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 .
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 2, 6, 8,, 19, 20 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.
Claims 2, 8, 12, 15, and 19 all recite the limitation “position data which is differentiated to produce servo velocity data” These claims are indefinite because position data must be time-series in order to differentiate to produce velocity data because velocity is the rate of change of position with respect to time and that requires at least two position values at points in times. Paragraph [0034] in the specification, states the position data is time-series when differentiating to produce velocity but position data in the claims do not specify if it is time series. The independent claims that these claims are depended on, do refer to collecting data over a time frame of during operation but the amount of data and points in times are not specified. A person of ordinary skill in the art could realistically interpret position data as a single value that would then not be able to differentiate to velocity. For examination purposes, the position data will be treated as multiple values over time.
Claim 9, 13, and 20 are also rejected under 35 USC 112 (b) by virtue of their dependency on claims 8, 12, and 19.
Claim 6 recites the limitation “and at least one of the predefined threshold values is in a range of 1.5-3.0.” Claim 6 is indefinite as the specific predefined threshold value range stated has no associated support in the specification. The values in the range also do not have any units so it would be difficult for one of ordinary skill in the art to give meaning to these values. The only mention of these specific values in the specification is in paragraph [0045] “The sensorless tool health monitoring system of the present disclosure, using the tool breakage indicator, has also been demonstrated to be effective in monitoring the health of small tools – such as cutting tools having a diameter in a range of about 1.5 mm to 3 mm.” The values have meaning and units but is only in reference to a range of small cutting tool diameters where the tool breakage indicator can also effectively monitor and is not related to range of threshold values. For examination purposes, these numbers have been interpreted as exceeding any threshold values.
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.
Claims 1, 3-7, 11, 14, and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (CN-114800040-A) in view of Soma (JP-2004351597-A).
Regarding claim 1, Zhang teaches in paragraphs [n0014], [n0015], [n0017], and [n0021]
a method for sensorless tool health monitoring, said method comprising:
[n0014] A method and system for {a method for} monitoring tool wear {tool health monitoring} by linking process and condition data {sensorless} includes the following steps (said method comprising):
collecting data by a machine controller, for a machine tool parameter during machining operations;
[n0015] Collect status data {collecting data} during high-frequency machining {during machining operations} and process data read from the CNC system of the machine tool; {by a machine controller,}
[n0017] The collected status data is segmented based on the tool name, and each segment is then categorized into the file corresponding to the tool. {for a machine tool parameter}
comparing the tool breakage indicator to one or more predefined threshold values; and
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold is reached {comparing the tool breakage indicator to one or more predefined threshold values} twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions.
taking remedial action, by the machine controller, when the tool breakage indicator exceeds one or more of the predefined threshold values.
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm {taking remedial action, by the machine controller} is triggered when the failure threshold is reached twice consecutively {when the tool breakage indicator exceeds one or more of the predefined threshold values} . The time interval between the two failure thresholds can be set according to the on-site working conditions.
Zhang fails to teach converting the data to a frequency domain to produce a frequency response spectrum;
calculating a tool breakage indicator as a magnitude of the frequency response spectrum at a spindle frequency divided by a magnitude of a reference frequency response spectrum at the spindle frequency;
However, Soma teaches in paragraph [0024], [0033], [0034]
converting the data to a frequency domain to produce a frequency response spectrum;
[0034] In the present invention, it is necessary to discriminate the obtained signal into frequencies {converting the data to a frequency domain} and specify the vibration frequency, and the signal is discriminated into frequencies by processing such as a band-pass filter or fast Fourier transform. {to produce a frequency response spectrum}
calculating a tool breakage indicator as a magnitude of the frequency response spectrum at a spindle frequency divided by a magnitude of a reference frequency response spectrum at the spindle frequency;
[0024] More specifically, each of the cylindrical workpieces fixed by the fixing jig has its own natural frequency. On the other hand, the cutting tool (turning tool) imparts vibration to the cylindrical workpiece during cutting, and the vibration frequency imparted to the cylindrical workpiece coincides with the spindle rotational speed. {a spindle frequency} When the integral multiple of the spindle rotational speed and the integral multiple of the natural frequency of the cylindrical workpiece coincide with each other, the cylindrical workpiece may resonate at the oscillation frequency S (Hz) to cause larger vibration. Accordingly, the transmission of the sound wave, and the period and depth of the cutting process vary, and chatter marks are formed on the cylindrical workpiece, and when an electrophotographic substrate is produced using this substrate, defects occur. The oscillation frequency of the oscillation is specific to each cylindrical workpiece, and if cylindrical workpieces of the same material and shape are used, the oscillation of the same frequency is transmitted each time. Therefore, the occurrence of chattering can be prevented by detecting a signal indicating the occurrence of resonance and shifting the rotational speed of the cylindrical workpiece or the cutting tool to a rotational speed that does not coincide with the natural frequency of the cylindrical workpiece. {Reason to combine references}
[0033] Examples of a method of automatically detecting and determining the occurrence of an abnormality include a method of detecting the occurrence of an abnormality {calculating a tool breakage indicator} based on the magnitude of the signal obtained by the detection means, and a method of discriminating the obtained signal into frequencies and determining the occurrence of an abnormality based on the magnitude of the signal of a specific frequency component or the ratio of the magnitudes. {as a magnitude of the frequency response spectrum divided by a magnitude of a reference frequency response spectrum} In order to selectively detect a chattering sound from various ambient sounds, it is preferable to make a determination based on the magnitude of a signal of a specific frequency component (at a spindle frequency} or the ratio of the magnitudes.
Zhang and Soma are considered to be analogous to the claimed invention because they are in the same field of endeavor of machine cutting tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang to incorporate the teachings of Soma by replacing the index calculation with the magnitude at a specific frequency being the vibration frequency coinciding with spindle rotational speed. Doing so would be in order to detect an occurrence of resonance to detect chatter which relates to wear.
Regarding claim 3, Zhang and Soma further teach the method according to Claim 1.
Zhang further teaches in paragraph [n0015] and [n0021]
wherein the data for the machine tool parameter is collected for a predefined time period, and collecting the data and calculating the tool breakage indicator is repeated periodically during the machining operation.
[n0015] Collect status data during high-frequency machining {wherein the data for the machine tool parameter is collected for a predefined time period} and process data read from the CNC system of the machine tool;
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold is reached twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions. { and collecting the data and calculating the tool breakage indicator is repeated periodically during the machining operation.}
Regarding claim 4, Zhang and Soma teach the method according to Claim 1
Soma further teaches in paragraph [0024]
wherein the spindle frequency is equal to a spindle rotational velocity in revolutions per second.
[0024] More specifically, each of the cylindrical workpieces fixed by the fixing jig has its own natural frequency. On the other hand, the cutting tool (turning tool) imparts vibration to the cylindrical workpiece during cutting, and the vibration frequency imparted to the cylindrical workpiece coincides with the spindle rotational speed. {vibration frequency = spindle frequency, wherein the spindle frequency is equal to a spindle rotational velocity in revolutions per second} When the integral multiple of the spindle rotational speed and the integral multiple of the natural frequency of the cylindrical workpiece coincide with each other, the cylindrical workpiece may resonate at the oscillation frequency S (Hz) {in Hz = in revolutions per second} to cause larger vibration. Accordingly, the transmission of the sound wave, and the period and depth of the cutting process vary, and chatter marks are formed on the cylindrical workpiece, and when an electrophotographic substrate is produced using this substrate, defects occur. The oscillation frequency of the oscillation is specific to each cylindrical workpiece, and if cylindrical workpieces of the same material and shape are used, the oscillation of the same frequency is transmitted each time. Therefore, the occurrence of chattering can be prevented by detecting a signal indicating the occurrence of resonance and shifting the rotational speed of the cylindrical workpiece or the cutting tool to a rotational speed that does not coincide with the natural frequency of the cylindrical workpiece.
Regarding claim 5, Zhang and Soma teach the method according to Claim 1
Zhang further teaches in paragraph [n0004]
wherein the reference frequency response spectrum was produced from a reference dataset for the machine tool parameter during the machining operation when a cutting tool was new.
[n0004] Many mature commercial application software programs, such as MARPOSS ARTIS from Italy, KOMETToolScope from Germany, and Sandvik Process Control, have implemented bandwidth monitoring strategies to monitor tool anomalies in high-volume cutting scenarios. This monitoring method requires first using the cutting status data of normal tools as a reference curve {normal can be interpreted as new; wherein the reference frequency response spectrum was produced from a reference dataset for the machine tool parameter during the machining operation when a cutting tool was new} , then using worn tools to obtain the machining curve, and finally setting alarm upper and lower limits based on the machining data of new and worn tools. The upper limit is used to monitor tool breakage caused by factors such as chipping and workpiece hard spots, while the lower limit is used to detect tool breakage, workpiece loss, or repeated machining.
Regarding claim 6, Zhang and Soma teach the method according to Claim 1
Zhang further teaches in paragraph [n0041] and [n0048]
wherein the tool breakage indicator indicates a health of a cutting tool, where a higher value of the tool breakage indicator indicates a poorer health of the cutting tool and at least one of the predefined threshold values is in a range of 1.5-3.0
[n0041] Furthermore, feature fusion: features are extracted from the cutting state data and normalized to eliminate the difference in magnitude between features; after normalization, the feature reflecting tool wear degradation { wherein the tool breakage indicator indicates a health of a cutting tool,} starts from 1 and gradually increases. When a new tool is cutting, the index fluctuates around 1, and as the degree of tool wear increases, the index gradually deviates from 1 { where a higher value of the tool breakage indicator indicates a poorer health of the cutting tool}; index fusion and dimensionality reduction are achieved by calculating the root mean square value (RMS) of the wear features.
[n0048] The relationship between the increased cutting force and monitoring indicators during the wear evolution of the tool under real cutting parameters was calibrated through experiments; {(also see 112(b) rejection) and at least one of the predefined threshold values is in a range of 1.5-3.0} when different cutting parameters are selected for cutting, the threshold is reasonably determined in real time based on the allowable cutting force of tool wear.
Regarding claim 7, Zhang and Soma teach the method according to Claim 1
Zhang further teaches in paragraphs [n0021], [n0071], and [n0088]
further comprising collecting data for at least one other machine tool parameter during the machining operation,
for the at least one other machine tool parameter,
[n0071] The internal data of the CNC system includes spindle power, spindle current, spindle torque, which reflect the spindle cutting load, as well as X/Y/Z coordinates that reflect changes in tool position.
In addition, there is process information such as cutting parameters, tool name, and program name that reflects the cutting process. { further comprising collecting data for at least one other machine tool parameter during the machining operation} { for the at least one other machine tool parameter}
comparing the tool breakage indicator
and taking remedial action
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold {and taking remedial action} is reached {comparing the tool breakage indicator} twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions.
to one or more other predefined threshold values,
when any of the tool breakage indicators exceeds any of its associated threshold values.
[n0088] Step (5), failure threshold acquisition: the normalization process based on the features in step (4) simplifies the selection of the tool wear monitoring threshold. For processes with different machining accuracy requirements, different levels of thresholds can be set for the monitoring threshold of the cutting tool. {to one or more other predefined thresholds} { when any of the tool breakage indicators exceeds any of its associated threshold values.} Taking the surface finish of a machined part as an example, the method for calculating the failure threshold is given below:
Soma further teaches in paragraphs [0033]
calculating the tool breakage indicator
[0033] Examples of a method of automatically detecting and determining the occurrence of an abnormality include a method of detecting the occurrence of an abnormality {calculating a tool breakage indicator} based on the magnitude of the signal obtained by the detection means, and a method of discriminating the obtained signal into frequencies and determining the occurrence of an abnormality based on the magnitude of the signal of a specific frequency component or the ratio of the magnitudes. In order to selectively detect a chattering sound from various ambient sounds, it is preferable to make a determination based on the magnitude of a signal of a specific frequency component (at a spindle frequency} or the ratio of the magnitudes.
Regarding claim 11, Zhang teaches in paragraph [n0014], [n0071],
A method for sensorless tool health monitoring, said method comprising:
[n0014] A method and system for {a method for} monitoring tool wear {tool health monitoring} by linking process and condition data {sensorless} includes the following steps (said method comprising):
collecting data, by a machine controller, for a plurality of machine tool parameters during machining operations;
[n0071] The internal data of the CNC system {collecting data, by a machine controller,} includes spindle power, spindle current, spindle torque, which reflect the spindle cutting load, as well as X/Y/Z coordinates that reflect changes in tool position. In addition, there is process information such as cutting parameters, tool name, and program name that reflects the cutting process. {for a plurality of machine tool parameters during machining operations;}
converting the data to a frequency domain to produce a frequency response spectrum for each of the parameters;
[0034] In the present invention, it is necessary to discriminate the obtained signal {for each of the parameters;} into frequencies {converting the data to a frequency domain} and specify the vibration frequency, and the signal is discriminated into frequencies by processing such as a band-pass filter or fast Fourier transform. {to produce a frequency response spectrum}
where the reference frequency response spectrum was produced from a reference dataset for the machine tool parameter during the machining operation when a cutting tool was new.
[n0004] Many mature commercial application software programs, such as MARPOSS ARTIS from Italy, KOMETToolScope from Germany, and Sandvik Process Control, have implemented bandwidth monitoring strategies to monitor tool anomalies in high-volume cutting scenarios. This monitoring method requires first using the cutting status data of normal tools as a reference curve {normal can be interpreted as new; wherein the reference frequency response spectrum was produced from a reference dataset for the machine tool parameter during the machining operation when a cutting tool was new} , then using worn tools to obtain the machining curve, and finally setting alarm upper and lower limits based on the machining data of new and worn tools. The upper limit is used to monitor tool breakage caused by factors such as chipping and workpiece hard spots, while the lower limit is used to detect tool breakage, workpiece loss, or repeated machining.
comparing the tool breakage indicators to one or more predefined threshold values; and
taking remedial action, by the machine controller, when any of the tool breakage indicator exceeds any of the predefined threshold values.
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold {Taking remedial action, by the machine controller} is reached {comparing the tool breakage indicator} twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions.
[n0088] Step (5), failure threshold acquisition: the normalization process based on the features in step (4) simplifies the selection of the tool wear monitoring threshold. For processes with different machining accuracy requirements, different levels of thresholds can be set for the monitoring threshold of the cutting tool. {to one or more other predefined thresholds; and} {when any of the tool breakage indicators exceeds any of its associated threshold values.} Taking the surface finish of a machined part as an example, the method for calculating the failure threshold is given below:
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold {taking remedial action, by the machine controller} is reached {comparing the tool breakage indicator} twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions.
Zhang fails to teach calculating a tool breakage indicator, for each of the parameters, as a magnitude of the frequency response spectrum at a spindle frequency divided by a magnitude of a reference frequency response spectrum at the spindle frequency,
However, Soma teaches in paragraph [0024] and [0033]
calculating a tool breakage indicator, for each of the parameters,
as a magnitude of the frequency response spectrum at a spindle frequency divided by a magnitude of a reference frequency response spectrum at the spindle frequency,
[0024] More specifically, each of the cylindrical workpieces fixed by the fixing jig has its own natural frequency. On the other hand, the cutting tool (turning tool) imparts vibration to the cylindrical workpiece during cutting, and the vibration frequency imparted to the cylindrical workpiece coincides with the spindle rotational speed. {a spindle frequency} When the integral multiple of the spindle rotational speed and the integral multiple of the natural frequency of the cylindrical workpiece coincide with each other, the cylindrical workpiece may resonate at the oscillation frequency S (Hz) to cause larger vibration. Accordingly, the transmission of the sound wave, and the period and depth of the cutting process vary, and chatter marks are formed on the cylindrical workpiece, and when an electrophotographic substrate is produced using this substrate, defects occur. The oscillation frequency of the oscillation is specific to each cylindrical workpiece, and if cylindrical workpieces of the same material and shape are used, the oscillation of the same frequency is transmitted each time. Therefore, the occurrence of chattering can be prevented by detecting a signal indicating the occurrence of resonance and shifting the rotational speed of the cylindrical workpiece or the cutting tool to a rotational speed that does not coincide with the natural frequency of the cylindrical workpiece. {Reason to combine references}
[0033] Examples of a method of automatically detecting and determining the occurrence of an abnormality include a method of detecting the occurrence of an abnormality {calculating a tool breakage indicator, for each of the parameters,} based on the magnitude of the signal obtained by the detection means, and a method of discriminating the obtained signal into frequencies and determining the occurrence of an abnormality based on the magnitude of the signal of a specific frequency component or the ratio of the magnitudes. {as a magnitude of the frequency response spectrum divided by a magnitude of a reference frequency response spectrum} In order to selectively detect a chattering sound from various ambient sounds, it is preferable to make a determination based on the magnitude of a signal of a specific frequency component (at a spindle frequency} or the ratio of the magnitudes.
Zhang and Soma are considered to be analogous to the claimed invention because they are in the same field of endeavor of machine cutting tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang to incorporate the teachings of Soma by replacing the index calculation with the magnitude at a specific frequency being the vibration frequency coinciding with spindle rotational speed. It would have also been obvious to one of ordinary skill in the art to do this method for different machine tool parameters at the same time as the CNC collects different types of data at the same time and different thresholds for these parameters can be determined so the actions of converting, calculating, and comparing does not change. Doing so would be in order to detect an occurrence of resonance to detect chatter which relates to wear.
Regarding claim 14, Zhang teaches in Figure 1 and paragraphs [n0014], [n0015], [n0017], [n0021], and [n0110]
A sensorless machine tool health monitoring system, said system comprising:
[n0014] A method and system for monitoring tool wear {machine tool health monitoring system} by linking process and condition data {A sensorless} includes the following steps (said system comprising):
a machine tool configured for performing an operation on a workpiece; and
Figure 1: {a machine tool configured for performing an operation on a work piece is shown as the CNC machine and the zoomed in cutting tool on a piece}
a computing device in communication with the machine tool, said computing device being configured to monitoring health of a cutting tool by performing steps including;
Figure 1: {a computing device in communication with the machine tool is shown as the screen and input pad shown connected to the CNC machine}
[n0110] In another embodiment of the present invention, a computer device is provided {a computing device}, the computer device including a data acquisition port, a processor and a memory, the memory being used to store a computer program, the computer program including program instructions, and the processor being used to execute the program instructions stored in the computer storage medium.
The processor may be a Central Processing Unit (CPU), or other general purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in a computer storage medium to realize the corresponding method flow or corresponding function. The processor described in this embodiment of the invention can be used for the operation of a tool wear monitoring method based on process-state data correlation. { said computing device being configured to monitoring health of a cutting tool by performing steps including}
collecting data for a machine tool parameter during the operation;
[n0015] Collect status data {collecting data} during high-frequency machining {during operations} and process data read from the CNC system of the machine tool;
[n0017] The collected status data is segmented based on the tool name, and each segment is then categorized into the file corresponding to the tool. {for a machine tool parameter}
comparing the tool breakage indicator to one or more predefined threshold values; and
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold is reached {comparing the tool breakage indicator to one or more predefined threshold values; and} twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions.
taking remedial action, including issuing an alert or stopping the operation by the machine tool, when the tool breakage indicator exceeds one or more of the predefined threshold values.
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm {taking remedial action, including issuing an alert or stopping the operation by the machine tool} is triggered when the failure threshold is reached twice consecutively {when the tool breakage indicator exceeds one or more of the predefined threshold values} . The time interval between the two failure thresholds can be set according to the on-site working conditions.
Zhang fails to teach converting the data to a frequency domain to produce a frequency response spectrum;
calculating a tool breakage indicator as a magnitude of the frequency response spectrum at a spindle frequency divided by a magnitude of a reference frequency response spectrum at the spindle frequency;
However, Soma teaches in paragraph [0024], [0033], [0034]
converting the data to a frequency domain to produce a frequency response spectrum;
[0034] In the present invention, it is necessary to discriminate the obtained signal into frequencies {converting the data to a frequency domain} and specify the vibration frequency, and the signal is discriminated into frequencies by processing such as a band-pass filter or fast Fourier transform. {to produce a frequency response spectrum}
calculating a tool breakage indicator as a magnitude of the frequency response spectrum at a spindle frequency divided by a magnitude of a reference frequency response spectrum at the spindle frequency;
[0024] More specifically, each of the cylindrical workpieces fixed by the fixing jig has its own natural frequency. On the other hand, the cutting tool (turning tool) imparts vibration to the cylindrical workpiece during cutting, and the vibration frequency imparted to the cylindrical workpiece coincides with the spindle rotational speed. {a spindle frequency} When the integral multiple of the spindle rotational speed and the integral multiple of the natural frequency of the cylindrical workpiece coincide with each other, the cylindrical workpiece may resonate at the oscillation frequency S (Hz) to cause larger vibration. Accordingly, the transmission of the sound wave, and the period and depth of the cutting process vary, and chatter marks are formed on the cylindrical workpiece, and when an electrophotographic substrate is produced using this substrate, defects occur. The oscillation frequency of the oscillation is specific to each cylindrical workpiece, and if cylindrical workpieces of the same material and shape are used, the oscillation of the same frequency is transmitted each time. Therefore, the occurrence of chattering can be prevented by detecting a signal indicating the occurrence of resonance and shifting the rotational speed of the cylindrical workpiece or the cutting tool to a rotational speed that does not coincide with the natural frequency of the cylindrical workpiece. {Reason to combine references}
[0033] Examples of a method of automatically detecting and determining the occurrence of an abnormality include a method of detecting the occurrence of an abnormality {calculating a tool breakage indicator} based on the magnitude of the signal obtained by the detection means, and a method of discriminating the obtained signal into frequencies and determining the occurrence of an abnormality based on the magnitude of the signal of a specific frequency component or the ratio of the magnitudes. {as a magnitude of the frequency response spectrum divided by a magnitude of a reference frequency response spectrum} In order to selectively detect a chattering sound from various ambient sounds, it is preferable to make a determination based on the magnitude of a signal of a specific frequency component (at a spindle frequency} or the ratio of the magnitudes.
Zhang and Soma are considered to be analogous to the claimed invention because they are in the same field of endeavor of machine cutting tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang to incorporate the teachings of Soma by replacing the index calculation with the magnitude at a specific frequency being the vibration frequency coinciding with spindle rotational speed in the method to be performed on the computer. Doing so would be in order to detect an occurrence of resonance to detect chatter which relates to wear.
Regarding claim 16, Zhang and Soma teach the system according to Claim 14
Zhang further teaches in paragraphs [n0015] and [n0021]
wherein the data for the machine tool parameter is collected for a predefined time period, and collecting the data and calculating the tool breakage indicator is repeated periodically during the operation.
[n0015] Collect status data during high-frequency machining {wherein the data for the machine tool parameter is collected for a predefined time period} and process data read from the CNC system of the machine tool;
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold is reached twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions. { and collecting the data and calculating the tool breakage indicator is repeated periodically during the machining operation.}
Regarding claim 17, Zhang and Soma teach the system according to Claim 14
Zhang further teaches in paragraph [n0004]
wherein the reference frequency response spectrum was produced from a reference dataset for the machine tool parameter during the operation when the cutting tool was new.
[n0004] Many mature commercial application software programs, such as MARPOSS ARTIS from Italy, KOMETToolScope from Germany, and Sandvik Process Control, have implemented bandwidth monitoring strategies to monitor tool anomalies in high-volume cutting scenarios. This monitoring method requires first using the cutting status data of normal tools as a reference curve {normal can be interpreted as new; wherein the reference frequency response spectrum was produced from a reference dataset for the machine tool parameter during the machining operation when a cutting tool was new} , then using worn tools to obtain the machining curve, and finally setting alarm upper and lower limits based on the machining data of new and worn tools. The upper limit is used to monitor tool breakage caused by factors such as chipping and workpiece hard spots, while the lower limit is used to detect tool breakage, workpiece loss, or repeated machining.
Regarding claim 18, Zhang and Soma teach the system according to Claim 14
Zhang further teaches in paragraphs [n0021], [n0071], and [n0088]
further comprising collecting data for at least one other machine tool parameter during the operation,
for the at least one other machine tool parameter,
[n0071] The internal data of the CNC system includes spindle power, spindle current, spindle torque, which reflect the spindle cutting load, as well as X/Y/Z coordinates that reflect changes in tool position.
In addition, there is process information such as cutting parameters, tool name, and program name that reflects the cutting process. { further comprising collecting data for at least one other machine tool parameter during the operation} { for the at least one other machine tool parameter}
comparing the tool breakage indicator
and taking remedial action
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold {and taking remedial action} is reached {comparing the tool breakage indicator} twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions.
to one or more other predefined threshold values,
when any of the tool breakage indicators exceeds any of its associated threshold values.
[n0088] Step (5), failure threshold acquisition: the normalization process based on the features in step (4) simplifies the selection of the tool wear monitoring threshold. For processes with different machining accuracy requirements, different levels of thresholds can be set for the monitoring threshold of the cutting tool. {to one or more other predefined thresholds} { when any of the tool breakage indicators exceeds any of its associated threshold values.} Taking the surface finish of a machined part as an example, the method for calculating the failure threshold is given below:
Soma further teaches in paragraphs [0033]
calculating the tool breakage indicator
[0033] Examples of a method of automatically detecting and determining the occurrence of an abnormality include a method of detecting the occurrence of an abnormality {calculating a tool breakage indicator} based on the magnitude of the signal obtained by the detection means, and a method of discriminating the obtained signal into frequencies and determining the occurrence of an abnormality based on the magnitude of the signal of a specific frequency component or the ratio of the magnitudes. In order to selectively detect a chattering sound from various ambient sounds, it is preferable to make a determination based on the magnitude of a signal of a specific frequency component (at a spindle frequency} or the ratio of the magnitudes.
Claim 2, 8, 9, 12, 13, 15, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (CN-114800040-A) in view of Soma (JP-2004351597-A) in view of Tsuneki (US-20230324885-A1)
Regarding claim 2, Zhang and Soma teach the method according to Claim 1.
Zhang further teaches in paragraph [n0071]
wherein the machine tool parameter is spindle torque command data,
[n0071] The internal data of the CNC system includes {wherein the machine tool parameter is} spindle power, spindle current, spindle torque, which reflect the spindle cutting load, {spindle torque command data} as well as X/Y/Z coordinates that reflect changes in tool position.
In addition, there is process information such as cutting parameters, tool name, and program name that reflects the cutting process. {Reasoning for combining references}
Zhang and Soma fail to teach or the machine tool parameter is a tool positioning servo motor position data which is differentiated to produce servo velocity data before converting to the frequency domain.
However, Tsuneki teaches in paragraph [0034]
or the machine tool parameter is a tool positioning servo motor position data which is differentiated to produce servo velocity data before converting to the frequency domain.
[0034] The servo control unit 100 inputs the detection speed or the differentiation { which is differentiated to produce servo velocity data} of the detection position { or the machine tool parameter is a tool positioning servo motor position data} to the frequency characteristic measurement unit 300. The frequency characteristic measurement unit 300 measures and outputs, to the control assistance unit 400, the frequency characteristics of the amplitude ratio (input/output gain) between the speed command to be the input signal and the output signal, and the phase shift. { before converting to the frequency domain.}
Zhang, Soma, and Tsuneki are considered to be analogous to the claimed invention because they are in the same field of endeavor of machine tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang and Soma to incorporate the teachings of Tsuneki by using the position data in Zhang and differentiating it to produce velocity before converting to the frequency, as shown in Tsuneki and converting to the frequency as in claim 1 is shown in Soma. Doing so in order to get velocity data straight from data available in the controller.
Regarding claim 8, Zhang and Soma teach the method according to Claim 7 wherein individual tool breakage indicators are calculated
Zhang further teaches in paragraph [n0071]
wherein the machine tool parameter is spindle torque command data and position data
[n0071] The internal data of the CNC system includes { wherein the machine tool parameter} spindle power, spindle current, spindle torque, which reflect the spindle cutting load, {is spindle torque command data} as well as X/Y/Z coordinates that reflect changes in tool position. {and position data}
In addition, there is process information such as cutting parameters, tool name, and program name that reflects the cutting process. {Reasoning for combining references}
Zhang and Soma fail to teach for at least one tool positioning servo motor, where the position data is differentiated to produce velocity data before converting to the frequency domain.
However, Tsuneki teaches in paragraph [0034]
for at least one tool positioning servo motor, where the position data is differentiated to produce velocity data before converting to the frequency domain.
[0034] The servo control unit 100 inputs the detection speed or the differentiation { is differentiated to produce servo velocity data} of the detection position { for at least one tool positioning servo motor, where the position data} to the frequency characteristic measurement unit 300. The frequency characteristic measurement unit 300 measures and outputs, to the control assistance unit 400, the frequency characteristics of the amplitude ratio (input/output gain) between the speed command to be the input signal and the output signal, and the phase shift. { before converting to the frequency domain.}
Zhang, Soma, and Tsuneki are considered to be analogous to the claimed invention because they are in the same field of endeavor of machine tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang and Soma to incorporate the teachings of Tsuneki by using the position data in Zhang and differentiating it to produce velocity before converting to the frequency, as shown in Tsuneki and converting to the frequency as in claim 1 is shown in Soma. Doing so in order to get velocity data straight from data available in the controller.
Regarding claim 9, Zhang Soma, and Tsuneki teach the method according to Claim 8
Zhang further teaches in paragraph [n0019], [n0020], [n0057].
further comprising computing a composite tool breakage indicator using a square-root-of-the-sum-of-the-squares calculation including each of the individual tool breakage indicators, and taking remedial action when the composite tool breakage indicator exceeds an associated threshold value.
[n0019] Wear characteristics are obtained by decomposing the high-frequency machine spindle current signal.
[n0020] The indexes are fused and dimensionality reduced by calculating {further comprising computing a composite tool breakage indicator} the root mean square value of wear characteristics; { using a square-root-of-the-sum-of-the-squares calculation including each of the individual tool breakage indicators}
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold is reached twice consecutively. { and taking remedial action when the composite tool breakage indicator exceeds an associated threshold value.} The time interval between the two failure thresholds can be set according to the on-site working conditions.
Regarding claim 12, Zhang and Soma teach the method according to Claim 11
Zhang further teaches in paragraph [n0071]
wherein the plurality of machine tool parameters includes spindle torque command data and position data,
[n0071] The internal data of the CNC system includes { wherein the plurality of machine tool parameters includes } spindle power, spindle current, spindle torque, which reflect the spindle cutting load, {spindle torque command data} as well as X/Y/Z coordinates that reflect changes in tool position. {and position data,} In addition, there is process information such as cutting parameters, tool name, and program name that reflects the cutting process. {Reasoning for combining references}
Zhang and Soma fail to teach for at least one tool positioning servo motor, where the position data is differentiated to produce velocity data before converting to the frequency domain.
However, Tsuneki teaches in paragraph [0034]
for at least one tool positioning servo motor, where the position data is differentiated to produce velocity data before converting to the frequency domain.
[0034] The servo control unit 100 inputs the detection speed or the differentiation { is differentiated to produce servo velocity data} of the detection position {for at least one tool positioning servo motor, where the position data} to the frequency characteristic measurement unit 300. The frequency characteristic measurement unit 300 measures and outputs, to the control assistance unit 400, the frequency characteristics of the amplitude ratio (input/output gain) between the speed command to be the input signal and the output signal, and the phase shift. { before converting to the frequency domain.}
Zhang, Soma, and Tsuneki are considered to be analogous to the claimed invention because they are in the same field of endeavor of machine tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang and Soma to incorporate the teachings of Tsuneki by using the position data in Zhang and differentiating it to produce velocity before converting to the frequency, as shown in Tsuneki and converting to the frequency as in claim 1 is shown in Soma. Doing so in order to get velocity data straight from data available in the controller.
Regarding claim 13, Zhang Soma, and Tsuneki teach the method according to Claim 12
Zhang further teaches in paragraph [n0019], [n0020], [n0057].
further comprising computing a composite tool breakage indicator using a square-root-of-the-sum-of-the-squares calculation including each of the tool breakage indicators, and taking remedial action when the composite tool breakage indicator exceeds an associated threshold value.
[n0019] Wear characteristics are obtained by decomposing the high-frequency machine spindle current signal.
[n0020] The indexes are fused and dimensionality reduced by calculating {further comprising computing a composite tool breakage indicator} the root mean square value of wear characteristics; { using a square-root-of-the-sum-of-the-squares calculation including each of the individual tool breakage indicators}
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold is reached twice consecutively. { and taking remedial action when the composite tool breakage indicator exceeds an associated threshold value.} The time interval between the two failure thresholds can be set according to the on-site working conditions.
Regarding claim 15, Zhang and Soma teach the system according to Claim 14.
Zhang further teaches in paragraph [n0071]
wherein the machine tool parameter is spindle torque command data,
[n0071] The internal data of the CNC system includes {wherein the machine tool parameter is} spindle power, spindle current, spindle torque, which reflect the spindle cutting load, {spindle torque command data} as well as X/Y/Z coordinates that reflect changes in tool position.
In addition, there is process information such as cutting parameters, tool name, and program name that reflects the cutting process. {Reasoning for combining references}
Zhang and Soma fail to teach or the machine tool parameter is a tool positioning servo motor position data which is differentiated to produce servo velocity data before converting to the frequency domain.
However, Tsuneki teaches in paragraph [0034]
or the machine tool parameter is a tool positioning servo motor position data which is differentiated to produce servo velocity data before converting to the frequency domain.
[0034] The servo control unit 100 inputs the detection speed or the differentiation { which is differentiated to produce servo velocity data} of the detection position { or the machine tool parameter is a tool positioning servo motor position data} to the frequency characteristic measurement unit 300. The frequency characteristic measurement unit 300 measures and outputs, to the control assistance unit 400, the frequency characteristics of the amplitude ratio (input/output gain) between the speed command to be the input signal and the output signal, and the phase shift. { before converting to the frequency domain.}
Zhang, Soma, and Tsuneki are considered to be analogous to the claimed invention because they are in the same field of endeavor of machine tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang and Soma to incorporate the teachings of Tsuneki by using the position data in Zhang and differentiating it to produce velocity before converting to the frequency, as shown in Tsuneki and converting to the frequency as in claim 1 is shown in Soma. Doing so in order to get velocity data straight from data available in the controller.
Regarding claim 19, Zhang and Soma teach the system according to Claim 18 wherein individual tool breakage indicators are calculated
Zhang further teaches in paragraph [n0071]
for spindle torque command data and position data
[n0071] The internal data of the CNC system includes spindle power, spindle current, spindle torque, which reflect the spindle cutting load, {for spindle torque command data} as well as X/Y/Z coordinates that reflect changes in tool position. {and position data}
In addition, there is process information such as cutting parameters, tool name, and program name that reflects the cutting process. {Reasoning for combining references}
Zhang and Soma fail to teach for at least one tool positioning servo motor, where the position data is differentiated to produce velocity data before converting to the frequency domain.
However, Tsuneki teaches in paragraph [0034]
for at least one tool positioning servo motor, where the position data is differentiated to produce velocity data before converting to the frequency domain.
[0034] The servo control unit 100 inputs the detection speed or the differentiation { is differentiated to produce servo velocity data} of the detection position { for at least one tool positioning servo motor, where the position data} to the frequency characteristic measurement unit 300. The frequency characteristic measurement unit 300 measures and outputs, to the control assistance unit 400, the frequency characteristics of the amplitude ratio (input/output gain) between the speed command to be the input signal and the output signal, and the phase shift. { before converting to the frequency domain.}
Zhang, Soma, and Tsuneki are considered to be analogous to the claimed invention because they are in the same field of endeavor of machine tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang and Soma to incorporate the teachings of Tsuneki by using the position data in Zhang and differentiating it to produce velocity before converting to the frequency, as shown in Tsuneki and converting to the frequency as in claim 1 is shown in Soma. Doing so in order to get velocity data straight from data available in the controller.
Claim 20 is merely the limitations of claim 9 so the rationales and prior art used for this claim can be applied here as well.
Regarding claim 20, Zhang Soma, and Tsuneki teach the system according to Claim 19
Zhang further teaches in paragraph [n0019], [n0020], [n0057].
further comprising computing a composite tool breakage indicator using a square-root-of-the-sum-of-the-squares calculation including each of the individual tool breakage indicators, and taking remedial action when the composite tool breakage indicator exceeds an associated threshold value.
[n0019] Wear characteristics are obtained by decomposing the high-frequency machine spindle current signal.
[n0020] The indexes are fused and dimensionality reduced by calculating {further comprising computing a composite tool breakage indicator} the root mean square value of wear characteristics; { using a square-root-of-the-sum-of-the-squares calculation including each of the individual tool breakage indicators}
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold is reached twice consecutively. { and taking remedial action when the composite tool breakage indicator exceeds an associated threshold value.} The time interval between the two failure thresholds can be set according to the on-site working conditions.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang (CN-114800040-A) in view of Soma (JP-2004351597-A) in view of Kettemer (US-9069347-B2).
Regarding claim 10, Zhang and Soma teach the method according to Claim 1
Zhang further teaches in paragraph [n0021]
wherein the remedial action includes issuing an alert when any of the threshold values is exceeded,
[n0021] The selection of tool wear monitoring threshold is simplified by normalizing the fusion features. The failure threshold is calculated and an alarm is triggered when the failure threshold is reached {wherein the remedial action includes issuing an alert when any of the threshold values is exceeded,} twice consecutively. The time interval between the two failure thresholds can be set according to the on-site working conditions.
Zhang and Soma do not teach and stopping the machining operation when a highest of the threshold values is exceeded.
However, Kettemer teaches in [Col 1 lines 42-50] and [Col 5 lines 65 -67]
and stopping the machining operation when a highest of the threshold values is exceeded.
[Col 1 Lines 42-50] As soon as the collision monitoring unit detects that the measuring value of the collision sensor exceeds the predetermined collision limit value, a fast shutdown is performed on the machine tool via machine control {stopping the machining operation when a highest of the threshold values is exceeded}, i.e. via the programmable logic controller (PLC), in which the drive of the work
spindle and the drives of the feed axes of the machine tool are stopped to be able to prevent or at least reduce damage to the machine tool due to the detected collision.
[Col 5 lines 65 -67] Thus, collision damage to the machine tool in case of collision or too hard machining can be avoided even more efficiently and safety. {Reason to combine references}
Zhang, Soma, and Kettemer are considered to be analogous to the claimed invention because they are all in the same field of endeavor of machine cutting tools with spindles. It would have been obvious to one of the ordinary skills in the art before the effective filling data of the claimed invention to have modified Zhang and Soma to incorporate the teachings of Kettemer by adding the machine tool fast shutdown by the machine controller to work alongside the alarm when higher threshold is exceeded. Doing so would be in order avoid damage more efficiently and safety.
Conclusion
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/JESSICA DORA CHAU/
/J.D.C./Examiner, Art Unit 2116
/KENNETH M LO/Supervisory Patent Examiner, Art Unit 2116
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