Data processing device for coating equipment, data processing method for coating equipment, data processing program for coating equipment

Abstract

To provide a data processing device for a coating device which can efficiently store data of a coating device.SOLUTION: A data processing device 1 for a coating device 2 includes: a raw data acquisition part 11 for acquiring raw data of the coating device 2 for subjecting a base material 3 to coating treatment; a statistical data generation part 13 for subjecting a series of raw data acquired over a predetermined reference period to statistical treatment, and generating at least one statistical data; and a statistical data storage part 14 for storing the statistical data. The data processing device 1 further includes: an abnormality determination part 15 for determining abnormality of the coating device 2 in a reference period on the basis of the statistical data; a raw data storage part 16 for storing a series of raw data acquired over a reference period during which abnormality has been determined; and a raw data discarding part 17 for discarding a series of raw data acquired over a reference period during which the abnormality has not been determined.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a data processing device for a coating apparatus and the like.

Background Art

[0002] Patent Document 1 discloses a coating apparatus that performs a coating process on a substrate. Guide rollers are provided upstream and downstream of the coating process section to convey the substrate before and after coating along the conveyance direction from the upstream side to the downstream side while pressing the substrate against the coating process section.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For the purpose of monitoring a coating apparatus and the like, various raw data such as the tension of a substrate are measured and stored. Typically, the raw data is measured and stored each time the substrate moves a predetermined reference length. However, the conveyance speed of the substrate in a coating apparatus is often smaller than that of the substrate in a printing machine, for example. With the measurement and storage of raw data for each reference length, the time interval becomes large, and it may be difficult to accurately grasp the behavior of the coating apparatus. On the other hand, by shortening the reference length, the time interval for measuring and storing the raw data can be shortened. However, since the amount of raw data to be stored increases, not only does it take a long time to confirm, but also the storage for it requires a large capacity.

[0005] The present invention has been made in view of such a situation, and an object thereof is to provide a data processing device for a coating apparatus and the like that can efficiently store data of the coating apparatus.

Means for Solving the Problems

[0006] To solve the above problems, a data processing device for a coating apparatus according to one aspect of the present invention includes: a raw data acquisition unit that acquires raw data of a coating apparatus that applies a coating process to a substrate; a statistical data generation unit that performs statistical processing on a series of raw data acquired over a predetermined reference period to generate at least one statistical data; and a statistical data storage unit that stores the statistical data.

[0007] According to this embodiment, data from the coating apparatus can be efficiently stored by saving statistical data, which is smaller in volume compared to raw data.

[0008] Another aspect of the present invention is a data processing method for a coating apparatus. This method comprises: a raw data acquisition step of acquiring raw data of a coating apparatus that applies a coating treatment to a substrate; a statistical data generation step of applying statistical processing to a series of raw data acquired over a predetermined reference period to generate at least one statistical data; and a statistical data storage step of storing the statistical data.

[0009] Furthermore, any combination of the above components, as well as methods, apparatus, systems, recording media, computer programs, etc., derived from these representations, are also included in the present invention. [Effects of the Invention]

[0010] According to the present invention, data from a coating apparatus can be stored efficiently. [Brief explanation of the drawing]

[0011] [Figure 1] A schematic diagram shows the configuration of a data processing device for a coating apparatus that applies a coating treatment to a substrate. [Figure 2] This section provides specific examples of raw data acquired by the raw data acquisition unit and statistical data generated by the statistical data generation unit. [Figure 3] This graph shows the time evolution of the raw data in Figure 2. [Modes for carrying out the invention]

[0012] The following describes in detail embodiments (hereinafter also referred to as "models") for carrying out the present invention, with reference to the drawings. In the description and / or drawings, identical or equivalent components, members, processes, etc., are denoted by the same reference numerals, and redundant descriptions are omitted. The scale and shape of each part shown in the drawings are set for convenience to simplify the description and are not to be interpreted restrictively unless otherwise specified. The embodiments are illustrative and do not limit the scope of the present invention in any way. Not all features or combinations thereof described in the embodiments are necessarily essential to the present invention.

[0013] Figure 1 schematically shows the configuration of a data processing device 1 for a coating apparatus 2 that applies a coating treatment to a substrate 3. Examples of substrates 3 include linear materials such as strings and wires, and planar or sheet materials such as paper, cloth, film, foil, and rubber. In this embodiment, a roll-to-roll type coater or coating apparatus 2 that applies a coating treatment to the surface and / or back surface of a sheet-like substrate 3 while conveying it in the conveying direction (generally from left to right in Figure 1) will be described.

[0014] The coating apparatus 2 comprises a first coating roller 21 and a second coating roller 22 that constitute the coating processing section, a tension detector 23 for detecting the tension of the substrate 3, and a length measuring roller 24 for measuring the amount of movement of the substrate 3 in the transport direction.

[0015] The first coating roller 21 and the second coating roller 22 constitute a coating processing unit that coats the coating material onto the coating surface (front and / or back) of the substrate 3. For example, a portion of the surface of the first coating roller 21 is immersed in coating material stored in a liquid tank or the like (not shown), and the first coating roller 21 rotates clockwise in Figure 1, coating the surface (bottom surface in Figure 1) of the substrate 3 while it is being transported in the transport direction. Similarly, in addition to or instead of the first coating roller 21, a portion of the surface of the second coating roller 22 may be immersed in coating material stored in a liquid tank or the like (not shown), and the second coating roller 22 rotates counterclockwise in Figure 1, coating the back surface (top surface in Figure 1) of the substrate 3 while it is being transported in the transport direction.

[0016] The first coating roller 21 and the second coating roller 22 apply a coating process to the coating surface of the substrate 3 while sandwiching and conveying the substrate 3 from both sides. For example, one of the first coating roller 21 and the second coating roller 22 is a drive roller that is rotationally driven by a drive motor (not shown), and the other of the first coating roller 21 and the second coating roller 22 is a driven roller that rotates in conjunction with the drive roller.

[0017] The tension detector 23 detects the tension of the substrate 3 in the transport direction. The configuration and principle of the tension detector 23 are arbitrary, but for example, a dancer roller that is biased by an air cylinder or the like to apply tension to the substrate 3 may be used as the tension detector 23, and the dancer that detects its position as tension may be used. As will be described later, in this embodiment, the raw data acquisition unit 11 of the data processing device 1 acquires the tension of the substrate 3 detected by the tension detector 23 as "raw data" to be processed by the data processing device 1. However, the tension of the substrate 3 is only one example of raw data, and various data useful for the operation and monitoring of the coating device 2 may be used as raw data to be processed by the data processing device 1 in addition to or instead of the tension of the substrate 3. Examples of such other raw data include the transport speed of each part of the substrate 3, which can also be detected by the length measuring roller 24 described later, the coating thickness and other indicators of coating quality, and the temperature, humidity, atmospheric pressure, brightness of each part of the coating device 2 and its surroundings.

[0018] The measuring roller 24 measures the amount of movement of the substrate 3 in the transport direction. The measuring roller 24 itself and / or the drive motor (not shown) that rotates the measuring roller 24 are provided with encoders that detect their rotation angles. For example, an incremental encoder outputs a predetermined number of A-phase and B-phase pulse signals and one Z-phase pulse signal for each rotation of the measuring roller 24 and / or the drive motor. The A-phase and B-phase pulse signals are counted by a counter, and the count value is reset by the Z-phase pulse signal. The count values ​​of the A-phase and B-phase pulse signals, which increase with each rotation of the measuring roller 24 and / or the drive motor, represent the phase or rotational position of the measuring roller 24 and / or the drive motor.

[0019] As described later, the reference length measuring unit 12 of the data processing device 1 detects when the substrate 3 has moved a predetermined reference length, and it is preferable that such a reference length is set based on Z-phase pulses output by an encoder. For example, if the interval at which the encoder provided on the length measuring roller 24 outputs Z-phase pulses is set as the reference length, the circumference of the length measuring roller 24 (typically the circumference) becomes the reference length. Alternatively, if the interval at which the encoder provided on the length measuring roller 24 outputs Z-phase pulses N times (N is a natural number) is set as the reference length, then N times the circumference of the length measuring roller 24 becomes the reference length. In this way, by utilizing the Z-phase pulses output during the normal operation of the encoder, the reference length measuring unit 12 can directly measure the reference length without any special additional processing. Note that the reference length may also be set based on A-phase and B-phase pulses. Furthermore, the encoder may be any other type of phase detector or rotational position detector, such as an absolute type.

[0020] The data processing device 1 includes a raw data acquisition unit 11, a reference length measurement unit 12, a statistical data generation unit 13, a statistical data storage unit 14, an abnormality determination unit 15, a raw data storage unit 16, and a raw data discard unit 17. These functional blocks are realized by the cooperation of hardware resources such as a central processing unit, memory, input device, output device, and peripheral devices connected to a computer, and software executed using them. Regardless of the type and installation location of the computer, each of the above functional blocks may be realized by the hardware resources of a single computer, or may be realized by combining hardware resources distributed among multiple computers. For example, some or all of the functional blocks of the data processing device 1 may be realized distributively or centrally by a computer or processor provided on the same site or building as the coating device 2, or may be realized distributively or centrally by a computer or processor provided on a site or building different from the coating device 2.

[0021] The raw data acquisition unit 11 acquires the raw data of the coating device 2. In the example of this embodiment, the raw data acquisition unit 11 acquires the tension of the base material 3 detected by the tension detector 23 as raw data. It is preferable that the frequency at which the raw data acquisition unit 11 acquires raw data is as high as possible. For example, it is preferable that the control cycle (typically several ms) of the computer or processor in which the raw data acquisition unit 11 is realized is used. Note that the raw data acquisition unit 11 may start acquiring raw data from the tension detector 23 using, as a trigger, the fact that the reference length measurement unit 12 described later has detected the first reference length (for example, the first Z-phase signal output by the encoder provided on the length measurement roller 24). Further, the raw data acquisition unit 11 includes a primary storage area that temporarily stores at least the raw data corresponding to the reference length, and executes a data transfer process to the raw data storage unit 16 described later according to the determination result of the abnormality determination unit 15 described later.

[0022] The reference length measurement unit 12 detects that the base material 3 has moved a predetermined reference length based on the pulses output by an encoder provided in the length measurement roller 24 and / or the drive motor. Hereinafter, the reference length is also referred to as the repeat length. The statistical data generation unit 13 performs statistical processing on a series of raw data (such as tension) acquired by the raw data acquisition unit 11 over a predetermined reference period to generate at least one piece of statistical data. This reference period is the period during which the base material 3 moves the reference length measured by the reference length measurement unit 12. For example, when the interval at which an encoder provided in the length measurement roller 24 with a circumference of 1,000 mm outputs Z-phase pulses (that is, 1,000 mm) is taken as the reference length, the statistical data generation unit 13 performs statistical processing on a series of raw data acquired by the raw data acquisition unit 11 at a control cycle of several milliseconds while the base material 3 moves 1,000 mm. That is, every time the base material 3 moves 1,000 mm, a set of statistical data is generated by the statistical data generation unit 13.

[0023] The statistical data generated by the statistical data generation unit 13 includes at least any one of the maximum value, minimum value, peak-to-peak value (pp value), root mean square (RMS), and frequency analysis data of a series of raw data acquired over the reference period, that is, the reference length (1,000 mm). Here, the frequency analysis data is various data (for example, the intensity of data in a specific frequency interval) obtained by converting a series of raw data in the time domain acquired over the reference period into the frequency domain by Fourier transform or the like.

[0024] Figure 2 shows specific examples of the raw data acquired by the raw data acquisition unit 11 and the statistical data generated by the statistical data generation unit 13. Further, Figure 3 is a graph showing the time change of the raw data in Figure 2. The raw data in these examples is the variation in the positive and negative directions from the reference value "0" of the tension of the base material 3 detected by the tension detector 23.

[0025] In Figure 2, the "data number" is a sequential number conveniently assigned to the raw data acquired during the control cycle (several ms) of the computer or processor in which the raw data acquisition unit 11 is implemented. In the examples in Figures 2 and 3, assuming that the transport speed of the substrate 3 is a constant production speed, "20" data numbers or raw data correspond to the standard period and / or standard length. In other words, "20" raw data are acquired by the raw data acquisition unit 11 while the substrate 3 moves the standard length of 1,000 mm, and a set of statistical data is generated by the statistical data generation unit 13 each time the substrate 3 moves the standard length of 1,000 mm.

[0026] Specifically, the raw data acquisition unit 11, which is activated when the reference length measuring unit 12 detects the first reference length (for example, the first Z-phase signal output by the encoder provided on the length measuring roller 24), acquires the raw data "0.000" with data number "0" immediately after activation. The statistical data generation unit 13 may also be activated substantially simultaneously with the raw data acquisition unit 11 when the reference length measuring unit 12 detects the first reference length, and may generate the raw data "0.000" with data number "0", which is the point at which the reference period and / or reference length is reached, as "periodic data" for the reference period and / or reference length up to data number "0". However, since this "periodic data" is the same as "raw data", and no other "raw data" for generating other statistical data such as the maximum value has been collected by the raw data acquisition unit 11 at this point, the statistical data generation unit 13 does not need to be activated yet.

[0027] While the base material 3 moves from data number "0" to the reference length of 1,000 mm (while the measuring roller 24 with a circumference of 1,000 mm completes one rotation), the raw data acquisition unit 11 acquires 20 raw data points with data numbers "1" to "20". The statistical data generation unit 13 generates the raw data "0.913" for data number "20", which is the point at which the reference period and / or reference length is reached, as "periodic data" for the reference period and / or reference length of data numbers "1" to "20". In addition, it generates other statistical data such as "MAX" (maximum value), "MIN" (minimum value), "RMS" (root mean square), and "PP" (peak-peak value) for the series of raw data from data numbers "1" to "20". In the example in Figure 2, the raw data value "0.913" for data number "14" becomes the "MAX" for data number "20", the raw data value "-1.000" for data number "11" becomes the "MIN" for data number "20", and the difference between the two, "1.991", becomes the "PP" for data number "20". Note that the "RMS" (0.473) for data number "20" is obtained by applying the well-known definition of the root mean square to the series of raw data from data numbers "1" to "20".

[0028] While the substrate 3 moves along the standard length of 1,000 mm from the point of data number "20", the raw data acquisition unit 11 acquires 20 raw data points from data numbers "21" to "40". The statistical data generation unit 13 generates the raw data "0.745" at data number "40", which is the point at which the standard period and / or standard length is reached, as "periodic data" for the standard period and / or standard length of data numbers "21" to "40", and also generates other statistical data such as "MAX", "MIN", "RMS", and "PP" for the series of raw data from data numbers "21" to "40". In the example in Figure 2, the raw data "1.000" at data number "33" becomes the "MAX" at data number "40", the raw data "-1.488" at data number "30" becomes the "MIN" at data number "40", and the difference between the two, "2.488", becomes the "PP" at data number "40". The RMS (0.583) for data number "40" is obtained by applying the well-known definition of the root mean square to the series of raw data from data numbers "21" to "40".

[0029] While the substrate 3 moves along the standard length of 1,000 mm from the point of data number "40", the raw data acquisition unit 11 acquires "20" raw data points from data numbers "41" to "60". The statistical data generation unit 13 generates "periodic data" from the raw data "-0.305" at data number "60", which is the point at which the standard period and / or standard length is reached, as statistical data for the standard period and / or standard length of data numbers "41" to "60", and also generates other statistical data such as "MAX", "MIN", "RMS", and "PP" for the series of raw data from data numbers "41" to "60". In the example in Figure 2, the raw data "0.993" at data number "58" becomes the "MAX" at data number "60", the raw data "-1.000" at data number "55" becomes the "MIN" at data number "60", and the difference between the two, "1.993", becomes the "PP" at data number "60". The "RMS" (0.499) for data number "60" is obtained by applying the well-known definition of the root mean square to the series of raw data from data numbers "41" to "60".

[0030] Figure 3 is a graph showing the time evolution of raw data, including the raw data with data numbers "0" to "60" shown in Figure 2. This figure also shows the raw data with data numbers "61" to "200" that follows Figure 2. The diamond-shaped marks represent "periodic data" that the statistical data generation unit 13 generates or stores as statistical data at data numbers "0", "20", "40", "60", "80", etc., which are the points in time when the base period and / or base length is reached.

[0031] The statistical data storage unit 14 stores the statistical data generated by the statistical data generation unit 13. As shown in Figure 2, each time the statistical data generation unit 13 acquires 20 raw data points corresponding to the reference period and / or reference length by the raw data acquisition unit 11, it generates 5 statistical data points: "periodic data," "MAX," "MIN," "RMS," and "PP." Except when an anomaly is detected based on the statistical data, as will be described later, the 20 raw data points are discarded without being saved, and only the 5 statistical data points are saved by the statistical data storage unit 14. In this way, according to this embodiment, the data of the coating apparatus 2 can be efficiently saved by saving statistical data, which is smaller in quantity than the raw data. Note that the number of raw data points, 20, corresponding to the reference period and / or reference length is merely an example for convenience, and in reality, it may be significantly more than 20. Even if the number of raw data points for the reference period and / or reference length increases in this way, the number of statistical data points saved by the statistical data storage unit 14 does not change, thus effectively preventing the need for a large-capacity storage unit (statistical data storage unit 14) for storage.

[0032] The abnormality determination unit 15 determines an abnormality in the coating apparatus 2 during the reference period and / or reference length based on the statistical data generated by the statistical data generation unit 13. Specifically, the abnormality determination unit 15 determines an abnormality in the coating apparatus 2 during the reference period and / or reference length based on a comparison of each statistical data with a predetermined abnormality determination threshold. In the example in Figure 2, an abnormality determination threshold is set individually for each of the five statistical data: "periodic data," "MAX," "MIN," "RMS," and "PP." The abnormality determination threshold may be a fixed value, or it may be a value that is set adaptively based on statistical values ​​such as the average value of past statistical data. For example, a fixed abnormality determination threshold of "-1.200" is set for "MIN," and if "MIN" in each reference period and / or each reference length falls below this threshold, the abnormality determination unit 15 determines that there was an abnormality in the coating apparatus 2 during each reference period and / or each reference length.

[0033] In the example in Figure 2, the "MIN" (-1.488) of data number "40" is below the abnormality detection threshold (-1.200), so the abnormality detection unit 15 determines that there was an abnormality in the coating apparatus 2 during the reference period and / or reference length for data numbers "21" to "40". In Figure 3, the reference period and / or reference length for data numbers "21" to "40" that the abnormality detection unit 15 determined to be abnormal is enclosed in a rectangular frame. The cause of this abnormality is the raw data "-1.488" of data number "30", but the abnormality detection unit 15 can accurately determine the abnormality based on the statistical data "MIN" rather than the raw data itself. In this way, the abnormality detection unit 15 does not need to check a huge amount of raw data one by one, and can efficiently determine abnormalities in the coating apparatus 2 based on a small amount of statistical data.

[0034] The raw data storage unit 16 stores a series of raw data acquired over a reference period and / or reference length for which an abnormality was determined by the abnormality determination unit 15. As described above, the series of raw data is temporarily stored in the primary storage area of ​​the raw data acquisition unit 11, and only the data corresponding to the reference period and / or reference length for which an abnormality was determined is transferred to and stored in the raw data storage unit 16. In the example in Figures 2 and 3, the raw data for data numbers "21" to "40" for which an abnormality was determined is stored in the raw data storage unit 16. Thus, for the reference period and / or reference length for data numbers "21" to "40" for which an abnormality was determined, in addition to the statistical data for data number "40" generated by the statistical data generation unit 13 being stored in the statistical data storage unit 14, the raw data for data numbers "21" to "40" is stored in the raw data storage unit 16. By referring to the series of raw data stored in the raw data storage unit 16, a detailed analysis of the abnormality of the coating apparatus 2 during the reference period and / or reference length can be effectively performed, and the cause can be identified.

[0035] The statistical data storage unit 14 and the raw data storage unit 16 may be configured with the same storage or with different storage. Also, the file for regular monitoring in which the statistical data storage unit 14 stores statistical data and the file for abnormal record storage in which the raw data storage unit 16 stores raw data may be the same or different. Regardless of the configuration of such storage and files, it is preferable that the statistical data (regular monitoring data) stored by the statistical data storage unit 14 and the raw data (abnormal record data) stored by the raw data storage unit 16 are stored in a manner that allows them to be identified and referenced from one another.

[0036] On the other hand, the raw data discard unit 17 discards a series of raw data acquired over a reference period and / or reference length for which no abnormality was detected by the abnormality detection unit 15. Specifically, the raw data temporarily stored in the primary storage area of ​​the raw data acquisition unit 11 that corresponds to the reference period and / or reference length for which no abnormality was detected is erased. In the example in Figure 2, the raw data with data numbers "0" to "20" and data numbers "41" to "60" for which no abnormality was detected is discarded by the raw data discard unit 17. In this way, for the reference period and / or reference length for which no abnormality was detected, only the minimum statistical data generated by the statistical data generation unit 13 is stored in the statistical data storage unit 14, and the raw data is not stored in the raw data storage unit 16. Therefore, according to this embodiment, it is possible to effectively prevent the storage capacity for raw data (raw data storage unit 16) from becoming excessively large.

[0037] According to this embodiment, even in a coating apparatus 2, which has a lower substrate transport speed compared to a printing press, it is possible to accurately grasp the behavior and abnormalities while efficiently saving data with a small-capacity storage device.

[0038] The present invention has been described above based on embodiments. Various modifications are possible for each component and each combination of processes in the exemplary embodiments, and it will be obvious to those skilled in the art that such modifications are included within the scope of the present invention.

[0039] The configuration, operation, and function of each device and method described in the embodiments can be realized by hardware resources or software resources, or by the cooperation of hardware resources and software resources. Hardware resources include, for example, processors, ROMs, RAMs, and various integrated circuits. Software resources include, for example, operating systems and application programs. [Explanation of Symbols]

[0040] 1 Data processing device, 2 Coating device, 3 Substrate, 11 Raw data acquisition unit, 12 Reference length measurement unit, 13 Statistical data generation unit, 14 Statistical data storage unit, 15 Anomaly detection unit, 16 Raw data storage unit, 17 Raw data discard unit.

Claims

1. A raw data acquisition unit that acquires raw data from a coating apparatus that applies a coating treatment to a substrate, A statistical data generation unit performs statistical processing on a series of raw data acquired over a predetermined reference period to generate statistical data that is smaller in quantity than at least one of the raw data, A statistical data storage unit for storing the aforementioned statistical data, An abnormality determination unit that determines an abnormality of the coating apparatus during the reference period based on the aforementioned statistical data, A raw data storage unit that stores a series of raw data acquired over the aforementioned reference period during which an abnormality was determined, A raw data discarding unit discards a series of raw data acquired over the reference period during which no abnormality was detected by the abnormality detection unit. A data processing device for a coating apparatus, comprising:

2. The data processing device for a coating apparatus according to claim 1, wherein the abnormality determination unit determines an abnormality in the coating apparatus during the reference period based on a comparison of a predetermined abnormality determination threshold with the statistical data.

3. The data processing apparatus for a coating apparatus according to claim 1 or 2, wherein the statistical data includes at least one of the maximum value, minimum value, peak-to-peak value, root mean square, and frequency analysis data of a series of raw data acquired over the reference period.

4. The data processing apparatus for a coating apparatus according to claim 1 or 2, wherein the reference period is the period during which the substrate moves a predetermined reference length.

5. A raw data acquisition step to acquire raw data from a coating apparatus that applies a coating treatment to a substrate, A statistical data generation step involves performing statistical processing on a series of raw data acquired over a predetermined reference period to generate statistical data that is smaller in quantity than at least one of the raw data, A statistical data storage step for storing the aforementioned statistical data, An abnormality determination step in which an abnormality of the coating apparatus during the reference period is determined based on the aforementioned statistical data, A raw data storage step involves storing a series of raw data acquired over the reference period during which an anomaly was determined, A raw data discard step which discards a series of raw data acquired over the reference period in which no abnormality was determined by the abnormality determination step, A data processing method for a coating apparatus, comprising the following components.

6. A raw data acquisition step to acquire raw data from a coating apparatus that applies a coating treatment to a substrate, A statistical data generation step involves performing statistical processing on a series of raw data acquired over a predetermined reference period to generate statistical data that is smaller in quantity than at least one of the raw data, A statistical data storage step for storing the aforementioned statistical data, An abnormality determination step in which an abnormality of the coating apparatus during the reference period is determined based on the aforementioned statistical data, A raw data storage step involves storing a series of raw data acquired over the reference period during which an anomaly was determined, A raw data discard step which discards a series of raw data acquired over the reference period in which no abnormality was determined by the abnormality determination step, A data processing program for coating equipment that causes a computer to execute the following.

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