Level adjustment device and level adjustment method

Abstract

A level adjustment device (300) is provided with: an analog leveling instrument (10) with which the inclination of an object (205) to be adjusted with respect to the horizontal plane is visually checked; an imaging unit (30) that images the leveling instrument (10); and an output unit (301) that outputs an image of the leveling instrument (10) captured by the imaging unit (30).

Description

Level adjustment device and level adjustment method

[0001] This disclosure relates to a leveling device and a method for controlling the leveling method.

[0002] Leveling devices for leveling an object to be adjusted relative to a floor have been disclosed. Japanese Patent No. 6724622 discloses a leveling support device for supporting an operator when adjusting the level of a semiconductor manufacturing equipment as the object to be adjusted. The leveling support device of Japanese Patent No. 6724622 includes a level measuring instrument, a data processing unit, and a display unit. In the leveling support device of Japanese Patent No. 6724622, a digital level measuring instrument is mounted on the semiconductor manufacturing equipment and detects the inclination of the semiconductor manufacturing equipment. The inclination data detected by the digital level measuring instrument is wirelessly transmitted to a data processing unit located at a distance from the semiconductor manufacturing equipment. Furthermore, multiple legs are disposed on the underside of the semiconductor manufacturing equipment. The legs include adjusters, and the height of the legs is changed by rotating the adjusters by the operator. The data processing unit calculates the number of rotations of the leg adjusters to level the semiconductor manufacturing equipment based on the inclination data of the semiconductor manufacturing equipment detected by the digital level measuring instrument.

[0003] Patent No. 6724622

[0004] However, the digital level measuring instrument disclosed in Japanese Patent No. 6724622 is large in size due to its relatively complex structure, and therefore it is desirable to reduce the size of the level adjustment device.

[0005] This disclosure has been made to solve the above-mentioned problems, and one object of this disclosure is to provide a level adjustment device and a level adjustment method that enable the level adjustment device to be miniaturized.

[0006] A level adjustment device according to a first aspect of this disclosure includes an analog level that allows the inclination of the object to be adjusted relative to a horizontal plane to be visually confirmed, an imaging unit that images the level, and an output unit that outputs the image of the level imaged by the imaging unit.

[0007] As described above, the level adjustment device according to a first aspect of this disclosure includes an analog level that allows the inclination of the object to be adjusted relative to a horizontal plane to be visually confirmed. As a result, the analog level has a relatively simpler structure than a digital level and is therefore smaller than a digital level. As a result, the level adjustment device can be made more compact. Furthermore, the level adjustment device according to the first aspect includes an imaging unit that captures an image of the level and an output unit that outputs an image of the level captured by the imaging unit. Therefore, an operator can easily check the inclination of the object to be adjusted from a position separated from the object by checking the image of the level output on a display unit or the like. Furthermore, the analog level is easier to handle than a digital level. Furthermore, the analog level does not require calibration like a digital level.

[0008] A level adjustment method according to a second aspect of this disclosure is a level adjustment method for a level adjustment device that includes an analog level, an imaging unit, and an output unit, in which the imaging unit images the analog level, which allows the inclination of the object to be adjusted relative to a horizontal plane to be visually confirmed, and the output unit outputs an image of the level imaged by the imaging unit.

[0009] In the level adjustment method according to a second aspect of this disclosure, as described above, an analog level is used, which allows the inclination of the object to be adjusted relative to a horizontal plane to be visually confirmed. As a result, an analog level has a relatively simpler structure than a digital level and is therefore smaller than a digital level. As a result, a level adjustment method that allows for a more compact level adjustment device can be provided. Furthermore, in the level adjustment method according to the second aspect, the output unit outputs an image of the level captured by the imaging unit. Therefore, an operator can easily check the inclination of the object to be adjusted from a position separated from the object by checking the image of the level output on a display unit, etc. Furthermore, an analog level is easier to handle than a digital level. Furthermore, an analog level does not require calibration, as does a digital level.

[0010] According to the present disclosure, it is possible to check the inclination of an object to be adjusted at a position separated from the object to be adjusted while miniaturizing the level adjustment device.

[0011] 10 is a diagram showing a level adjustment device according to a first embodiment; FIG. 11 is a diagram showing the configuration of a substrate processing system; FIG. 12 is a diagram showing a level according to the first embodiment; FIG. 13 is a block diagram of the level adjustment device according to the first embodiment; FIG. 14 is a flow chart for explaining a level adjustment method according to the first embodiment; FIG. 15 is a diagram showing a level adjustment device and an EFEM according to a second embodiment; FIG. 16 is a block diagram of the level adjustment device according to the second embodiment; FIG. 17 is a diagram for explaining a learning model for estimating the adjustment amount of the level adjustment mechanism according to the second embodiment; FIG. 18 is a diagram showing a state in which the EFEM is bent; FIG. 19 is a diagram showing a level placed in the EFEM; FIG. 19 is a diagram showing a level placed in a position different from that in FIG. 10; FIG. 19 is a flow chart for explaining a level adjustment method according to the second embodiment; FIG. 19 is a diagram showing a level adjustment device and an EFEM according to a third embodiment; FIG. 19 is a block diagram of the level adjustment device according to the third embodiment; FIG. 19 is a flow chart for explaining a level adjustment method according to the third embodiment.

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0013] [First Embodiment] A level adjustment device 300 according to the first embodiment will be described. As shown in Fig. 1, the level adjustment device 300 is a device for assisting an operator in leveling an Equipment Front End Module (EFEM) 205 with respect to a floor surface 1. The EFEM 205 is an example of an object to be adjusted and a semiconductor manufacturing device.

[0014] (Substrate Processing System) The configuration of a substrate processing system 200 including an EFEM 205 will be described. As shown in FIG. 2 , the substrate processing system 200 includes a substrate transfer robot 201, a load lock unit 202, a plurality of processing module units 203, a transfer chamber 204, and an EFEM 205. The substrate transfer robot 201 is a horizontal articulated robot. The load lock unit 202 is a room for loading and unloading substrates 210. In the processing module unit 203, processes such as resist coating and etching are performed on the substrates 210. The substrate transfer robot 201 is disposed in the transfer chamber 204. A robot 205a for transferring the substrates 210 is disposed in the EFEM 205.

[0015] (Level Adjustment Device) A description will be given of the configuration of the level adjustment device 300. As shown in FIG.

[0016] The configuration of the spirit level 10 will be described. The spirit level 10 is placed on the EFEM 205 and detects the inclination of the EFEM 205 with respect to a horizontal plane. The spirit level 10 is an analog type spirit level 10 that allows the inclination of the EFEM 205 with respect to a horizontal plane to be visually confirmed. As shown in FIG. 3 , in the first embodiment, the spirit level 10 includes a liquid 12 contained in a container 11 and an air bubble 13 contained in the liquid 12. When the spirit level 10 is placed on a horizontal surface, the air bubble 13 is located at the center of the container 11. Specifically, the surface of the container 11 of the spirit level 10 is made of a transparent material that allows the air bubble 13 inside to be seen, and the inside is a spherical surface with a very large curvature. Therefore, when the spirit level 10 is placed on a horizontal surface, the air bubble 13 moves to the center of the highest point of the spherical surface. On the other hand, when the spirit level 10 is placed on an inclined surface, the air bubble 13 moves to a position shifted from the center of the highest point of the spherical surface, and therefore the air bubble 13 is located at a position shifted from the center of the container 11.

[0017] The configuration of the level adjustment mechanism 20 will be described. As shown in FIG. 1 , the level adjustment mechanism 20 may be, for example, an electric hydraulic jack, a manual jack, or an adjuster whose height is manually adjusted. In an electric hydraulic jack, the height of the electric hydraulic jack is adjusted by the amount of oil pumped from the electric pump. For example, by turning on a switch, oil is pumped to the electric pump, and the height of the electric hydraulic jack is adjusted. In a manual jack, the height of the manual jack is adjusted by manually moving the handle up and down to change the amount of oil pumped. In an adjuster, the height of the adjuster is adjusted by manually rotating a nut that threads onto a bolt of the adjuster. Furthermore, a plurality of level adjustment mechanisms 20 are arranged below the EFEM 205. For example, a level adjustment mechanism 20 is arranged at each of the four lower corners of the EFEM 205.

[0018] The configuration of the imaging unit 30 will be described. The imaging unit 30 is, for example, a two-dimensional camera. The imaging unit 30 captures an image of the spirit level 10 placed in the EFEM 205. Specifically, the imaging unit 30 captures an image of the container 11, the liquid 12, and the bubbles 13 in the spirit level 10. The imaging unit 30 may be disposed in a position where it can capture an image of the spirit level 10. For example, the imaging unit 30 is disposed on the ceiling above the spirit level 10. The imaging unit 30 may also be disposed on a support member such as a stand that supports the imaging unit 30.

[0019] The configuration of the output unit 301 will be described. The output unit 301 outputs an image of the level 10 captured by the imaging unit 30 to the display unit 302. For example, the output unit 301 is disposed in the imaging unit 30. The output unit 301 is also connected to the display unit 302 by wiring 303, for example, and outputs the image of the level 10 captured by the imaging unit 30 to the display unit 302 via the wiring 303. The output unit 301 may also wirelessly output the image of the level 10 captured by the imaging unit 30 to the display unit 302. The image captured by the imaging unit 30 may be a still image or a video.

[0020] The configuration of the display unit 302 will be described. As shown in FIG. 4 , the display unit 302 is disposed separately from the level adjustment device 300. The display unit 302 may also be included in the level adjustment device 300. The display unit 302 is, for example, a liquid crystal display. The display unit 302 may also be disposed near the EFEM 205 or far from the EFEM 205.

[0021] Next, the level adjustment method of the first embodiment will be described with reference to Fig. 5. The level adjustment method is performed using a level adjustment device 300 including the above-described image capture unit 30 and output unit 301. The level 10 is placed on the top surface of the EFEM 205 in advance by an operator. The image capture unit 30 is also placed in advance by the operator in a position where it can capture an image of the level 10.

[0022] In step S21, the level adjustment device 300 receives an instruction from the operator to start imaging by the imaging unit 30.

[0023] In step S22, the imaging unit 30 captures an image of the analog level 10, which allows the inclination of the EFEM 205 with respect to the horizontal plane to be visually confirmed.

[0024] In step S23, the output unit 301 outputs the image of the spirit level 10 captured by the imaging unit 30 to the display unit 302. If the imaging unit 30 captures a still image, the operations of steps S21 to S23 are repeated. If the imaging unit 30 captures a moving image, the operations of steps S22 and S23 are repeated until the level adjustment device 300 receives an instruction to stop capturing images by the imaging unit 30. While visually checking the image of the spirit level 10 displayed on the display unit 302, the operator manually adjusts the level adjustment mechanism 20 so that the EFEM 205 is horizontal.

[0025] Effect of the First Embodiment The level adjustment device 300 includes an analog level 10 that allows visual confirmation of the inclination of the EFEM 205 with respect to a horizontal plane. The analog level 10 has a relatively simpler structure than a digital level and is therefore smaller than a digital level. As a result, the level adjustment device 300 can be made more compact. The level adjustment device 300 also includes an imaging unit 30 that captures an image of the level 10 and an output unit 301 that outputs the image of the level 10 captured by the imaging unit 30 to a display unit 302. Therefore, an operator can easily visually confirm the inclination of the EFEM 205 from a position separated from the EFEM 205 by checking the image of the level 10 displayed on the display unit 302. Furthermore, the analog level 10 does not require calibration, as does the digital level 10. Furthermore, the analog level 10 is easier to handle than a digital level.

[0026] The spirit level 10 has a liquid 12 contained in a container 11 and an air bubble 13 contained in the liquid 12, and the image capturing unit 30 captures an image of the container 11, the liquid 12, and the air bubble 13 in the spirit level 10. This allows the operator to easily check the inclination of the EFEM 205 with respect to the horizontal plane based on the position of the air bubble 13 in the container 11 of the spirit level 10 displayed on the display unit 302.

[0027] The level 10 is disposed in the EFEM 205. This allows the size of the level adjustment device 300 for leveling the EFEM 205 to be reduced.

[0028] Second Embodiment A level adjustment device 100 according to a second embodiment will be described. As shown in Fig. 6 , the level adjustment device 100 is a device for assisting a worker in leveling an Equipment Front End Module (EFEM) 205 with respect to a floor surface 1.

[0029] (Level Adjustment Device) The configuration of the level adjustment device 100 will be described. As shown in FIG. 7 , the level adjustment device 100 includes a spirit level 10, a plurality of level adjustment mechanisms 20, an imaging unit 30, a control unit 40, and a display unit 50. The level adjustment device 100 is a device including the imaging unit 30, the display unit 50, and the control unit 40, such as a tablet terminal. The display unit 50 is an example of an adjustment amount display unit. The display unit 50 may also function as the display unit 302 that displays the image of the spirit level 10 captured by the imaging unit 30 of the first embodiment, or a display unit 302 that displays the image of the spirit level 10 captured by the imaging unit 30 may be provided separately from the display unit 50.

[0030] The configuration of the imaging unit 30 will be described. In the second embodiment, the image captured by the imaging unit 30 is transmitted to the control unit 40. The imaging unit 30 also captures an image of the EFEM 205 along with the level 10. The control unit 40 then recognizes, for example, by image processing, the level 10, the position of the bubble 13 in the level 10, the EFEM 205, and the position of the FEM 205 at which the level 10 is located, based on the image captured by the imaging unit 30.

[0031] The configuration of the control unit 40 will be described. As shown in FIG. 7 , the control unit 40 includes, for example, a CPU (Central Processing Unit). The control unit 40 also includes memories such as RAM and ROM, and a storage unit such as a hard disk. The control unit 40 also includes a machine learning unit 41. The machine learning unit 41 generates a trained model 43 by machine learning based on input training data 42. The machine learning unit 41 also generates the trained model 43 by using, for example, deep learning.

[0032] A method for generating the trained model 43 will be described in detail. As shown in FIG. 8 , in the second embodiment, the trained model 43 is generated by machine learning of images of the level 10 arranged in the EFEM 205. The trained model 43 is also generated by machine learning of images of the level 10 when the adjustment amount of at least one of the multiple level adjustment mechanisms 20 is changed. Specifically, the image capture unit 30 captures images of the level 10 arranged in the EFEM 205 while changing the adjustment amounts of the multiple level adjustment mechanisms 20 in various ways. Each captured image is associated with the adjustment amount of the level adjustment mechanism 20 at the time of capture. For example, if four level adjustment mechanisms 20 are arranged in the EFEM 205, the majority of the weight of the EFEM 205 may be supported by three of the level adjustment mechanisms 20, and one level adjustment mechanism 20 may bear almost no weight. At this time, the change in the level of the EFEM 205 will not be the same when one of the three level adjustment mechanisms 20 that support most of the weight of the EFEM 205 is changed as when one level adjustment mechanism 20 that is not bearing any weight is changed. For this reason, it is necessary to learn images of the spirit level 10 when the adjustment amount of at least one of the multiple level adjustment mechanisms 20 is changed. Then, multiple images obtained when the adjustment amounts of the multiple level adjustment mechanisms 20 are variously changed are input to the machine learning unit 41 as learning data 42. The machine learning unit 41 generates a trained model 43 by machine learning the training data 42. The trained model 43 generated in this manner has learned the position of the air bubble 13 of the spirit level 10 placed on the EFEM 205 in the spirit level 10 relative to the adjustment amount of the level adjustment mechanism 20.

[0033] 9 , in the second embodiment, the trained model 43 is generated by machine learning an image of the level 10 placed on the EFEM 205 in a deflected state. That is, the image capturing unit 30 captures an image of the level 10 placed on the EFEM 205 in a deflected state while varying the adjustment amounts of the multiple level adjustment mechanisms 20. That is, changing the adjustment amounts of the level adjustment mechanisms 20 changes the weight balance of the EFEM 205, and therefore the deflected state of the EFEM 205 changes. Therefore, the adjustment amounts of the level adjustment mechanisms 20 and the inclination of the level 10 are not simply proportional to each other. Therefore, it is necessary to train the EFEM 205 in a deflected state.

[0034] The operation of the control unit 40 for acquiring the adjustment amount of the level adjustment mechanism 20 will be described. As shown in FIG. 8 , in the second embodiment, the control unit 40 acquires the adjustment amount of each of the multiple level adjustment mechanisms 20 based on an image of the level 10 by using a trained model 43 generated by machine learning. Specifically, the control unit 40 acquires the adjustment amount of each of the multiple level adjustment mechanisms 20 based on an image of the level 10 captured by the imaging unit 30 by using the trained model 43. For example, as shown in FIGS. 10 and 11 , the imaging unit 30 captures an image of the level 10 arranged on the upper surface of the EFEM 205. The imaging unit 30 also captures an image of not only the level 10 but also the EFEM 205. The captured image is then input to the trained model 43. The trained model 43 estimates the adjustment amount of each of the multiple level adjustment mechanisms 20 to level the EFEM 205 based on the input image. The adjustment amount of the level adjustment mechanism 20 is estimated for each of the multiple level adjustment mechanisms 20. The control unit 40 acquires the adjustment amount of the level adjustment mechanism 20 from the trained model 43. If the level adjustment mechanism 20 is an electric hydraulic jack, the adjustment amount acquired is the time or number of times that a switch for adjusting the amount of oil delivered from the electric pump is turned on. If the level adjustment mechanism 20 is a manual jack, the adjustment amount acquired is the number of times the handle is moved up and down. If the level adjustment mechanism 20 is an adjuster, the adjustment amount acquired is the number of rotations of the nut portion of the adjuster.

[0035] The configuration of the display unit 50 will be described. As shown in FIG. 6 , the display unit 50 is, for example, a liquid crystal display. The display unit 50 may be attached to the housing of the level adjustment device 100, or may be disposed separately from the housing of the level adjustment device 100. In the second embodiment, the display unit 50 displays the adjustment amounts of each of the multiple level adjustment mechanisms 20 acquired by the control unit 40. That is, the control unit 40 executes a process of displaying the acquired adjustment amounts of each of the multiple level adjustment mechanisms 20 on the display unit 50. Then, the operator adjusts the multiple level adjustment mechanisms 20 based on the adjustment amounts of each of the multiple level adjustment mechanisms 20 displayed on the display unit 50.

[0036] Next, a level adjustment method according to the second embodiment will be described with reference to Fig. 12. The level adjustment method is a method for leveling the EFEM 205 by adjusting a plurality of level adjustment mechanisms 20. In the second embodiment, the adjustment of the level adjustment mechanisms 20 is performed by an operator.

[0037] In step S1, a trained model 43 is generated. In the second embodiment, the trained model 43 is generated by machine learning data related to the inclination of the EFEM 205 detected by the level 10 when the level 10 is placed on the EFEM 205. Specifically, training data 42 for generating the trained model 43 is prepared. The training data 42 is a plurality of images of the level 10 and the EFEM 205 captured by the imaging unit 30 when the adjustment amounts of the plurality of level adjustment mechanisms 20 are changed in various ways. The training data 42 is then input to the machine learning unit 41 by the operator, and the machine learning unit 41 generates the trained model 43.

[0038] A case where the level adjustment mechanisms 20 are floating above the floor surface 1 will be described. When the level adjustment mechanisms 20 are arranged at the four corners of the EFEM 205, the EFEM 205 may be leveled by the level adjustment mechanisms 20 arranged at three corners, while the level adjustment mechanism 20 arranged at the remaining corner may be floating above the floor surface 1. Therefore, the trained model 43 has also learned the adjustment amounts of the level adjustment mechanisms 20 in a state where the EFEM 205 is leveled by the level adjustment mechanisms 20 arranged at three corners, while the level adjustment mechanism 20 arranged at the remaining corner is floating above the floor surface 1. This prevents the trained model 43 from estimating the adjustment amounts of the level adjustment mechanisms 20 such that the EFEM 205 is leveled by the level adjustment mechanisms 20 arranged at three corners, while the level adjustment mechanism 20 arranged at the remaining corner is floating above the floor surface 1.

[0039] In step S2, the control unit 40 acquires data relating to the inclination of the EFEM 205 with respect to the horizontal plane from the level 10 placed on the EFEM 205. Specifically, the worker places the level 10 on the EFEM 205. Then, the imaging unit 30 captures an image of the level 10 together with the EFEM 205. The control unit 40 acquires an image of the level 10 and the EFEM 205 from the imaging unit 30 as data relating to the inclination of the EFEM 205 with respect to the horizontal plane.

[0040] In step S3, the control unit 40 uses the trained model 43 generated by machine learning to acquire the adjustment amounts of each of the multiple level adjustment mechanisms 20 based on data related to the tilt of the EFEM 205 detected by the level 10. Specifically, the control unit 40 inputs the images of the level 10 and the EFEM 205 acquired in step S2 into the trained model 43. Then, based on the input images, the trained model 43 estimates the adjustment amounts of each of the multiple level adjustment mechanisms 20 to level the EFEM 205, and the control unit 40 acquires the estimated adjustment amounts of each of the multiple level adjustment mechanisms 20.

[0041] In step S4, the control unit 40 executes a process of displaying the acquired adjustment amounts of each of the multiple level adjustment mechanisms 20 on the display unit 50. The worker adjusts the multiple level adjustment mechanisms 20 based on the adjustment amounts of each of the multiple level adjustment mechanisms 20 displayed on the display unit 50. If the EFEM 205 is not level even after adjusting the multiple level adjustment mechanisms 20, the operations from steps S2 to S4 are repeated. For example, the worker operates the level adjustment device 100 so as to repeat the operations from steps S2 to S4 while checking the level 10.

[0042] Effect of the Second Embodiment A plurality of level adjustment mechanisms 20 are disposed below the EFEM 205. The level adjustment device 100 includes a control unit 40 that acquires the adjustment amount of each of the plurality of level adjustment mechanisms 20 based on an image of the level 10 disposed on the EFEM 205 captured by the imaging unit 30. The display unit 50 displays the adjustment amount of each of the plurality of level adjustment mechanisms 20 acquired by the control unit 40. This allows an operator to easily adjust the plurality of level adjustment mechanisms 20 based on the adjustment amount of each of the plurality of level adjustment mechanisms 20 displayed on the display unit 50. Furthermore, unlike a case in which an operator visually checks the level 10 and another operator adjusts the plurality of level adjustment mechanisms 20, the EFEM 205 can be leveled by a single operator.

[0043] The control unit 40 uses the trained model 43 generated by machine learning to acquire the adjustment amount for each of the multiple level adjustment mechanisms 20 based on the image of the spirit level 10 captured by the imaging unit 30. In this way, machine learning can learn the actual state of the EFEM 205, such as a state in which the EFEM 205 is bent, in association with the adjustment amounts for the multiple level adjustment mechanisms 20. Therefore, by using the trained model 43 trained in this way, it is possible to accurately acquire the adjustment amount for horizontally positioning the EFEM 205, taking into account the actual state of the EFEM 205.

[0044] The trained model 43 is generated by machine learning an image of the level 10 placed in the EFEM 205. As a result, an image of the level 10 in a state in which the level 10 is actually placed in the EFEM 205 is machine learned, and therefore the trained model 43 is a trained model 43 that takes into account the actual state of the EFEM 205. In other words, simply by actually placing the level 10 in the EFEM 205, it is possible to easily generate a trained model 43 that takes into account the actual state of the EFEM 205.

[0045] The trained model 43 is generated by machine learning an image of the spirit level 10 placed on the EFEM 205 in a deflected state. This makes it possible to generate a trained model 43 that takes into account changes in the deflection of the EFEM 205 caused by changes in the adjustment amount of the level adjustment mechanism 20.

[0046] The trained model 43 is generated by machine learning images of the spirit level 10 captured by the imaging unit 30 when the adjustment amount of at least one of the multiple level adjustment mechanisms 20 is changed. As a result, images of the spirit level 10 when the level adjustment mechanisms 20 are adjusted when the weight of the EFEM 205 acting on the multiple level adjustment mechanisms 20 is not uniform are also trained, so the adjustment amount of the EFEM 205 can be learned with high accuracy.

[0047] Third Embodiment A level adjustment device 110 according to a third embodiment will be described. In the third embodiment, an electric hydraulic jack 111 serving as a level adjustment mechanism is controlled by a control unit 112.

[0048] The configuration of a level adjustment device 110 according to the third embodiment will be described. As shown in Fig. 13 , the level adjustment device 110 has a plurality of electric hydraulic jacks 111 arranged as a level adjustment mechanism. As shown in Fig. 14 , an output unit 301 of the level adjustment device 110 outputs an image of the spirit level 10 captured by the imaging unit 30 to a display unit 302 via a wiring 303. The display unit 302 may be included in the level adjustment device 110.

[0049] Next, a level adjustment method according to the third embodiment will be described with reference to Fig. 15. The operations of steps S1, S2 and S3 are the same as those of steps S1, S2 and S3 in the second embodiment.

[0050] In step S14, the control unit 40 operates the multiple electric hydraulic jacks 111 based on the acquired adjustment amounts of each of the multiple electric hydraulic jacks 111, thereby adjusting the inclination of the EFEM 205 so that the EFEM 205 is aligned with the horizontal plane.

[0051] In step S15, the control unit 40 determines whether the EFEM 205 is level. Specifically, after adjusting the multiple electric hydraulic jacks 111, the control unit 40 causes the imaging unit 30 to capture an image of the spirit level 10, and determines whether the EFEM 205 is level based on the image captured by the imaging unit 30. If the answer is no in step S15, the process returns to step S3. If the answer is yes in step S15, the level adjustment operation by the control unit 40 ends.

[0052] [Effects of the Third Embodiment] The control unit 112 adjusts the inclination of the EFEM 205 so that the EFEM 205 is aligned with the horizontal plane by operating the multiple electric hydraulic jacks 111 based on the acquired adjustment amounts of each of the multiple electric hydraulic jacks 111. This eliminates the need for an operator to manually adjust the multiple electric hydraulic jacks 111, thereby reducing the operator's workload.

[0053] [Modifications] The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present disclosure is defined by the claims, not by the description of the above-mentioned embodiments, and includes all modifications (modifications) within the meaning and scope of the claims.

[0054] In the first, second, and third embodiments, examples have been shown in which the present disclosure is applied to an analog level 10 having a container 11, a liquid 12, and an air bubble 13, but the present disclosure is not limited to this. For example, an analog level 10 other than the analog level 10 having a container 11, a liquid 12, and an air bubble 13 may be applied to the present disclosure.

[0055] In the first, second, and third embodiments described above, an example has been shown in which the EFEM 205 is applied as the object to be adjusted according to the present disclosure, but the present disclosure is not limited thereto. The present disclosure may be applied to an object to be adjusted other than the EFEM 205. For example, the level adjustment device 300 may be a device that assists an operator in leveling the transfer chamber 204 with the floor surface 1.

[0056] In the second embodiment, an example has been described in which the trained model 43 is generated based on an image of one level 10 placed in the EFEM 205, but the present disclosure is not limited to this. For example, a plurality of level 10 may be placed in the EFEM 205, and the trained model 43 may be generated based on images of the plurality of level 10. The same applies to the third embodiment.

[0057] In the second embodiment described above, an example was shown in which the level adjustment device 100 includes the machine learning unit 41, but the present disclosure is not limited to this. For example, the trained model 43 may be generated by a machine learning unit 41 arranged in an external device other than the level adjustment device 100. The same applies to the third embodiment.

[0058] In the second and third embodiments described above, an example was shown in which an image of the spirit level 10 placed on the EFEM 205 in a deflected state was learned, but the present disclosure is not limited to this. For example, if the EFEM 205 is of a size that does not deflect, it is not necessary to learn an image of the spirit level 10 placed on the EFEM 205 in a deflected state.

[0059] In the second embodiment described above, the control unit 40 uses the trained model 43 generated by machine learning to acquire the adjustment amount of each of the multiple level adjustment mechanisms 20 based on the image of the spirit level 10, but the present disclosure is not limited to this. For example, the control unit 40 may acquire the adjustment amount of each of the multiple level adjustment mechanisms 20 by image processing of the image of the spirit level 10 without using the trained model 43.

[0060] In the first and second embodiments, the level adjustment mechanisms 20 are disposed at the four lower corners of the EFEM 205, but the present disclosure is not limited to this. For example, the level adjustment mechanisms 20 may be disposed at the center of the EFEM 205 in addition to the four lower corners. The number of level adjustment mechanisms 20 may be one, two, or three. The same applies to the third embodiment.

[0061] In the first embodiment described above, an example has been shown in which the output unit 301 outputs the image of the spirit level 10 captured by the imaging unit 30 to the display unit 302. However, the present disclosure is not limited to this. For example, the output unit 301 may output the image of the spirit level 10 to a device other than the display unit 302.

[0062] Furthermore, when the electric hydraulic jacks 111 are controlled by the control unit 112 as in the third embodiment, it is possible to determine whether the electric hydraulic jacks 111 are floating above the floor surface 1. Specifically, when the electric hydraulic jacks 111 are arranged at the four corners below the EFEM 205, the EFEM 205 can be leveled by three of the electric hydraulic jacks 111 arranged at the four corners. In this case, the remaining electric hydraulic jack 111 may be floating above the floor surface 1. Therefore, while the EFEM 205 is leveled, the control unit 40 increases the height of the electric hydraulic jacks 111 arranged at the four corners one by one, and the imaging unit 30 captures an image of the spirit level 10. When the control unit 40 determines, based on the image captured by the imaging unit 30, that the horizontal state of the EFEM 205 is maintained even when the height of the electric hydraulic jack 111 is increased, the control unit 40 can determine that the electric hydraulic jack 111 is floating above the floor surface 1. This makes it possible to prevent the EFEM 205 from being placed in an unstable state in which the electric hydraulic jack 111 placed at one corner is floating above the floor surface 1.

[0063] The functions of the elements disclosed herein can be performed using circuits or processing circuits, including general-purpose processors, special-purpose processors, integrated circuits, ASICs (Application Specific Integrated Circuits), conventional circuits, and / or combinations thereof, configured or programmed to perform the disclosed functions. A processor is considered a processing circuit or circuit because it includes transistors and other circuitry. In this disclosure, a circuit, unit, or means is hardware that performs the recited functions or hardware that is programmed to perform the recited functions. The hardware may be hardware disclosed herein or other known hardware that is programmed or configured to perform the recited functions. Where the hardware is a processor, which is considered a type of circuit, the circuit, means, or unit is a combination of hardware and software, and the software is used to configure the hardware and / or processor.

[0064] Aspects It will be appreciated by those skilled in the art that the exemplary embodiments described above are examples of the following aspects.

[0065] (Aspect 1) A level adjustment device comprising: an analog level that allows visual confirmation of the inclination of an object to be adjusted relative to a horizontal plane; an imaging unit that images the level; and an output unit that outputs the image of the level captured by the imaging unit.

[0066] (Aspect 2) The level adjustment device according to Aspect 1, wherein the level has a liquid contained in a container and an air bubble contained in the liquid, and the imaging unit images the container, the liquid, and the air bubble of the level.

[0067] (Aspect 3) The level adjustment device according to Aspect 1 or Aspect 2, wherein a level adjustment mechanism is disposed on the object to be adjusted, and the level adjustment device further comprises a control unit that acquires an adjustment amount of the level adjustment mechanism based on an image of the spirit level disposed on the object to be adjusted captured by the imaging unit.

[0068] (Aspect 4) The level adjustment device according to aspect 3, further comprising an adjustment amount display unit that displays the adjustment amount of the level adjustment mechanism acquired by the control unit.

[0069] (Aspect 5) The level adjustment device according to Aspect 3 or Aspect 4, wherein the control unit acquires the adjustment amount of the level adjustment mechanism by using a trained model that receives an input of an image of the spirit level placed on the object to be adjusted captured by the imaging unit and outputs an adjustment amount of the level adjustment mechanism.

[0070] (Aspect 6) The level adjustment device according to Aspect 5, wherein the trained model is generated by machine learning an image of the spirit level placed on the object to be adjusted in a bent state.

[0071] (Aspect 7) The level adjustment device according to Aspect 5 or Aspect 6, wherein a plurality of the level adjustment mechanisms are arranged, and the trained model is generated by machine learning images of the spirit level captured by the imaging unit when the adjustment amount of at least one of the plurality of level adjustment mechanisms is changed.

[0072] (Aspect 8) The level adjustment device according to Aspect 7, wherein the plurality of level adjustment mechanisms are respectively arranged at four corners below the object to be adjusted, and the control unit identifies a level adjustment mechanism floating above the floor surface based on an image of the spirit level captured by the imaging unit when the adjustment amount of the level adjustment mechanism located at one corner is changed.

[0073] (Aspect 9) A level adjustment device according to any one of Aspects 3 to 8, wherein the level adjustment mechanism includes an electric hydraulic jack, and the control unit operates the electric hydraulic jack based on the acquired adjustment amount of each of the level adjustment mechanisms, thereby adjusting the inclination of the object to be adjusted so that the object is aligned with a horizontal plane.

[0074] (Aspect 10) The level adjustment device according to any one of Aspects 1 to 9, wherein the object to be adjusted includes a semiconductor manufacturing device.

[0075] (Aspect 11) The level adjustment device according to any one of Aspects 1 to 10, wherein the output unit outputs an image of the level captured by the imaging unit to a display unit.

[0076] (Aspect 12) A level adjustment method for a level adjustment device including an analog level, an imaging unit, and an output unit, the imaging unit capturing an image of the analog level, which allows the tilt of an object to be adjusted relative to a horizontal plane to be visually confirmed, and the output unit outputting the image of the level captured by the imaging unit.

Claims

1. A level adjustment device comprising: an analog level gauge that allows the inclination of an object to be adjusted relative to a horizontal plane to be visually confirmed; an imaging unit that images the level gauge; and an output unit that outputs the image of the level gauge captured by the imaging unit.

2. A level adjustment device as described in claim 1, wherein the spirit level has a liquid contained in a container and air bubbles contained in the liquid, and the imaging unit images the container, the liquid and the air bubbles of the spirit level.

3. A level adjustment device as described in claim 1, comprising: a level adjustment mechanism disposed on the object to be adjusted; and a control unit that acquires the adjustment amount of the level adjustment mechanism based on an image of the spirit level disposed on the object to be adjusted captured by the imaging unit.

4. The level adjustment device according to claim 3, further comprising an adjustment amount display unit that displays the adjustment amount of the level adjustment mechanism acquired by the control unit.

5. A level adjustment device as described in claim 3, wherein the control unit acquires the adjustment amount of the level adjustment mechanism by using a trained model that inputs an image of the spirit level placed on the object to be adjusted captured by the imaging unit and outputs the adjustment amount of the level adjustment mechanism.

6. The level adjustment device according to claim 5, wherein the trained model is generated by machine learning an image of the spirit level placed on the object to be adjusted in a bent state.

7. The level adjustment device described in claim 5, wherein the level adjustment mechanisms are arranged in a plurality of locations, and the trained model is generated by machine learning images of the spirit level captured by the imaging unit when the adjustment amount of at least one of the plurality of level adjustment mechanisms is changed.

8. The level adjustment device according to claim 7, wherein the plurality of level adjustment mechanisms are respectively arranged at four corners below the object to be adjusted, and the control unit identifies a level adjustment mechanism floating above the floor surface based on an image of the spirit level captured by the imaging unit when the adjustment amount of the level adjustment mechanism located at one corner is changed.

9. A level adjustment device as described in claim 3, wherein the level adjustment mechanism includes an electric hydraulic jack, and the control unit adjusts the inclination of the object to be adjusted so that the object is aligned with a horizontal plane by operating the electric hydraulic jack based on the adjustment amount of each of the level adjustment mechanisms obtained.

10. The level adjustment device according to claim 1, wherein the object to be adjusted includes a semiconductor manufacturing device.

11. The level adjustment device according to claim 1, wherein the output section outputs the image of the level captured by the imaging section to a display section.

12. A level adjustment method for a level adjustment device equipped with an analog level, an imaging unit, and an output unit, comprising: the imaging unit capturing an image of the analog level, which allows the inclination of the object to be adjusted relative to a horizontal plane to be visually confirmed; and the output unit outputting an image of the level captured by the imaging unit.

Images