claims. Thus, the claims recite an abstract idea and are not patent-eligible.
Claim 9 “wherein the processor calculates a mean value A of each of the unit periods for a difference between a maximum value and a minimum value which are calculated individually after the data in each of the unit periods is divided into a predetermined number of pieces of the data…” It further describes the abstract idea and mathematical process previously identified in the independent claims. Thus, the claims recite an abstract idea and are not patent-eligible.
Claim 10 “wherein the processor determines that the representative values of pieces of data in a specific unit period which is one of the individual unit periods and pieces of data in another specific unit period whose ranges between minimum values and maximum values…” It further describes the abstract idea and mathematical process previously identified in the independent claims. Thus, the claims recite an abstract idea and are not patent-eligible.
Claim 11 “wherein each of the plurality of sensors is a vibration sensor, and the time series data is data of a vibration level of the equipment” Abstract idea, fall under Step 2A, prong 2 as merely uses a computer and sensor as a tool to perform the abstract idea.
Claim 12 describes obtaining data in time series from an equipment (data from machine), divides the data from start to end in a time series and calculates a representative value indicative of a relative relationship of data See par. 16-17 of the specification. Accordingly, claims 7 recites an abstract idea because the particular limitations, as briefly outlined above, fall into at least one of the groupings of abstract ideas (see MPEP 2106.04(a)).
Limitations under prong 1:
The specific limitations of
-
- “calculation processing of dividing data from a start to an end of a specific operation cycle in the time series data for each of unit periods…” (these are mathematical concepts - see MPEP § 2106.04(a)(2)).
- “grouping processing of assigning a group number which is selected in order of magnitude of the representative value to the data in each of the unit periods” (these are mathematical concepts - see MPEP § 2106.04(a)(2)).
Limitations under prong 2:
“output processing of outputting a screen of a graph…” (gathering and presenting the calculated data) is insignificant extra-solution activity to the judicial exception, as mere data gathering (See MPEP 2106.05(g)).
Step 2B – not significant more.
Thus, the recited “Method” is an abstract idea in that it is not tied to a particular machine or apparatus. Furthermore, the additional element of using a computer, sensor as a tool to perform the recited steps amounts to no more than mere instructions to apply the abstract idea using a generic computer component. Mere instructions to apply a judicial exception using a generic computer component cannot provide an inventive concept.
Accordingly, the recited Method is non-statutory subject matter.
Claim 13 is rejected along the same rationale as claim 12, as is a computer readable medium with the instructions as provided in claim 12.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 7, 11, 12 and 13 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tamaki (US 20130132000).
In regards to claim 7, 12 and 13, Tamaki discloses a diagnosis device for diagnosing a status of equipment in which a plurality of processes are present in one operation cycle, the diagnosis device comprising: a memory which stores time series data of a plurality of sensors indicative of the status of the equipment (see abstract and at least para 49: “The CPU of the abnormality monitoring-diagnosing device 100 (hereinafter, simply referred to as the CPU) executes a process as a condition-mode transition point detecting process unit 21 every time the sensor data is collected by the sensor-data collecting process unit 1 and is stored in the sensor data DB 11, or for each predetermined time cycle. That is, the CPU detects a condition-mode transition point from the pieces of sensor data stored in a time-series manner (step S1). Data on the detected condition-mode transition point is stored in a condition-mode transition point DB 51 in the memory 5.”); and a processor which determines change of the status of the equipment from the time series data, wherein the processor executes: calculation processing of dividing data from a start to an end of a specific operation cycle in the time series data for each of unit periods and calculating a representative value indicative of a relative relationship of data in each unit period to data in all periods in the specific operation cycle for each of the unit periods (see at least para 17, 130: “In the estimation of a defect cause successively carried out after the abnormality detection, the abnormality monitoring-diagnosing device 100 builds, from the pieces of sensor data of the data item condition mode by condition mode, the link model between the data items in the group for each group, and builds the link model between the groups relative to the representative data in each group. Hence, the abnormality cause of the data item where the abnormality is detected can be traced at fast speed, and the fundamental cause (defective part) can be diagnosed promptly”); grouping processing of assigning a group number which is selected in order of magnitude of the representative value to the data in each of the unit periods (see at least para 82: “The data-item group sorting process is a process by the data-item group sorting process unit 23, and is a process of sorting the data items of the sensor data into a plurality of groups. That is, this is a process of, among the data items of the plural pieces of sensor data, collecting ones having a large mutual connection in the behavior of the sensor data identified by that data item and grouping those”); and output processing of outputting a screen of a graph in which a plurality of graphs which are obtained by plotting the group number assigned to the data in each of the unit periods in chronological order of each of the unit periods and correspond to a plurality of operation cycles are shown so as to overlap each other (see FIG. 11 and at least para 115-116: “The process of building such link models can be realized by, for example, applying a concept of a graphical model disclosed in Non-patent literature 1. According to such a graphical model, the presence/absence of a causal association can be determined from the correlation coefficient between the pieces of sensor data of the two data items, and the direction of cause and result can be determined from time anticipation information for a change point occurrence of behaviors of both data items. That is, data item which has changed in advance in time is determined as a "cause" and the data item which starts changing subsequently is determined as a "result". When the causal association and the direction of cause and result between the two data items are obtained for between all data items in the group, a link model between the data items in the group can be built”).
In regards to claim 11, Tamaki discloses wherein each of the plurality of sensors is a vibration sensor, and the time series data is data of a vibration level of the equipment (see abstract and at least para 14, 17, 133: sensor data and application including vibration detection).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 10 is rejected under 35 U.S.C. 103 as being unpatentable over Tamaki (US 20130132000).
In regard to claim 10, Tamaki doesn’t specifically teach wherein the processor determines that the representative values of pieces of data in a specific unit period which is one of the individual unit periods and pieces of data in another specific unit period whose ranges between minimum values and maximum values of differences of magnitude of dispersion of the pieces of data overlap each other are at a same level, and assigns a same group number to each of the pieces of data of the unit periods in the grouping processing.
However Tamaki teaches grouping and cluster analysis using similar quantity and relationship and mutual connections between behaviors and values (see at least para 17, 82-99, 103-104 for examples and calculation for sorting into groups. Para 17 mentions “a data-item group sorting process of sorting data items identifying the time-series physical quantities of the plurality of components into a plurality of groups; and an abnormality determining process (the transient-condition abnormality determining process and the steady-condition abnormality determining process in the embodiment) of determining an abnormality for each sorted group based on the time-series physical quantity of the component identified by the data item belonging to that group and statistical data on the time-series physical quantity of the component, and the third process unit being configured to execute: a link-model building process of building, for each sorted group, a link model including an inter-data-item link model representing a dependency relation between the time-series physical quantities of the components identified by the data item belonging to that group, and an inter-group link model representing a dependency relation between representative values of the groups”. Para 82: “this is a process of, among the data items of the plural pieces of sensor data, collecting ones having a large mutual connection in the behavior of the sensor data identified by that data item and grouping those”. Also Para 103: “FIGS. 8A to 8C illustrate an example case in which transient-condition multivariable data and steady-condition multivariable data is generated for the data items SS11 to SS13 in the group G1, but the same is true of the other groups.”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to use these teachings of Tamaki for grouping and analysis using similar quantity and relationship and mutual connections between behaviors and values, since it allows for the identification of hidden or similar patterns and improves the analysis of future trends with similar values or relationships.
Allowable Subject Matter
Claims 8-9 are objected to as being dependent upon a rejected base claim, but are allowable over the prior art.
Claim 1-6 are allowed over the prior art.
The following is an examiner’s statement of reasons for allowance of claims 1-6:
None of these references taken either alone or in combination in the prior art of record teach all the limitations as provided by the claim language of the independent claims. It is for these reasons that the applicant’s invention defines over the prior art of record.
The closes prior art of record are:
Natsumeda (US 20190265088): teaches analysis apparatus includes a history information generation part generating, based on sensor values output by a plurality of sensors provided in a system, history information representing in a time series whether or not the sensor value(s) output by each of the plurality of sensors is abnormal, and/or whether or not a relationship between the sensor values output by different sensors is abnormal, a clustering part classifying the plurality of sensors into a plurality of groups, based on the history information, and a cluster hierarchy structuring part structuring a hierarchy of the plurality of groups by using causality information that indicates causality between the sensor values output by the plurality of sensors.
Sekine (US 11200529): teaches detects an abnormality based of signals obtained from equipment (sensors). A first divider that divides time series data measured at a normal time into periodic data in period units; a reference data generator that generates reference data based on a plurality of pieces of periodic data; an allowable error calculator that calculates an allowable error of a divergence value, based on the time series data of the normal time and the reference data the divergence value indicates a degree of divergence from the reference data; a divergence value calculator that calculates a divergence value between time series data for detection, the time series data for detection is a detection object for detection of a non-normal state; and a detector that detects the non-normal state in accordance with whether or not the divergence value is within a range of allowable errors.
Nakatani (US 20200117652): teaches an analysis device for enabling correction of variation of measurement data resultant from aging degradation of measurement device without use of information about sample subjected to measurement, measurement conditions and raw measurement data in analysis system. A case data set storage unit includes a plurality of case data sets including difference data representing, a variation from measurement data taken at an initial state to measurement data taken at a plurality of points of time for the same sample under the same measurement condition. An aging degradation estimation unit uses these case data sets to output difference data representing an estimate value of a variation from the measurement data taken at the initial state to measurement data taken, by a measurement device, at or after a first elapsed time, based on difference data representing a variation from the measurement data taken at the initial state to measurement data taken at a plurality of points of time that precede the first elapsed time. An aging degradation correction unit corrects the measurement data taken at or after the first elapsed time, based on the output difference data.
Kitajima et al. (US 11308181) teaches a first time-series data set indicating first measured values obtained by a first device and a second time-series data set indicating second measured values obtained by a second device are obtained. First alignment is performed to convert the positions in the time domain of the first measured values belonging to a second period, based on the first measured values belonging to a first period. Second alignment is performed to convert the positions in the time domain of the second measured values belonging to the second period, based on a relationship between positions before and after the conversion. Correlation analysis is performed between third and fourth time-series data sets respectively obtained by the first and second alignment. The existence or absence of an inclusion relationship in which the second measured values contain a component of the first measured values is determined based on the correlation analysis result.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARIO M VELEZ-LOPEZ whose telephone number is (571)270-7971. The examiner can normally be reached on M-F 10:30am-5:30pm ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott Baderman, can be reached at telephone number 571-272-3644. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARIO M VELEZ-LOPEZ/
Examiner, Art Unit 2118
/SCOTT T BADERMAN/Supervisory Patent Examiner, Art Unit 2118
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