Ion implantation apparatus and ion implantation method

Abstract

The present invention can accelerate the adjustment of action parameters. An ion implantation device is provided with: a beam generating device that generates an ion beam to be irradiated to a workpiece; a control device (52) that sets a plurality of action parameters for controlling the action of the beam generating device; a measuring device that measures at least one beam characteristic of the ion beam; a storage device (56) that accumulates data sets that correspondingly associate a set of the set values of the plurality of action parameters with a measured value of at least one beam characteristic of the ion beam; and an analysis device (54) that generates a function for calculating at least one beam characteristic from the set value of at least one specific parameter included in the plurality of action parameters, based on the plurality of data sets accumulated in the storage device (56). When the set value of at least one specific parameter included in the plurality of action parameters is changed, the control device (52) inputs the changed set value of at least one specific parameter to the function to calculate the calculated value of at least one beam characteristic.

Description

Technical Field

[0001] This application claims priority based on Japanese Patent Application No. 2021-019204, filed on February 9, 2021. The entire contents of that Japanese application are incorporated herein by reference.

[0002] This invention relates to an ion implantation device and an ion implantation method. Background Technology

[0003] In semiconductor manufacturing, a standard procedure is performed to implant ions into a semiconductor wafer (also known as ion implantation) to alter its conductivity, crystal structure, or other properties. The apparatus used in this process is called an ion implantation unit. An ion implantation unit is configured to measure beam characteristics such as the beam current or beam angle of the ion beam to be irradiated onto the wafer, and adjust operating parameters based on these measurements to achieve the desired beam characteristics.

[0004] Patent Document 1: Japanese Patent Application Publication No. 2020-161470

[0005] In recent years, the required precision of beam characteristics has become more stringent, sometimes resulting in time-consuming adjustments to achieve the desired beam characteristics. Furthermore, even using operating parameters from previous examples, it is sometimes impossible to achieve the previously obtained beam characteristics, necessitating repeated, time-consuming measurements and adjustments. If this adjustment time increases, the productivity of the ion implantation device decreases. Summary of the Invention

[0006] One exemplary objective of one embodiment of the present invention is to provide a technique for adjusting acceleration parameters.

[0007] An ion implantation apparatus according to one embodiment of the present invention includes: a beam generating apparatus for generating an ion beam irradiating a workpiece; a control device for setting a plurality of operating parameters for controlling the operation of the beam generating apparatus; a measuring device for measuring at least one beam characteristic of the ion beam; a storage device for accumulating a dataset that establishes a corresponding association between the set values ​​of the plurality of operating parameters and the measured values ​​of at least one beam characteristic of the ion beam; and an analysis device for generating a function based on the plurality of datasets accumulated in the storage device for estimating at least one beam characteristic based on the set value of at least one specific parameter included in the plurality of operating parameters. When the set value of at least one specific parameter included in the plurality of operating parameters is changed, the control device inputs the changed set value of at least one specific parameter to the function and calculates the estimated value of at least one beam characteristic.

[0008] Another embodiment of the present invention is an ion implantation method. This method comprises the following steps: accumulating a dataset, wherein the dataset is formed by establishing a corresponding association between a set of set values ​​of multiple action parameters for controlling the operation of a beam generating device for generating an ion beam and measured values ​​of at least one beam characteristic in the ion beam; classifying the accumulated datasets into multiple clusters; generating multiple functions corresponding to each of the multiple clusters, wherein the multiple functions are used to calculate at least one beam characteristic based on the set value of at least one specific parameter included in the multiple action parameters; when changing the set value of at least one specific parameter included in the multiple action parameters of the beam generating device, determining which of the multiple clusters the multiple action parameters containing the set value before or after the change of the at least one specific parameter are classified into; and inputting the changed set value of at least one specific parameter into the function corresponding to the determined cluster, and calculating the calculated value of at least one beam characteristic.

[0009] Furthermore, any combination of the above-mentioned constituent elements or the constituent elements or expressions of the present invention that can be substituted for each other in the method, apparatus, system, etc., is equally effective as an embodiment of the present invention.

[0010] Invention Effects

[0011] According to the present invention, the adjustment of motion parameters can be accelerated. Attached Figure Description

[0012] Figure 1 This is a top view showing the general structure of the ion implantation apparatus according to the embodiment.

[0013] Figure 2 A block diagram illustrating the functional structure of the central control unit.

[0014] Figure 3 This is a flowchart illustrating an example of a method for adjusting motion parameters.

[0015] Figure 4 This is a flowchart illustrating an example of a method for adjusting beam characteristics.

[0016] Figure 5 A graph illustrating the relationship between a specific parameter and beam characteristics.

[0017] Figure 6 A graph illustrating the relationship between specific parameters and beam characteristics.

[0018] Figure 7 A diagram illustrating classification methods for multiple datasets.

[0019] Figure 8 This diagram illustrates an example of a method for calculating beam characteristics.

[0020] In the diagram: 12-Ion generation unit, 14-Beam acceleration unit, 16-Beam deflection unit, 18-Beam delivery unit, 20-Substrate transfer and processing unit, 22a, 22b, 22c-Linear acceleration device, 23-Beam measurement unit, 24-Energy analysis electromagnet, 26-Lateral converging quadrupole lens, 30-Deflection electromagnet, 32-Beam shaper, 34-Beam scanner, 36-Beam parallelizer, 38-Final energy filter, 41-Beam monitor, 42-Beam analyzer, 90-Beam generation device, 100-Ion implantation device. Detailed Implementation

[0021] Hereinafter, the embodiments for carrying out the present invention will be described in detail with reference to the accompanying drawings. Furthermore, the same symbols are used to denote the same elements in the description of the drawings, and repeated descriptions are omitted. Also, the structures described below are examples and do not limit the scope of the present invention in any way.

[0022] Before detailing the implementation method, a general overview is provided. The ion implantation apparatus according to this embodiment includes: a beam generation apparatus for generating an ion beam that irradiates a wafer; a control device for setting multiple operating parameters for controlling the operation of the beam generation apparatus; and a measurement device for measuring at least one beam characteristic of the ion beam. Before the ion implantation process of irradiating the wafer with the ion beam, the control device pre-adjusts the operating parameters to generate an ion beam with desired beam characteristics. For example, after setting the operating parameters, at least one beam characteristic is measured; if the measured value of the beam characteristic deviates from a target value, at least one operating parameter is adjusted to bring the beam characteristic closer to the target value.

[0023] The aforementioned adjustment process requires performing adjustments on all multiple beam characteristics of the ion beam. These multiple beam characteristics refer to beam energy, beam current, beam current density distribution, beam size, beam angle, beam parallelism, etc. In recent years, the required precision of these beam characteristics has become more stringent, demanding high-precision adjustment of each individual beam characteristic. On the other hand, measuring each beam characteristic separately and then adjusting the operating parameters with high precision based on the measured values ​​becomes extremely time-consuming, leading to a decrease in the productivity of the ion implantation unit.

[0024] Therefore, in this embodiment, at least one beam characteristic can be estimated instead of measured. This allows for the omission (skipping) of measuring at least one beam characteristic and adjustment based on the estimated value. Specifically, a function is generated to estimate at least one beam characteristic based on set values ​​of multiple operating parameters set in the beam generation device, and this function is used to estimate at least one beam characteristic. This function is generated based on multiple datasets accumulated during the use of the ion implantation device. Each dataset is a dataset that establishes a corresponding association between the set values ​​of multiple operating parameters and the measured values ​​of at least one beam characteristic. By using this function, even after changing the operating parameters and not measuring the beam characteristic, it is possible to estimate whether the beam characteristic meets the desired conditions.

[0025] Figure 1 This is a top view of the ion implantation apparatus 100 according to the embodiment for schematic representation. The ion implantation apparatus 100 includes a beam generation apparatus 90. The beam generation apparatus 90 includes an ion generation unit 12, a beam acceleration unit 14, a beam deflection unit 16, and a beam delivery unit 18. The ion implantation apparatus 100 also includes a substrate transfer processing unit 20. In this specification, the ion generation unit 12, the beam acceleration unit 14, the beam deflection unit 16, and the beam delivery unit 18 are collectively referred to as "beam generation apparatus 90".

[0026] The ion generation unit 12 includes an ion source 10 and a mass spectrometry analysis device 11. In this specification, the ion generation unit 12 is also referred to as the "ion generation device". In the ion generation unit 12, an ion beam is drawn from the ion source 10, and the drawn ion beam undergoes mass spectrometry analysis via the mass spectrometry analysis device 11. The mass spectrometry analysis device 11 includes a mass spectrometry magnet 11a and a mass spectrometry slit 11b. The mass spectrometry slit 11b is located downstream of the mass spectrometry magnet 11a. Based on the mass spectrometry analysis results from the mass spectrometry analysis device 11, only the desired ion species are selected for implantation, and the ion beams of the selected ion species are guided to the next beam acceleration unit 14.

[0027] The beam acceleration unit 14 includes multiple linear acceleration devices 22a, 22b, and 22c for accelerating the ion beam, and a beam measurement unit 23, forming a linearly extending portion of the beamline BL. Each of the multiple linear acceleration devices 22a to 22c has at least one high-frequency acceleration unit, and applies a high-frequency (RF) electric field to the ion beam to accelerate it. The beam measurement unit 23 is located at the downstream end of the beam acceleration unit 14 and measures at least one beam characteristic of the high-energy ion beam accelerated by the multiple linear acceleration devices 22a to 22c. The beam measurement unit 23 can also be a measuring device for measuring beam characteristics such as beam energy, beam current, and beam distribution.

[0028] In this embodiment, three linear acceleration devices 22a to 22c are provided. The first linear acceleration device 22a is located at the upper stage of the beam acceleration unit 14 and includes multiple stages (e.g., 5 to 15 stages) of high-frequency acceleration. The first linear acceleration device 22a performs "bunching," aligning the continuous beam (DC beam) output from the ion generation unit 12 to a specific acceleration phase, for example, accelerating the ion beam to an energy of approximately 1 MeV. The second linear acceleration device 22b is located at the middle stage of the beam acceleration unit 14 and includes multiple stages (e.g., 5 to 15 stages) of high-frequency acceleration. The second linear acceleration device 22b accelerates the ion beam output from the first linear acceleration device 22a to an energy of, for example, approximately 2 to 3 MeV. The third linear acceleration device 22c is located at the lower stage of the beam acceleration unit 14 and includes multiple stages (e.g., 5 to 15 stages) of high-frequency acceleration. The third linear accelerator 22c accelerates the ion beam output from the second linear accelerator 22b to high energies, for example, above 4 MeV.

[0029] The high-energy ion beam output from the beam acceleration unit 14 has a certain range of energy distribution. Therefore, in order to reciprocate and scan the high-energy ion beam downstream of the beam acceleration unit 14 and parallelize it to irradiate the wafer, it is necessary to perform high-precision energy analysis, energy dispersion control, trajectory correction, and beam convergence and divergence adjustment in advance.

[0030] The beam deflection unit 16 performs energy analysis, energy dispersion control, and trajectory correction of the high-energy ion beam output from the beam acceleration unit 14. The beam deflection unit 16 constitutes the arc-shaped extension of the beamline BL. The direction of the high-energy ion beam is converted by the beam deflection unit 16 and directed toward the beam delivery unit 18.

[0031] The beam deflection unit 16 includes an energy analysis electromagnet 24, a lateral converging quadrupole lens 26 to suppress energy dispersion, an energy analysis slit 27, a first Faraday cup 28, a deflection electromagnet 30 to provide steering (track correction), and a second Faraday cup 31. The energy analysis electromagnet 24 is also referred to as an energy filtering electromagnet (EFM). Furthermore, the assembly consisting of the energy analysis electromagnet 24, the lateral converging quadrupole lens 26, the energy analysis slit 27, and the first Faraday cup 28 is collectively referred to as an "energy analysis device".

[0032] The energy analysis slit 27 can be configured with a variable slit width to adjust the resolution of the energy analysis. The energy analysis slit 27 may be composed of two shielding bodies capable of moving in the slit width direction, and the slit width can be adjusted by changing the interval between the two shielding bodies. The energy analysis slit 27 can also be configured to have a variable slit width by selecting any one of a plurality of slits with different widths.

[0033] The first Faraday cup 28 is positioned immediately behind the energy analysis slit 27 and is used for measuring the beam current for energy analysis. The second Faraday cup 31 is positioned immediately behind the deflecting electromagnet 30 and is configured to measure the beam current of the ion beam entering the beam delivery unit 18 after trajectory correction. Both the first Faraday cup 28 and the second Faraday cup 31 are configured to move in and out of the beamline BL via the operation of a Faraday cup drive unit (not shown). Both the first Faraday cup 28 and the second Faraday cup 31 can also be used as measuring devices for measuring beam characteristics such as beam current or beam distribution.

[0034] The beam delivery unit 18 constitutes another straight extension of the beamline BL, and runs parallel to the beam acceleration unit 14 across the maintenance area MA in the center of the device. The length of the beam delivery unit 18 is designed to be approximately the same as the length of the beam acceleration unit 14. As a result, the beamline BL, composed of the beam acceleration unit 14, the beam deflection unit 16, and the beam delivery unit 18, forms a U-shaped layout. In this specification, the beam delivery unit 18 is also referred to as the "beamline device".

[0035] The beam delivery unit 18 includes a beam shaper 32, a beam scanner 34, a beam collector 35, a beam parallelizer 36, a final energy filter 38, and left and right Faraday cups 39L and 39R.

[0036] The beam shaper 32 includes converging / diverging lenses such as quadrupole lenses (Q lenses) and is configured to shape the ion beam passing through the beam deflection unit 16 into a desired cross-sectional shape. The beam shaper 32 may be constructed, for example, by an electric field-type triple quadrupole lens (also called a triple Q lens), which has three electrostatic quadrupole lenses. By using the three lens devices, the beam shaper 32 can independently adjust the convergence or divergence of the ion beam in both the horizontal (x-direction) and vertical (y-direction) directions. The beam shaper 32 may include magnetic field lenses, or it may include lenses that utilize both electric and magnetic fields to shape the beam.

[0037] The beam scanner 34 is a beam deflection device configured to provide reciprocating scanning of the beam and to scan the shaped ion beam in the x-direction. The beam scanner 34 has a pair of scanning electrodes facing each other in the beam scanning direction (x-direction). The scanning electrode pair is connected to a variable voltage power supply (not shown), and by periodically changing the voltage applied between the scanning electrode pair, the electric field generated between the electrodes is changed, thereby deflecting the ion beam at various angles. As a result, the ion beam scans throughout the scanning range indicated by arrow X. Figure 1 In the diagram, multiple trajectories of the ion beam within the scanning range are represented by thin solid lines. Furthermore, the beam scanner 34 can be replaced with other beam scanning devices, which can also be configured as a magnet device utilizing a magnetic field.

[0038] The beam scanner 34 directs the ion beam to a beam collector 35 located away from the beam line BL by deflecting the beam beyond the scanning range indicated by arrow X. The beam scanner 34 blocks the ion beam by temporarily avoiding the beam line BL by directing the ion beam toward the beam collector 35, thus preventing the ion beam from reaching the downstream substrate transfer processing unit 20.

[0039] The beam parallelizer 36 is configured to make the travel direction of the scanned ion beam parallel to the designed trajectory of the beam line BL. The beam parallelizer 36 has multiple arc-shaped parallelizing lens electrodes with the ion beam passing through a slit at the center. The parallelizing lens electrodes are connected to a high-voltage power supply (not shown), and an electric field generated by the applied voltage is applied to the ion beam to achieve parallelism in its travel direction. Alternatively, the beam parallelizer 36 can be replaced with other beam parallelizing devices, which can also be configured as a magnetic device utilizing a magnetic field.

[0040] The final energy filter 38 is configured to analyze the energy of the ion beam and deflect ions of the required energy downwards (in the -y direction) to guide them to the substrate transport processing unit 20. The final energy filter 38 is sometimes referred to as an angle energy filter (AEF) and has an AEF electrode pair for electric field deflection. The AEF electrode pair is connected to a high-voltage power supply (not shown). By applying a positive voltage to the upper AEF electrode and a negative voltage to the lower AEF electrode, the ion beam is deflected downwards. Alternatively, the final energy filter 38 can be constructed from a magnetic field deflection magnet device, or from a combination of the electric field deflection AEF electrode pair and the magnetic field deflection magnet device.

[0041] The left and right Faraday cups 39L and 39R are located downstream of the final energy filter 38 and positioned at the left and right ends of the scanning range indicated by arrow X, where the beam can enter. The left and right Faraday cups 39L and 39R are positioned so as not to obstruct the beam directed toward the wafer W, and the beam current is measured during ion implantation of the wafer W.

[0042] A substrate transfer processing unit 20 is provided downstream of the beam delivery unit 18, i.e., at the very downstream of the beam line BL. The substrate transfer processing unit 20 includes an implantation processing chamber 40, a beam monitor 41, a beam analyzer 42, an analyzer drive 43, a substrate transfer device 44, and a loading port 46. A platform drive device (not shown) is provided in the implantation processing chamber 40 to hold the wafer W during ion implantation and move the wafer W in a direction orthogonal to the beam scanning direction (x direction) (y direction).

[0043] A beam monitor 41 is located at the downstream end of the beamline BL inside the implantation processing chamber 40. The beam monitor 41 is positioned on the beamline BL where the ion beam can be incident when there is no wafer W, and is configured to measure beam characteristics before or during the ion implantation process. The beam monitor 41 can also be a measuring device for beam characteristics such as beam current, beam current density distribution, beam angle, and beam parallelism. For example, the beam monitor 41 is located near the transfer port (not shown) connecting the implantation processing chamber 40 and the substrate transfer device 44, and is positioned vertically below the transfer port.

[0044] The beam analyzer 42 is configured to measure the beam current at a position on the surface of the wafer W. The beam analyzer 42 is configured to move in the x-direction via the action of the analyzer drive device 43, avoiding the implantation position of the wafer W during ion implantation, and inserting into the implantation position when the wafer W is not in the implantation position. By measuring the beam current while moving in the x-direction, the beam analyzer 42 can measure the beam current across the entire beam scanning range in the x-direction. The beam analyzer 42 may have multiple Faraday cups arranged in an array in the x-direction to simultaneously measure the beam current at multiple positions in the beam scanning direction (x-direction). The beam analyzer 42 may also be a measuring device for measuring the beam current density distribution in the x-direction.

[0045] The beam analyzer 42 may include a single Faraday cup for measuring beam current, or an angle measuring device for measuring beam angle information. The angle measuring device may include, for example, a slit and multiple current detection units disposed away from the slit in the beam travel direction (z-direction). The angle measuring device, for example, measures the beam passing through the slit using multiple current detection units arranged in the slit width direction, and can determine the angular component of the beam in the slit width direction. The beam analyzer 42 may include a first angle measuring device capable of measuring angle information in the x-direction and a second angle measuring device capable of measuring angle information in the y-direction. The beam analyzer 42 may also be a measuring device for measuring the beam angle in the x-direction and the beam angle in the y-direction. The beam analyzer 42 can also measure angular centroid or convergence / divergence angles, etc., as beam angle information.

[0046] The substrate transfer device 44 is configured to transfer wafers W between the loading port 46 of the wafer container 45 and the implantation processing chamber 40. The loading port 46 is configured to simultaneously hold multiple wafer containers 45, for example, having four loading stages arranged in the x-direction. A wafer container transfer port (not shown) is provided vertically above the loading port 46 and is configured to allow wafer containers 45 to pass through in the vertical direction. The wafer containers 45 are automatically moved into the loading port 46 through the wafer container transfer port, for example, by a transfer robot installed on the ceiling or the like in a semiconductor manufacturing plant where the ion implantation device 100 is installed, and are automatically removed from the loading port 46.

[0047] The ion implantation apparatus 100 also includes a central control unit 50. The central control unit 50 controls the overall operation of the ion implantation apparatus 100. The central control unit 50 is implemented in hardware through components and mechanical devices, such as a computer's CPU and memory, and in software through computer programs. The various functions provided by the central control unit 50 can be achieved through the cooperation of hardware and software.

[0048] An operation panel 49 is provided near the central control unit 50. This operation panel 49 has a display device and an input device for setting the operating parameters of the ion implantation apparatus 100. The positions of the operation panel 49 and the central control unit 50 are not particularly limited; for example, they can be positioned adjacent to the entrance / exit 48 of the maintenance area MA between the ion generation unit 12 and the substrate transfer processing unit 20. By placing the ion source 10, loading port 46, operation panel 49, and central control unit 50—areas with high frequency of operation performed by personnel managing the ion implantation apparatus 100—adjacent to these locations, operational efficiency can be improved.

[0049] Figure 2 This is a block diagram schematically illustrating the functional structure of the central control unit 50. The central control unit 50 includes a control unit 52, an analysis unit 54, and a storage unit 56.

[0050] The control device 52 sets multiple operating parameters for controlling the operation of the beam generating device 90. The control device 52 includes an automatic adjustment unit 60, a measurement control unit 62, and a calculation unit 64. The automatic adjustment unit 60 executes an automatic adjustment program for adjusting the multiple operating parameters and adjusts the multiple operating parameters to achieve the desired beam characteristics. The measurement control unit 62 controls the operation of the measurement device and acquires measured values ​​of at least one beam characteristic. The calculation unit 64 calculates calculated values ​​of at least one beam characteristic using functions generated by the analysis device 54.

[0051] Analysis device 54 analyzes multiple datasets accumulated in storage device 56. Analysis device 54 includes a classification unit 66 and a function generation unit 68. Classification unit 66 classifies the multiple datasets into multiple clusters. Function generation unit 68 generates a function for estimating at least one beam characteristic for each cluster classified by classification unit 66. Function generation unit 68 generates multiple functions corresponding to each of the multiple clusters.

[0052] The storage device 56 accumulates a dataset that establishes a correspondence between setpoints of multiple operating parameters and measured values ​​of at least one beam characteristic. The storage device 56 establishes a correspondence between setpoints of multiple operating parameters adjusted by the automatic adjustment unit 60 and measured values ​​of at least one beam characteristic obtained from the measuring device, and stores this as a dataset. The storage device 56 accumulates multiple datasets generated during the use of the ion implantation device 100.

[0053] Figure 3 This is a flowchart illustrating an example of a method for adjusting motion parameters. First, initial values ​​(also called initial parameters) for multiple motion parameters are set (S10). Next, multiple beam characteristics of the ion beam are adjusted (S12-S20). Figure 3 In the example, the beam energy (S12), beam current (S14), beam angle (S16), beam parallelism (S18), and beam current density distribution are adjusted sequentially (S20). Finally, the adjusted dataset is saved (S22). Furthermore, the adjustment order of S12 to S20 is not limited and can be appropriately interchanged. Also, multiple adjustments of specific beam characteristics can be performed. For example, the second beam characteristic can be adjusted after the first beam characteristic is adjusted, and then the first beam characteristic can be readjusted.

[0054] In S10, for example, initial parameters corresponding to the beam characteristics targeted are determined. The automatic adjustment unit 60 can also determine the initial parameters through simulation experiments using a prescribed algorithm. The automatic adjustment unit 60 can also determine the initial parameters based on a dataset accumulated in the storage device 56. For example, if there is a previous dataset of ion beams with beam characteristics consistent with or approximating those of the target beam, the set values ​​of the operating parameters contained in that dataset can be used as the initial parameters.

[0055] In adjusting the beam energy in S12, the operating parameters of the ion generation unit 12 and the beam acceleration unit 14 are adjusted. Specifically, the extraction voltage of the ion source 10 and the high-frequency voltage V applied to each of the multi-stage high-frequency acceleration sections included in the beam acceleration unit 14 are adjusted. RF The amplitude, frequency, and phase of the beam are used to adjust the beam energy. The beam energy is measured, for example, by the beam measuring unit 23.

[0056] In adjusting the beam current in S14, the operating parameters of the ion generation unit 12 and the beam acceleration unit 14 are adjusted. Specifically, the beam current is adjusted by adjusting operating parameters such as the source gas flow rate, arc current, arc voltage, and source magnetocurrent of the ion source 10, and the slit opening width of the mass spectrometry analysis slit 11b and the energy analysis slit 27. The beam current is measured, for example, by the beam measurement unit 23, the first Faraday cup 28, the second Faraday cup 31, the beam monitor 41, or the beam analyzer 42.

[0057] In the beam angle adjustment in S16, the operating parameters of the beam deflection unit 16 and the beam delivery unit 18 are adjusted. For example, the center of gravity of the beam angle in the x-direction is adjusted by the magnetic current of the deflecting electromagnet 30. The center of gravity of the beam angle in the y-direction is adjusted by the applied voltage of the final energy filter 38. The convergence / divergence angles in the x and y directions are adjusted by the applied voltage of the Q lens included in the beam shaper 32. The beam size can also be adjusted by adjusting the applied voltage of the Q lens included in the beam shaper 32. The beam angle and beam size are measured, for example, by the beam monitor 41 or the beam analyzer 42.

[0058] In adjusting the beam parallelism in S18, the operating parameters of the beam delivery unit 18 are adjusted. Specifically, the applied voltage of the parallelizing lens electrode included in the beam parallelizer 36 is adjusted to adjust the beam parallelism. The beam parallelism is measured, for example, by a beam monitor 41 or a beam analyzer 42.

[0059] In adjusting the beam current density distribution in S20, the operating parameters of the beam delivery unit 18 are adjusted. Specifically, the voltage waveform applied to the scanning electrode pair included in the beam scanner 34 is adjusted to adjust the beam current density distribution in the x-direction. The beam current density distribution is measured, for example, by a beam monitor 41 or a beam analyzer 42.

[0060] In the adjustment steps S12 to S20, for example, the beam characteristics to be adjusted are measured, and at least one operating parameter is adjusted based on the measured value of the beam characteristics. The measurement control unit 62 activates the measuring device to acquire the measured value of the beam characteristics to be adjusted. If the measured value of the beam characteristics meets the desired conditions, the automatic adjustment unit 60 terminates the adjustment of the beam characteristics to be adjusted. If the measured value of the beam characteristics does not meet the desired conditions, the automatic adjustment unit 60 adjusts the set value of the operating parameter to make the beam characteristics meet the desired conditions.

[0061] In the adjustment processes S12 to S20, a calculated value of the beam characteristic can be used instead of measuring the beam characteristic to be adjusted, and at least one operating parameter can be adjusted based on the calculated value of the beam characteristic. The calculation unit 64 calculates the calculated value of at least one beam characteristic using a function generated by the function generation unit 68. As long as the calculated value of the beam characteristic meets the desired conditions, the automatic adjustment unit 60 skips the measurement of the beam characteristic to be adjusted and ends the adjustment of the beam characteristic to be adjusted. The automatic adjustment unit 60 can also adjust at least one operating parameter based on the function generated by the function generation unit 68. For example, a function can be used to calculate the value of the operating parameter if the calculated value of the beam characteristic meets the desired conditions. If the calculated value of the beam characteristic obtained from the calculation unit 64 does not meet the desired conditions, the automatic adjustment unit 60 adjusts the set value of the operating parameter based on the calculated value. When the adjustment of the operating parameter based on the calculated value is not successful, the automatic adjustment unit 60 can also adjust the operating parameter based on the measured value. When the reliability of the calculated value is low, the automatic adjustment unit 60 can also adjust the operating parameters based on the measured value. The reliability of the calculated value is determined, for example, by the cumulative amount of data used to generate the function or by the cumulative date and time, which will be described in detail later.

[0062] Figure 4 This is a flowchart illustrating an example of a method for adjusting beam characteristics. Figure 4 express Figure 3 The specific content of the process of adjusting a beam characteristic in each of steps S12 to S20 is as follows: If the specified condition is met ("Yes" in S30), the beam characteristic to be adjusted is calculated using a function (S32). If the specified condition is not met ("No" in S30), the beam characteristic to be adjusted is measured using a measuring device (S34). Here, the specified condition in S30 can include various conditions. The conditions that are met include the ability to calculate the beam characteristic to be adjusted, the ability to rely on the calculated value of the beam characteristic to be adjusted, and the number of adjustments based on the calculated value being less than a specified number. If the calculated or measured beam characteristic needs to be adjusted ("Yes" in S36), the action parameters are adjusted according to the calculated or measured value of the beam characteristic (S38), and the process returns to S30. In S36, if the beam characteristic adjustment is not required ("No" in S36), the process ends.

[0063] As Figure 4In one example of the process, when the specified conditions are met in S30, the operating parameters are adjusted based on the calculated values ​​of the beam characteristics, and the adjustment of the operating parameters is completed as long as the calculated values ​​of the beam characteristics meet the desired conditions. In this case, the measurement of the beam characteristics is omitted in the beam characteristic adjustment step, thus shortening the time spent on beam characteristic measurement. On the other hand, when the specified conditions are not met in S30, the operating parameters are adjusted based on the measured values ​​of the beam characteristics, and the adjustment of the operating parameters is completed as long as the measured values ​​of the beam characteristics meet the desired conditions. For example, by measuring the beam characteristics when the calculated values ​​of the beam characteristics cannot be relied upon or when the number of adjustments based on the calculated values ​​of the beam characteristics is repeated to a predetermined number, the operating parameters can be adjusted more reliably based on the measured values.

[0064] Next, the function used to calculate the beam characteristics will be explained. In this embodiment, at least one beam characteristic is calculated based on at least one specific action parameter (also called a specific parameter) included in a plurality of action parameters set in the beam generating device 90. If the specific parameter is set to p, the calculated beam characteristic is set to q, and the function is set to f, it can be expressed as q = f(p). The specific parameter p is an action parameter used to adjust the beam characteristic q. The specific parameter p is an action parameter that is highly correlated with the beam characteristic q, and by changing the setting value of the specific parameter p, a substantial change in the beam characteristic q can be made. This specific parameter p is determined for each type of beam characteristic q. The number of specific parameters p can be one for a beam characteristic q, or it can be multiple for a beam characteristic q.

[0065] Figure 5 A graph illustrating the relationship between a specific parameter p and the beam characteristics q. Figure 5 The multiple plots 70 shown in the diagram correspond to multiple datasets accumulated in the storage device 56. Each dataset includes set values ​​of multiple action parameters containing a specific parameter p and measured values ​​of multiple beam characteristics containing beam characteristics q. The function generation unit 68 determines a function (e.g., a straight line 80) representing the correlation between the specific parameter p and the beam characteristics q contained in each dataset. The straight line 80 is, for example, an approximate straight line of the multiple plots 70, which can be determined using the least squares method, etc. Figure 5 The example shows the case where the function f is represented by the straight line 80, but the function f is not limited to a straight line and can also be any nonlinear function.

[0066] Figure 6 A graph illustrating the relationship between a specific parameter p and the beam characteristics q. Figure 6 Used with Figure 5 The examples use the same dataset, but will Figure 5The multiple plots 70 shown are classified into multiple clusters, and a function (e.g., lines 81, 82, 83) is determined for each classified cluster. The first line 81 is, for example, an approximate line of the multiple first plots 71 contained in the first cluster. The second line 82 is an approximate line of the multiple second plots 72 contained in the second cluster. The third line 83 is an approximate line of the multiple third plots 73 contained in the third cluster. The classification unit 66 classifies the multiple datasets accumulated in the storage device 56 into multiple clusters. The function generation unit 68 generates a function (e.g., lines 81-83) representing the correlation between a specific parameter p and the beam characteristic q for each classified cluster. Figure 6 In the example, the accumulated datasets are clustered, and a function is generated for each cluster, thus... Figure 5 Compared to previous examples, this can improve the accuracy of beam characteristic q estimation.

[0067] Figure 7 This is a diagram illustrating classification methods for multiple datasets. Figure 7 In this study, based on the two components u and v contained in the dataset, multiple datasets are classified into five clusters: 91, 92, 93, 94, and 95. Cluster 1, 91, contains multiple plots 71 and... Figure 6 The multiple drawings 71 correspond to each other. The multiple drawings 72 contained in the second cluster 92 are... Figure 6 The multiple drawings 72 correspond to each other. The multiple drawings 73 contained in the third cluster 93 are... Figure 6 The multiple plots 73 correspond to each other. The components u and v used for clustering are, for example, equivalent to the principal components used in classifying multiple datasets accumulated in storage device 56 via Principal Component Analysis (PCA). The components u and v used for clustering can also be generated using dimensionality compression methods other than PCA. Components u and v are, for example, action parameters different from a specific parameter p. Components u and v can be a combination of action parameters different from a specific parameter p and beam characteristics different from beam characteristics q derived using the specific parameter p. Figure 7 In the example, clustering is performed based on two principal components, u and v, but the principal components used for clustering can also be three or more.

[0068] Figure 7The multiple clusters 91-95 shown represent multiple device states that the beam generating apparatus 90 can adopt. Here, "device state" can be interpreted, for example, as a state described by "hidden parameters" that differ from the operating parameters that can be explicitly set in the beam generating apparatus 90. For example, as the various devices constituting the beam generating apparatus 90 gradually deteriorate with use, the device state may change depending on the degree of deterioration. Furthermore, in cases such as switching the operation of the beam generating apparatus 90, the device state after the switch may sometimes change depending on the device state before the switch, or it may become a transitional device state until the device state after the switch stabilizes. Thus, when the device state differs, the set values ​​of the multiple operating parameters required to obtain the desired beam characteristics may differ depending on the device state. In other words, even if the set values ​​of the multiple operating parameters are set to be exactly the same, the generated ion beam may possess at least one different beam characteristic. Considering this difference in device state, by classifying the dataset including the set values ​​of the multiple operating parameters and the measured values ​​of the obtained beam characteristics, and generating functions for each classification, multiple functions corresponding to the differences in device state can be generated. As a result, the function can be distinguished according to the differences in device state, and the accuracy of beam characteristic calculation can be improved by using the appropriate function corresponding to the device state.

[0069] The classification unit 66 analyzes and classifies multiple datasets accumulated in the storage device 56 into multiple clusters. The classification unit 66 classifies the multiple datasets into multiple clusters based on the correlation between components u and v that differ from at least one specific parameter p. When the accumulated number of datasets is small, the classification unit 66 may not classify the multiple datasets into multiple clusters. When new datasets accumulate in the storage device 56, the classification unit 66 updates the classification of the multiple clusters using the multiple datasets that include the new datasets. If the accumulated number of datasets gradually increases with the use of the ion implantation device 100, the cluster classification continues to be updated; for example, the clusters are further subdivided and the number of clusters gradually increases. As the datasets gradually accumulate, the differences in device states can be classified more finely.

[0070] The function generation unit 68 generates a function for each cluster classified by the classification unit 66. When the accumulated amount of the dataset is small and it is impossible to classify multiple datasets into multiple clusters, the function generation unit 68 can also generate only one function based on multiple datasets. When new datasets accumulate in the storage device 56, the function generation unit 68 updates the function using the new datasets. When the classification of clusters based on the classification unit 66 is updated, the function generation unit 68 generates multiple functions corresponding to each of the updated multiple clusters. If the accumulated amount of the dataset gradually increases with the use of the ion implantation device 100, functions can be generated for each subdivided cluster, thus improving the estimation accuracy using the beam characteristics of the function. Furthermore, if the accumulated amount of the dataset gradually increases, the number of datasets used to generate a single function increases, thus improving the estimation accuracy using the beam characteristics of the function.

[0071] The function generation unit 68 can also determine the reliability of each generated function. The reliability of a function is determined based on the cumulative amount or cumulative dates and times of the dataset used for function generation. For example, the function generation unit 68 can make functions generated from large datasets more reliable than those generated from small datasets. For example, with... Figure 7 The functions corresponding to cluster 1 (91) or cluster 3 (93) are more reliable than the functions corresponding to cluster 4 (94) or cluster 5 (95). For example, the function generation unit 68 makes the functions generated based on new datasets of accumulated dates and times more reliable than those generated based on older datasets of accumulated dates and times. As the state of the beam generation device 90 gradually changes over time, the state corresponding to the older dataset is more likely to differ from the current state. Therefore, if beam characteristics are calculated using functions generated based on older datasets, the error compared to the beam characteristics in the current state increases, potentially leading to a decrease in the accuracy of beam characteristic calculations.

[0072] The function generation unit 68 can also classify multiple datasets differently based on the type of the calculated beam characteristics. The first function f1, used to calculate the first beam characteristic q1 (e.g., beam current) based on the first specific parameter p1 (e.g., the operating parameters of the ion source 10), is generated for each cluster classified according to operating parameters different from the first specific parameter p1. Similarly, the second function f2, used to calculate the second beam characteristic q2 (e.g., the centroid of the beam angle in the x-direction) based on the second specific parameter p2 (e.g., the operating parameters of the deflecting electromagnet 30), is generated for each cluster classified according to operating parameters different from the second specific parameter p2. As a result, the classification of multiple clusters corresponding to each of the multiple first functions f1 may differ from the classification of multiple clusters corresponding to each of the multiple second functions f2. Furthermore, when multiple clusters are classified according to operating parameters different from both the first specific parameter p1 and the second specific parameter p2, the classification of multiple clusters corresponding to each of the multiple first functions f1 can be generalized to the classification of multiple clusters corresponding to each of the multiple second functions f2.

[0073] The calculation unit 64 calculates beam characteristics using the function generated by the function generation unit 68. When the function generation unit 68 generates multiple functions corresponding to multiple clusters, the calculation unit 64 selects any one of the multiple functions and calculates the beam characteristics using the selected function. The calculation unit 64 determines which of the multiple clusters the current device state belongs to and calculates the beam characteristics using the function corresponding to the determined cluster. Specifically, it determines which of the multiple clusters the dataset representing the current device state belongs to and calculates the beam characteristics using the function corresponding to the determined cluster. The dataset used for cluster determination can be a complete dataset identical to the dataset accumulated in the storage device 56, or it can be an incomplete dataset lacking some measured values ​​of the beam characteristics. An incomplete dataset, for example, is... Figure 3 It is generated midway through the adjustment process.

[0074] Figure 8 This diagram illustrates an example of a method for calculating beam characteristics. Figure 8 This describes the process of determining a function corresponding to the current device state, using that function to calculate beam characteristics, and then changing the action parameters based on the calculated beam characteristics. Dataset D (First Dataset) A This represents the device state before the change of motion parameters during the adjustment process. Dataset D (1) A Including the setting value p of the first specific parameter 1A The setting value p of the second specific parameter 2A The measured value q of the first beam characteristics 1A The measured value q of the second beam characteristics 2A Dataset D (Part 1) A One example is in Figure 3The initial parameters set in S10 are, for example, action parameters that have been used in recent ion implantation processes.

[0075] The calculation unit 64 determines the first dataset D. A The cluster to which it belongs, and determine the first function f corresponding to the determined cluster. 1A and the second function f 2A (S40). The first function f 1A This is a function used to calculate the first beam characteristic q1 based on the first specific parameter p1. The second function f... 2A This is a function used to calculate the second beam characteristic q2 based on the second specific parameter p2. Based on the first dataset D... A The first function f is determined 1A and the second function f 2A This is a function that enables high-precision calculation of beam characteristics under the device state at the start of the adjustment process. It is assumed that the device state at the start of the adjustment process is the same as or very similar to the device state during the adjustment process. Therefore, based on the first dataset D... A The first function f is determined 1A and the second function f 2A It can be used as a function to calculate beam characteristics with high accuracy during the adjustment process.

[0076] The automatic adjustment unit 60 determines the changed setpoint p of the first specific parameter for the purpose of adjusting the first beam characteristic q1. 1B (S42). The calculation unit 64 calculates the first function f determined in S40. 1A Input the changed setting value p of the first specific parameter 1B The estimated value q of the modified first beam characteristics was calculated. 1B =f 1A (p 1B (S44). The calculation unit 64 can also calculate the second function f determined in S40. 2A Input the setting value p of the second specific parameter 2A The estimated value q of the second beam characteristic was calculated. 2B =f 2A (p 2A (S44). The second dataset D represents the device state during the adjustment of the first beam characteristic q1. B Including the changed setting value p of the first specific parameter. 1B and the calculated value q of the modified first beam characteristics. 1B The calculated value q of the first beam characteristic is obtained by calculating in S44. 1B The automatic adjustment unit 60 can omit the measurement of the first beam characteristics and instead perform the calculation based on the value q. 1BThe adjustment of the motion parameters. Furthermore, if the calculated value q of the first beam characteristic is obtained in S44... 1B If the desired conditions are met, the adjustment of the first beam characteristic q1 is completed, and the process can then transition to the adjustment of other beam characteristics.

[0077] exist Figure 8 In the example, with the aim of adjusting the first beam characteristic q1, the setting value of the first specific parameter is changed from p. 1B Change to p 1C The measured value q was obtained by measuring the characteristics q1 of the first beam. 1C (S46). Dataset D, Part 3 C Including the changed setting value p of the first specific parameter 1C and the measured value q of the characteristics of the first beam 1C Dataset D (3rd dataset) C This indicates the device state at the moment when the adjustment of the first beam characteristic q1 is completed during the adjustment process. The calculation unit 64 determines the third dataset D. C The cluster to which it belongs, and the second function f corresponding to the determined cluster. 2C (S48). Based on dataset D (S3) C The determined second function f 2C This is a function that enables high-precision calculation of the second beam characteristic q2 during the adjustment process, taking into account the device's state. The second function f, determined in S48, is... 2C It is possible that it is related to the second function f determined in S40. 2A The same, but sometimes different depending on the adjustment of the action parameters, it is similar to the second function f. 2A different.

[0078] The automatic adjustment unit 60 determines the modified setpoint p of the second specific parameter for the purpose of adjusting the second beam characteristic q2. 2D (S50). The calculation unit 64 calculates the second function f determined in S48. 2C Input the changed setting value p of the second specific parameter 2D The estimated value q of the modified second beam characteristics was calculated. 2D =f 2C (p 2D (S52). The calculated value q of the second beam characteristic is obtained by calculating in S52. 2D The automatic adjustment unit 60 can omit the measurement of the second beam characteristics and perform the adjustment based on the calculated value q. 2D The adjustment of the motion parameters. Furthermore, if the calculated value q of the third beam characteristic is calculated in S52... 2D If the desired conditions are met, the adjustment of the second beam characteristic q2 is completed, and the process can then transition to the adjustment of other beam characteristics.

[0079] exist Figure 8 The first function f determined in S40 1A With dataset D of the first dataset A The corresponding cluster. Dataset D, Part 1. A The dataset prior to the adjustment process includes the pre-change settings of multiple action parameters and the measured beam characteristics of the ion beam generated by the beam generating device 90 with the pre-change settings. Therefore, the first function f 1A The function corresponds to the cluster to which the following dataset belongs, the dataset including the pre-change settings of multiple action parameters, and the measured values ​​of the beam characteristics of the ion beam generated by the beam generating device 90 with the pre-change settings set. In S44, by adjusting the first function f... 1A Input the changed setting value p of the first specific parameter 1B The estimated value q of the first beam characteristic was calculated. 1B Therefore, calculations can be performed even without measuring the characteristics of the first beam at the start of the adjustment process.

[0080] Furthermore, the first dataset D A The measured value q includes the characteristics of the second beam generated by the beam generating device 90 with the settings set before the change. 2A Therefore, the first function f 1A A function corresponding to the cluster to which the following dataset belongs, the dataset including pre-change settings of multiple action parameters and measured values ​​q of a second beam characteristic that differs from the first beam characteristic of the ion beam generated by the beam generating device 90 with the pre-change settings. 2A In S44, by modifying the first function f... 1A Input the changed setting value p of the first specific parameter 1B The estimated value q of the first beam characteristic, which is different from that of the second beam, was calculated. 1B .

[0081] exist Figure 8 The second function f determined in S48 2C With dataset D (number 3) C Corresponding to the cluster they belong to. Dataset D (3rd dataset) C To adjust the dataset during the process, including the changed set values ​​of multiple action parameters, and the measured value q of the first beam characteristic which differs from the second beam characteristic of the ion beam generated by the beam generating device 90 with the changed set values. 1C Therefore, the second function f 2CA function corresponding to the cluster to which the following dataset belongs, the dataset including modified setpoints for multiple action parameters and measured values ​​q of a first beam characteristic that differs from the second beam characteristic of an ion beam generated by a beam generating device 90 with modified setpoints. 1C In S52, by modifying the second function f... 2C Input the changed setting value p of the second specific parameter 2D The estimated value q of the second beam characteristic, which is different from that of the first beam, is calculated. 2D Therefore, without measuring the characteristics of the second beam, which differ from those of the first beam, it is possible to utilize the second function f, which reflects the state during the adjustment process. 2C To make the calculation.

[0082] An example of the first beam characteristic measured during the adjustment process is the beam current. The beam current can be measured, for example, using the beam monitor 41 at the downstream end of the beamline, and the measurement time is very short. Therefore, the beam current can be adjusted based on the actual measured value, rather than being estimated by omitting the measurement. An example of the second beam characteristic estimated during the adjustment process is the beam angle, beam parallelism, or beam current density distribution. The beam angle, beam parallelism, and beam current density distribution, for example, need to be measured while moving the beam analyzer 42 in the x-direction, which increases the measurement time. Therefore, if repeated measurements are taken for adjustment, the time required to complete the adjustment increases significantly. Therefore, it is highly advantageous to estimate the beam characteristics for the beam angle, beam parallelism, or beam current density distribution instead of actually measuring them, thus omitting the measurement.

[0083] According to this embodiment, by estimating beam characteristics during the adjustment of operating parameters, the measurement of beam characteristics is omitted, thereby shortening the time spent on beam characteristic measurement and accelerating the adjustment of operating parameters. Furthermore, according to this embodiment, the correlation between the beam characteristics to be adjusted and specific parameters is determined by a function, thus allowing the function to derive modified setpoints for specific parameters used to obtain the desired beam characteristics. Therefore, compared to adjusting parameters through trial and error via repeated measurements and adjustments, the adjustment of operating parameters can be accelerated. Moreover, by measuring beam characteristics after adjustment based on estimated values, the beam characteristics of the ion beam used for ion implantation can be definitively confirmed, and the number of beam characteristic measurements in the overall adjustment process is reduced, thus shortening the adjustment time. Therefore, beam characteristics can be adjusted with high precision while improving the productivity of the ion implantation apparatus.

[0084] The present invention has been described above with reference to the various embodiments described above, but the present invention is not limited to the embodiments described above. Appropriate combinations or substitutions of the structures of the embodiments are also included in the present invention. Furthermore, based on the knowledge of those skilled in the art, it is possible to appropriately change the combination or processing order of the embodiments, or to make various design modifications or other variations to the embodiments, and such modified embodiments are also included within the scope of the present invention. In each embodiment, a semiconductor wafer has been described as an example, but it is applicable to any working element (e.g., a wafer or substrate), and is not limited to semiconductor wafers. Other specific examples of working elements include substrates for flat panel displays (e.g., glass substrates).

Claims

1. An ion implantation device, characterized in that, have: A beam generating device that generates an ion beam that irradiates the workpiece; A control device that sets multiple action parameters for controlling the operation of the beam generating device; A measuring device for measuring at least one beam characteristic of the ion beam; The storage device accumulates a dataset that establishes a corresponding association between the set of set values ​​of the plurality of action parameters and the measured values ​​of at least one beam characteristic of the ion beam; and An analysis device generates a function based on multiple datasets accumulated in the storage device for estimating at least one beam characteristic based on a set value of at least one specific parameter included in the multiple action parameters; When the setting value of at least one specific parameter included in the plurality of action parameters is changed, the control device inputs the changed setting value of the at least one specific parameter to the function to calculate the estimated value of the at least one beam characteristic. When the estimated value meets the specified conditions, the control device omits the measurement of the at least one beam characteristic based on the measuring device.

2. The ion implantation apparatus according to claim 1, characterized in that, The control device adjusts at least one specific parameter included in the plurality of action parameters based on the calculated value.

3. The ion implantation apparatus according to claim 1 or 2, characterized in that, When the calculated value does not meet the specified conditions, the control device causes the measuring device to measure the at least one beam characteristic.

4. The ion implantation apparatus according to claim 3, characterized in that, The control device adjusts at least one specific parameter included in the plurality of action parameters based on the measured value of the at least one beam characteristic and the function.

5. The ion implantation apparatus according to claim 1, characterized in that, When new datasets accumulate in the storage device, the analysis device uses the new datasets to update the function.

6. The ion implantation apparatus according to claim 1, characterized in that, The analysis device classifies multiple datasets accumulated in the storage device into multiple clusters and generates multiple functions corresponding to each of the multiple clusters. The control device uses any one of the plurality of functions to calculate the estimated value.

7. An ion implantation device, characterized in that, have: A beam generating device that generates an ion beam that irradiates the workpiece; A control device that sets multiple action parameters for controlling the operation of the beam generating device; A measuring device for measuring at least one beam characteristic of the ion beam; The storage device accumulates a dataset that establishes a corresponding association between the set of set values ​​of the plurality of action parameters and the measured values ​​of at least one beam characteristic of the ion beam; and The analysis device generates a function, based on multiple datasets accumulated in the storage device, for estimating at least one beam characteristic based on a set value of at least one specific parameter included in the multiple action parameters. When the setting value of at least one specific parameter included in the plurality of action parameters is changed, the control device inputs the changed setting value of the at least one specific parameter to the function to calculate the estimated value of the at least one beam characteristic. The analysis device classifies multiple datasets accumulated in the storage device into multiple clusters and generates multiple functions corresponding to each of the multiple clusters. The control device uses any one of the plurality of functions to calculate the estimated value, determines which of the plurality of action parameters, including the modified set value of at least one specific parameter, is classified into which of the plurality of clusters, and uses the function corresponding to the determined cluster to calculate the estimated value.

8. An ion implantation device, characterized in that, have: A beam generating device that generates an ion beam that irradiates the workpiece; A control device that sets multiple action parameters for controlling the operation of the beam generating device; A measuring device for measuring at least one beam characteristic of the ion beam; The storage device accumulates a dataset that establishes a corresponding association between the set of set values ​​of the plurality of action parameters and the measured values ​​of at least one beam characteristic of the ion beam; and The analysis device generates a function, based on multiple datasets accumulated in the storage device, for estimating at least one beam characteristic based on a set value of at least one specific parameter included in the multiple action parameters. When the setting value of at least one specific parameter included in the plurality of action parameters is changed, the control device inputs the changed setting value of the at least one specific parameter to the function to calculate the estimated value of the at least one beam characteristic. The analysis device classifies multiple datasets accumulated in the storage device into multiple clusters and generates multiple functions corresponding to each of the multiple clusters. The control device calculates the estimated value using any one of the plurality of functions. The measuring device measures the characteristics of a first beam of the ion beam generated by the beam generating device, which is configured with multiple action parameters having modified set values ​​including at least one specific parameter. The control device determines which of the plurality of clusters the dataset, which includes a modified set value containing at least one specific parameter and the measured value of the first beam characteristic, is classified into, and uses a function corresponding to the determined cluster to calculate a calculated value of a second beam characteristic that is different from the first beam characteristic.

9. An ion implantation device, characterized in that, have: A beam generating device that generates an ion beam that irradiates the workpiece; A control device that sets multiple action parameters for controlling the operation of the beam generating device; A measuring device for measuring at least one beam characteristic of the ion beam; The storage device accumulates a dataset that establishes a corresponding association between the set of set values ​​of the plurality of action parameters and the measured values ​​of at least one beam characteristic of the ion beam; and The analysis device generates a function, based on multiple datasets accumulated in the storage device, for estimating at least one beam characteristic based on a set value of at least one specific parameter included in the multiple action parameters. When the setting value of at least one specific parameter included in the plurality of action parameters is changed, the control device inputs the changed setting value of the at least one specific parameter to the function to calculate the estimated value of the at least one beam characteristic. The analysis device classifies multiple datasets accumulated in the storage device into multiple clusters and generates multiple functions corresponding to each of the multiple clusters. The control device uses any one of the plurality of functions to calculate the estimated value, determines which of the plurality of action parameters, including the previous set value of at least one specific parameter, is classified into which of the plurality of clusters, and uses the function corresponding to the determined cluster to calculate the estimated value.

10. An ion implantation device, characterized in that, have: A beam generating device that generates an ion beam that irradiates the workpiece; A control device that sets multiple action parameters for controlling the operation of the beam generating device; A measuring device for measuring at least one beam characteristic of the ion beam; The storage device accumulates a dataset that establishes a corresponding association between the set of set values ​​of the plurality of action parameters and the measured values ​​of at least one beam characteristic of the ion beam; and The analysis device generates a function, based on multiple datasets accumulated in the storage device, for estimating at least one beam characteristic based on a set value of at least one specific parameter included in the multiple action parameters. When the setting value of at least one specific parameter included in the plurality of action parameters is changed, the control device inputs the changed setting value of the at least one specific parameter to the function to calculate the estimated value of the at least one beam characteristic. The analysis device classifies multiple datasets accumulated in the storage device into multiple clusters and generates multiple functions corresponding to each of the multiple clusters. The control device calculates the estimated value using any one of the plurality of functions. The measuring device measures the characteristics of a first beam of the ion beam generated by the beam generating device, which has multiple operating parameters set with pre-change values ​​including at least one specific parameter. The control device determines which of the plurality of clusters a dataset including multiple action parameters containing at least one specific parameter and the measured values ​​of the first beam characteristic is classified into, and uses a function corresponding to the determined cluster to calculate a calculated value of a second beam characteristic that is different from the first beam characteristic.

11. The ion implantation apparatus according to any one of claims 7 to 10, characterized in that, The analysis device classifies the multiple datasets into multiple clusters based on the correlation between the set values ​​of two or more of the multiple action parameters that are different from the at least one specific parameter.

12. The ion implantation apparatus according to any one of claims 7 to 10, characterized in that, When at least one of the number of datasets contained in the determined cluster and the cumulative date and time meets the specified conditions, the control device omits the measurement of at least one beam characteristic based on the measuring device.

13. The ion implantation apparatus according to any one of claims 6 to 10, characterized in that, When a new dataset accumulates in the storage device, the analysis device uses the new dataset to update the classification of the dataset in multiple clusters and generates multiple functions corresponding to each of the multiple clusters for updating the classification.

14. An ion implantation device, characterized in that, have: A beam generating device that generates an ion beam that irradiates the workpiece; A control device that sets multiple action parameters for controlling the operation of the beam generating device; A measuring device for measuring at least one beam characteristic of the ion beam; The storage device accumulates a dataset that establishes a corresponding association between the set of set values ​​of the plurality of action parameters and the measured values ​​of at least one beam characteristic of the ion beam; and The analysis device generates a function, based on multiple datasets accumulated in the storage device, for estimating at least one beam characteristic based on a set value of at least one specific parameter included in the multiple action parameters. When the setting value of at least one specific parameter included in the plurality of action parameters is changed, the control device inputs the changed setting value of the at least one specific parameter to the function to calculate the estimated value of the at least one beam characteristic. The beam generating apparatus includes an ion generating device and a beamline device for conveying the ion beam drawn from the ion generating device. The at least one beam characteristic is the beam current of the ion beam delivered through the beamline device. The at least one specific parameter is an action parameter used to control the operation of the ion generating device.

15. An ion implantation device, characterized in that, have: A beam generating device that generates an ion beam that irradiates the workpiece; A control device that sets multiple action parameters for controlling the operation of the beam generating device; A measuring device for measuring at least one beam characteristic of the ion beam; The storage device accumulates a dataset that establishes a corresponding association between the set of set values ​​of the plurality of action parameters and the measured values ​​of at least one beam characteristic of the ion beam; and The analysis device generates a function, based on multiple datasets accumulated in the storage device, for estimating at least one beam characteristic based on a set value of at least one specific parameter included in the multiple action parameters. When the setting value of at least one specific parameter included in the plurality of action parameters is changed, the control device inputs the changed setting value of the at least one specific parameter to the function to calculate the estimated value of the at least one beam characteristic. The beam generating apparatus includes a deflection device that applies at least one of an electric field and a magnetic field to the ion beam to deflect the ion beam. The at least one beam characteristic is the angle of the ion beam in the deflection direction by which the ion beam is deflected by the deflection device. The at least one specific parameter is an action parameter used to control the operation of the deflection device.

16. The ion implantation apparatus according to any one of claims 1, 7, 8, 9, 10, 14, and 15, characterized in that, The beam generating device includes a lens device that applies at least one of an electric field and a magnetic field to the ion beam to converge or diverge the ion beam. The at least one beam characteristic is the beam size or convergence / divergence angle of the ion beam. The at least one specific parameter is an action parameter used to control the operation of the lens device.

17. An ion implantation device, characterized in that, have: A beam generating device that generates an ion beam that irradiates the workpiece; A control device that sets multiple action parameters for controlling the operation of the beam generating device; A measuring device for measuring at least one beam characteristic of the ion beam; The storage device accumulates a dataset that establishes a corresponding association between the set of set values ​​of the plurality of action parameters and the measured values ​​of at least one beam characteristic of the ion beam; and The analysis device generates a function, based on multiple datasets accumulated in the storage device, for estimating at least one beam characteristic based on a set value of at least one specific parameter included in the multiple action parameters. When the setting value of at least one specific parameter included in the plurality of action parameters is changed, the control device inputs the changed setting value of the at least one specific parameter to the function to calculate the estimated value of the at least one beam characteristic. The beam generating device includes: a scanner that applies at least one of an electric field and a magnetic field to the ion beam to perform reciprocating scanning; The lens device applies at least one of an electric field and a magnetic field to the ion beam that is reciprocating through the scanner to parallelize it. The at least one beam characteristic is the parallelism of the ion beam. The at least one specific parameter is an action parameter used to control the operation of the lens device.

18. An ion implantation method, characterized in that, It has the following processes: The cumulative dataset is formed by establishing a corresponding association between a set of set values ​​of multiple operating parameters used to control the operation of the beam generating device for generating ion beams and measured values ​​of at least one beam characteristic of the ion beam. The accumulated datasets are classified into multiple clusters; Multiple functions corresponding to each of the plurality of clusters are generated. These functions are used to calculate at least one beam characteristic based on a set value of at least one specific parameter included in the plurality of action parameters. When changing the setting value of at least one specific parameter included in the plurality of operating parameters of the beam generating device, it is determined which of the plurality of operating parameters, including the setting value before or after the change of the at least one specific parameter, is classified into which of the plurality of clusters; and The estimated value of the at least one beam characteristic is calculated by inputting the modified set value of the at least one specific parameter to the function corresponding to the determined cluster.

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