Information processing method, information processing device, and program

Abstract

An information processing method for optimizing a control parameter in a device that executes an operation on the basis of a plurality of control parameters, the information processing unit causing the device to execute a plurality of operations included in all operations that the device can execute, a plurality of time-series measurement data relating to a prescribed evaluation index measured during execution of each of the plurality of actions are acquired, a waveform is created on the basis of the plurality of measurement data relating to each of the actions, and a plurality of waveform information relating to the plurality of actions are superimposed to create a superimposed image. An operation screen including the superimposed image is created, and data of the operation screen is input to a display unit to cause the display unit to display the operation screen.

Description

Technical Field

[0001] This disclosure relates to information processing methods, information processing devices, and programs. Background Technology

[0002] The method for generating control parameters involved in the background art has been disclosed, for example, in Patent Document 1.

[0003] In the past, the goal was to provide users with easily understandable and useful information during the optimization of control parameters.

[0004] Existing technical documents

[0005] Patent documents

[0006] Patent Document 1: International Patent Publication No. 2018 / 151215 Summary of the Invention

[0007] The purpose of this disclosure is to provide information processing methods, devices, and programs that can easily provide useful information to users in a way that is easy to understand.

[0008] One aspect of this disclosure relates to an information processing method for optimizing the control parameters in a device that performs actions based on multiple control parameters. An information processing unit instructs the device to perform multiple actions included in all actions the device can perform, acquires multiple time-series measurement data related to a predetermined evaluation index measured during the execution of each of the multiple actions, generates waveforms based on the multiple measurement data related to each action, generates an overlapping image by overlaying the multiple waveform information related to the multiple actions, generates an operation screen containing the overlapping image, and inputs data from the operation screen to a display unit, causing the display unit to display the operation screen. Attached Figure Description

[0009] Figure 1 This is a diagram that concisely illustrates the structure of the control parameter generation apparatus according to the embodiments of this disclosure.

[0010] Figure 2 This is a diagram that briefly represents an example of control parameters.

[0011] Figure 3 This is a diagram that briefly represents an example of a selection rule.

[0012] Figure 4 This is a schematic diagram illustrating an example of the change in the positional deviation of a driven object relative to a target position.

[0013] Figure 5 This is a simplified diagram illustrating an example of the measurement data output by the sensor.

[0014] Figure 6 This is a flowchart representing the processes performed by the information processing department.

[0015] Figure 7 It is a flowchart showing the details of the control parameter optimization process.

[0016] Figure 8 This is a flowchart showing the details of the evaluation result output processing.

[0017] Figure 9 This is a simplified representation of an example of a user interface created based on representative actions.

[0018] Figure 10 This is a simplified illustration of an example of an operation screen created based on an evaluation action.

[0019] Figure 11 This is a simplified representation of the overlapping images involved in the first variation.

[0020] Figure 12 This is a simplified representation of the overlapping images involved in the second variation.

[0021] Figure 13 This is a simplified representation of the overlapping images involved in the second variation.

[0022] Figure 14 This is a simplified representation of the overlapping images involved in the third variation.

[0023] Figure 15 This is a simplified representation of the overlapping images involved in the fourth variation.

[0024] Figure 16 It is a simplified representation of overlapping images.

[0025] Figure 17 This is a simplified representation of the first example of the overlapping images involved in the fifth variation.

[0026] Figure 18 This is a simplified representation of the second example of the overlapping images involved in the fifth variation. Detailed Implementation

[0027] (The insights that form the basis of this disclosure)

[0028] In recent years, a method has been proposed for generating appropriate control parameters related to the drive unit in a production apparatus. This method involves using a machine learning model or similar tool to search for appropriate control parameters, thereby generating appropriate control parameters. The production apparatus includes a drive unit such as a servo motor that drives an object (see, for example, Patent Document 1).

[0029] Generally speaking, the number of control parameters used in the drive unit of a production device can sometimes reach more than 50. In addition, the adjustment levels of these control parameters can sometimes reach more than 100 levels.

[0030] For example, if a production unit performs 80 actions, the number of control parameters for the drive source is 50, and the adjustment level of the control parameters is 100, the number of combinations of these parameters reaches 100. 50 ×80.

[0031] The inventors discovered the following problem: when generating control parameters for such a large number of combinations, when using methods such as machine learning models to search for appropriate control parameters, due to the excessively large search range, sometimes it takes a lot of time to find appropriate control parameters, or no appropriate control parameters can be found no matter how much time is spent.

[0032] Therefore, in order to realize the following parameter generation method, the inventors have conducted repeated experiments and research. This parameter generation method can efficiently generate appropriate control parameters even when dealing with a large number of combinations of control parameters.

[0033] Through the above experiments and research, the inventors have gained the following insights: Instead of searching for appropriate control parameters from the outset using a vast array of combinations, in the case of 80 actions performed by the production device, as an initial step, appropriate control parameters are searched only for a subset of these 80 actions, such as a single action. In the next step, the number of actions performed by the production device is increased, for example, to combinations related to two actions, and appropriate control parameters are searched using the results from the initial step as a guide. In the next step, the number of actions performed by the production device is further increased, for example, to combinations related to four actions, and appropriate control parameters are searched using the results from the previous step as a guide. These steps are repeated until finally, appropriate control parameters are searched using combinations related to all 80 actions. Thus, by focusing on combinations related to all 80 actions, appropriate control parameters can be generated more efficiently and reliably.

[0034] Furthermore, the inventors discovered the following problem: In the optimization processing of control parameters, if waveforms of measurement data related to each action of multiple actions are generated and multiple waveforms are displayed side by side, the display size of each waveform will become too small due to the limitation of the screen size of the display unit, making it impossible to provide useful information to the user in an easy-to-understand manner.

[0035] Regarding this issue, the inventors have gained the following insight: by displaying multiple waveforms in an overlapping manner, useful information can be provided to the user in an easy-to-understand way.

[0036] Subsequently, based on this insight, the inventors conducted further experiments and research, and came up with the following method for generating control parameters as disclosed herein.

[0037] Next, the various methods of this disclosure will be described.

[0038] The information processing method disclosed in the first aspect is used to optimize the control parameters in a device that performs actions based on multiple control parameters. The information processing unit instructs the device to perform multiple actions included in all actions that the device can perform, acquires multiple measurement data of time series related to a specified evaluation index measured during the execution of each of the multiple actions, generates waveforms based on the multiple measurement data related to each action, generates an overlapping image by overlapping multiple waveform information related to the multiple actions, generates an operation screen including the overlapping image, and instructs the display unit to display the operation screen by inputting the data of the operation screen to the display unit.

[0039] According to the first method, the information processing unit creates an overlay image by overlaying multiple waveform information related to multiple actions, and then creates an operation screen containing the overlay image. In this way, multiple waveform information are displayed overlay on the display unit, thereby providing useful information to the user in a clear and understandable manner.

[0040] The information processing method involved in the second aspect of this disclosure may be: in the first aspect, the plurality of actions are all the actions, or a plurality of representative actions selected from all the actions.

[0041] According to the second method, by displaying multiple waveforms related to all or multiple representative actions in an overlapping manner, useful information can be easily provided to the user.

[0042] The information processing method involved in the third aspect of this disclosure may be: in the second aspect, accepting operation input of selection information, wherein the selection information is used to select one waveform information from the plurality of waveform information contained in the operation screen displayed by the display unit, and changing the representative action based on the selection information.

[0043] According to the third method, users can change the representative action using the operation screen displayed on the display unit, thus improving user convenience.

[0044] The information processing method involved in the fourth aspect of this disclosure may be: in any one of the first to third aspects, the plurality of waveform information is a plurality of waveforms related to the plurality of actions, or a plurality of evaluation values ​​calculated based on the plurality of waveforms.

[0045] According to method 4, by displaying multiple waveforms or multiple evaluation values ​​in an overlapping manner, useful information can be easily provided to the user.

[0046] The information processing method involved in the fifth aspect of this disclosure may be: in any one of the first to fourth aspects, in the production of the overlapping image, the display form of the waveform information that has achieved the target value of the evaluation index is different from the display form of the waveform information that has not achieved the target value.

[0047] According to the fifth method, by making the display form of waveform information that has achieved the target value different from the display form of waveform information that has not achieved the target value, useful information can be provided to the user in an easy-to-understand way.

[0048] The information processing method involved in the sixth aspect of this disclosure may be as follows: In any one of the first to fifth aspects, the operation screen further includes: a first input field for selecting and displaying waveform information that has achieved the target value of the evaluation index from among the plurality of waveform information; and a second input field for selecting and displaying waveform information that has not achieved the target value. In the creation of the overlapping image, when selection information is entered in the first input field, the waveform information that has achieved the target value from among the plurality of waveform information is included in the overlapping image. When selection information is entered in the second input field, the waveform information that has not achieved the target value from among the plurality of waveform information is included in the overlapping image.

[0049] According to method 6, users can select the waveform displayed on the operation screen by entering selection information into the first and second input fields, thus improving user convenience.

[0050] The information processing method involved in the seventh aspect of this disclosure may be as follows: In any of the first to sixth aspects, the operation screen further includes a first input field for selecting a first evaluation indicator as the evaluation indicator and a second input field for selecting a second evaluation indicator as the evaluation indicator. In the waveform production, when selection information is input into the first input field, the waveform is produced based on the multiple measurement data of the time series related to the first evaluation indicator measured during the execution of each action. When selection information is input into the second input field, the waveform is produced based on the multiple measurement data of the time series related to the second evaluation indicator measured during the execution of each action.

[0051] According to method 7, users can select evaluation indicators by entering selection information into the first and second input fields, thus improving user convenience.

[0052] The information processing method involved in the eighth aspect of this disclosure may be: in any one of the first to seventh aspects, in the creation of the waveform, by having the device perform each action multiple times, multiple waveforms are created for each action; in the creation of the overlapping image, the waveform information with the best evaluation value for the evaluation index among the multiple waveform information related to each action is selected, and the overlapping image is created by overlapping the multiple best waveform information related to the multiple actions.

[0053] According to method 8, an overlay image is created by overlapping the waveform information with the best evaluation value among multiple waveform information related to each action. Therefore, the user can easily determine the actions that need further adjustment by referring to the overlay image.

[0054] The information processing method involved in the ninth aspect of this disclosure may be: in any one of the first to eighth aspects, during the creation of the overlapping image, the waveform information related to each action is shifted or scaled in the time axis direction according to the target value of each action with respect to the evaluation index.

[0055] According to the ninth method, waveform information with respect to the target value offset or scaling of the evaluation index based on each action can be displayed. Therefore, the waveform information with the worst evaluation value can be appropriately determined, and the convenience for users can be improved.

[0056] The information processing method disclosed in the tenth aspect is used to optimize the control parameters in a device that performs actions based on multiple control parameters. The information processing unit instructs the device to perform multiple actions, acquires multiple measurement data of time series related to a predetermined evaluation index measured during the execution of each of the multiple actions, generates waveforms based on the multiple measurement data related to each action, generates an overlapping image by overlaying multiple waveform information related to the multiple actions, generates a screen containing the overlapping image, and displays the screen by inputting the data of the screen to a display unit. The overlapping image contains a graphic, which represents the evaluation value corresponding to the waveform information with the worst evaluation value for the evaluation index among the multiple waveform information.

[0057] According to the 10th method, the overlapping image includes a graph that represents the evaluation value corresponding to the waveform information with the worst evaluation value for the evaluation index among multiple waveform information, thus improving user convenience.

[0058] The information processing apparatus according to the 11th aspect of this disclosure is used to optimize the control parameters in an apparatus that performs actions based on multiple control parameters. It includes: a control unit that causes the apparatus to perform multiple actions included in all actions that the apparatus can perform; an acquisition unit that acquires multiple measurement data of time series related to a predetermined evaluation index measured during the execution of each of the multiple actions; a production unit that produces waveforms based on the multiple measurement data related to each action, produces an overlapping image by overlapping multiple waveform information related to the multiple actions, and produces an operation screen including the overlapping image; and an output unit that inputs data from the operation screen to a display unit, causing the display unit to display the operation screen.

[0059] According to the eleventh method, the information processing device creates an overlay image by overlaying multiple waveform information related to multiple actions, and creates an operation screen containing the overlay image. In this way, multiple waveform information are displayed overlappingly on the display unit, thereby providing useful information to the user in a clear and understandable manner.

[0060] The 12th aspect of this disclosure involves a program that causes an information processing device to perform processing, the information processing device being used to optimize the control parameters in a device that performs actions based on multiple control parameters, the processing causing the device to perform multiple actions included in all actions that the device can perform, acquiring multiple measurement data of time series related to a predetermined evaluation index measured during the execution of each of the multiple actions, generating waveforms based on the multiple measurement data related to each action, generating an overlapping image by overlapping multiple waveform information related to the multiple actions, generating an operation screen including the overlapping image, and causing the display unit to display the operation screen by inputting data of the operation screen to a display unit.

[0061] According to the 12th method, the information processing device creates an overlay image by superimposing multiple waveform information related to multiple actions, and creates an operation screen containing the overlay image. In this way, multiple waveform information are displayed overlappingly on the display unit, thereby providing useful information to the user in a clear and understandable manner.

[0062] This disclosure also enables the implementation of programs that cause a computer to execute the characteristic structures contained in the above-described methods or apparatus, or systems that utilize such programs to perform actions. Furthermore, such computer programs can of course be distributed via computer-readable non-transitory storage media such as CD-ROMs (Compact Disc Read-Only Memory) or communication networks such as the Internet.

[0063] (Implementation of this disclosure)

[0064] Hereinafter, embodiments of the present disclosure will be described in detail using the accompanying drawings. It is assumed that elements with the same symbol in different drawings represent the same or corresponding elements. Furthermore, the constituent elements, their arrangement, connection methods, and order of operation shown in the following embodiments are examples and are not intended to limit the present disclosure. The present disclosure is limited only by the claims. Therefore, while it may not be necessary to achieve the objectives of this disclosure through the constituent elements of the following embodiments that are not described in the independent claims representing the highest-level concept of the present disclosure, such constituent elements will be described as constituent elements constituting a more preferred embodiment.

[0065] Figure 1 This is a simplified diagram illustrating the structure of the control parameter generation system according to an embodiment of the present disclosure. The control parameter generation system optimizes control parameters 31 by generating and updating them for the production apparatus 2. The control parameter generation system includes a control parameter generation device 1 and a sensor 3.

[0066] Production device 2 is a device used for production equipment, such as an installation device, processing device, manufacturing device, or handling device for installing, processing, manufacturing, or transporting equipment. Production device 2 is, for example, a production line set up in a factory.

[0067] Production apparatus 2 is capable of performing N actions (N is an integer greater than or equal to 3). N is, for example, 80. Furthermore, this disclosure is not limited to production apparatus 2, but can be applied to any apparatus capable of performing N actions.

[0068] The production apparatus 2 includes a storage unit 41, a control unit 42, a drive unit 43, and a drive object 44.

[0069] The storage unit 41 is composed of HDD, SSD or semiconductor memory, etc.

[0070] The control unit 42 is composed of processors such as CPU (Central Processing Unit).

[0071] The operation of the drive unit 43 is controlled by the control unit 42, which drives the object 44.

[0072] The drive unit 43 is, for example, a servo motor, a directional flow control valve for controlling the fluid in a pneumatic artificial muscle arm, or a directional flow control valve for controlling the fluid in a hydraulic arm. The servo motor can be, for example, a rotary motor or a linear motor.

[0073] The driven object 44 is an object driven by the drive unit 43. When the drive unit 43 is a servo motor, the driven object 44 is a head that transports the workpiece, or a nozzle mounted on the head for adsorbing the workpiece. Alternatively, when the drive unit 43 is a directional flow control valve, the driven object 44 is a pneumatic or hydraulic artificial muscle arm.

[0074] The control unit 42 controls the drive unit 43 by outputting a command to the drive unit 43 to move the driven object 44 to a predetermined target position. The command output from the control unit 42 to the drive unit 43 may be a position command indicating the position of the drive unit 43 or the driven object 44, or a torque command indicating the torque of the drive unit 43.

[0075] The storage unit 41 stores the control parameters 31 generated and updated by the control parameter generation device 1. The control unit 42 controls the drive unit 43 based on the control parameters 31 read from the storage unit 41. In other words, the control unit 42 uses the control parameters 31 when controlling the drive unit 43. The number of control parameters 31 is, for example, 50.

[0076] The control parameter generation device 1 includes an information processing unit 11, a storage unit 12, an input unit 13, a display unit 14, and a communication unit 15.

[0077] The information processing unit 11 is constructed using a processor such as a CPU. As a function implemented by the processor executing a program read from a non-volatile storage medium such as a computer-readable ROM, the information processing unit 11 includes a selection unit 21, a control unit 22, an acquisition unit 23, an update unit 24, an output unit 25, a production unit 26, and a receiving unit 27. In other words, the aforementioned program is used to enable the information processing unit 11, which is mounted on the control parameter generation device 1, to function as the selection unit 21 (selection unit), control unit 22 (control unit), acquisition unit 23 (acquisition unit), update unit 24 (update unit), output unit 25 (output unit), production unit 26 (production unit), and receiving unit 27 (receiving unit). Details of the processing performed by each processing unit will be described below.

[0078] The storage unit 12 is constructed using HDDs, SSDs, or semiconductor memory. The storage unit 12 stores control parameters 31, selection rules 32, measurement data 33, and inference models 34.

[0079] Figure 2 This is a simplified diagram illustrating an example of control parameter 31. Control parameter 31 includes parameters a1 and a2 that adjust the vibration frequency of the driven object 44, parameters b1 and b2 that adjust the speed of the driven object 44, parameters c1 and c2 that adjust the depth of singularities in the vibration characteristics of the driven object 44, and parameters d1 and d2 that adjust the vibration amplitude of the driven object 44. Control parameter 31 may also include, for example, parameters b1, b2, c1, c2, and d1, d2 that have trade-off relationships with each other.

[0080] Figure 3 This diagram is a simplified representation of an example of selection rule 32. Selection rule 32 illustrates the rule by which the selection unit 21 selects at least one representative action from all N actions that the production unit 2 can perform. The representative action is the action that the production unit 2 is instructed to perform during control parameter optimization processing by the control parameter generation device 1. Figure 3In the example shown, the representative action is executed in eight stages, from stage 1 to stage 8. The number of actions X contained in the representative action increases as the stage progresses. For example, stage 1 has 1 action X, representing action 2. Stage 2 has 2 action X, representing actions 3 and 6. Stage 3 has 4 action X, representing actions 2, 7, 9, and so on. Stage 4 has 8 action X, representing actions 1, 3, 7, 9, and so on. Stage 5 has 16 action X, representing actions 2, 4, 6, 8, 10, and so on. Stage 6 has 32 action X, representing actions 1, 3, 5, 7, 9, 10, and so on. Stage 7 has 64 action X, representing actions 1, 2, 3, 5, 6, 7, 9, 10, and so on. Stage 8 represents all actions from 1 to 50. In addition, the representative actions in each stage can be all actions. Furthermore, the number of representative actions in each stage can be set to a fixed value and the representative actions can be replaced.

[0081] Selection rule 32 is specified in advance by the user through operation input of input unit 13. In addition, it is not limited to user specification. In selection rule 32, the number and actions of representative actions of each stage can be preset according to the prescribed rules, or the number and actions of representative actions of each stage can be dynamically changed according to a specific method specified by the user.

[0082] Additionally, selection rule 32 may also include setting information for the actions executed in the evaluation actions among all N actions that production device 2 can perform. Evaluation actions are actions that control parameter generation device 1 instructs production device 2 to perform in the evaluation result output processing in order to comprehensively evaluate the actions of production device 2. In this embodiment, the evaluation actions include all actions. Evaluation actions are executed during at least one period, including the period during which representative actions of each stage are executed and the period during which transitions from one stage to the next. Furthermore, in Figure 3 In the example shown, the representative action of stage 8, which includes all actions, can also be performed as the evaluation action, which includes all actions.

[0083] The evaluation action is not limited to all actions; it can also be the difference between all actions and the nearest representative action. For example, regarding the period during which the representative actions of stage 4 are executed, the representative actions include actions 1, 3, 7, 9, ... Therefore, the evaluation actions executed during this period include the differences between all actions and the representative actions, namely actions 2, 4, 5, 6, 8, 10, ... Similarly, regarding the period during which the representative actions of stage 5 are executed, the representative actions include actions 2, 4, 6, 8, 10, ... Therefore, the evaluation actions executed during the transition from stage 5 to stage 6 include the differences between all actions and the representative actions, namely actions 1, 3, 5, 7, 9, ...

[0084] Furthermore, the evaluation action is not limited to all actions, but can also be predetermined actions from all actions. For example, multiple actions from all actions, ordered from largest to smallest impact on the performance of production unit 2, are defined as predetermined actions. In the evaluation action, the control parameter generation device 1 instructs production unit 2 to perform only the predetermined actions.

[0085] Reference Figure 1 Measurement data 33 refers to the measured values ​​representing predetermined evaluation indicators obtained by sensor 3 during the execution of representative and evaluation actions. Multiple measurement data 33 are stored in storage unit 12, thereby forming a database. The evaluation indicator can be any indicator capable of quantifying the operation of production device 2; in this embodiment, a setpoint time is used.

[0086] Sensor 3 is, for example, a position sensor, which measures the position of the driven object 44 in the representative action and the evaluation action in a time sequence. Then, measurement data 33, representing the measured position corresponding to each action included in the representative action and the evaluation action, is sent to the control parameter generation device 1. Alternatively, sensor 3 may be a torque sensor or the like, instead of a position sensor.

[0087] Figure 4 This is a schematic diagram illustrating an example of the change in the positional deviation of the driven object 44 relative to the target position during the action of the production device 2 moving the driven object 44 to the target position.

[0088] exist Figure 4 In the diagram, the horizontal axis represents time, and the vertical axis represents the positional deviation of the driven object 44 relative to the target position.

[0089] like Figure 4 As shown in this specification, the allowable range refers to the range in which the positional deviation from the target position is within the required accuracy.

[0090] In addition, such as Figure 4As shown in this specification, the moment when the target position is reached (hereinafter also referred to as the "setting moment") is the moment when the driven object 44 is last within the allowable range after it has reached the allowable range and has not exceeded the allowable range again.

[0091] In addition, such as Figure 4 As shown, in this specification, the setting time refers to the time from the start of the stop of the drive object 44 based on the instruction to move the drive object 44 to the end of the time until the drive object 44 reaches an allowable position that can be evaluated as having reached the target position; that is, the time from the start of the stop to the setting time. Alternatively, the setting time refers to the time from the start of the movement of the drive object 44 based on the instruction to move the drive object 44 to the end of the time until the drive object 44 reaches an allowable position that can be evaluated as having reached the target position; that is, the time from the start of the movement to the setting time.

[0092] Figure 5 This is a simplified diagram illustrating an example of the measurement data 33 output by sensor 3.

[0093] like Figure 5 As shown, measurement data 33 is data that corresponds one-to-one with the elapsed time [ms] after the reference time and the deviation [mm] relative to the target position. Here, the reference time is the stop start time of the drive object 44 based on the command to move the drive object 44 to the target position, or the movement start time of the drive object 44 based on the command to move the drive object 44 to the target position.

[0094] Reference Figure 1 The inference model 34 is a learned model obtained through machine learning for optimizing the control parameters 31. The inference model 34 may also include a machine learning program. Alternatively, a machine learning program may be used instead of the inference model 34 to optimize the control parameters 31. The update unit 24 uses the inference model 34 to perform optimization that shortens the longest settling time among the settling times corresponding to each action contained in the representative action. Thus, the control parameters 31 are updated. Furthermore, the optimization object is not limited to the longest settling time; it can be the average of multiple settling times, or multiple settling times or their average, ordered from longest to shortest.

[0095] It can use known algorithms such as Bayesian optimization, evolutionary strategy algorithm (CMA-ES), or genetic algorithm (GA) as the optimization algorithm.

[0096] The information processing unit 11 and / or storage unit 12 may also be installed in an external terminal or server device capable of communicating with the control parameter generation device 1. The external terminal may include a personal computer, smartphone, or tablet terminal, etc. The server device may include an edge server or cloud server, etc.

[0097] The input section 13 is constructed using any input device such as a mouse, keyboard, or touchscreen.

[0098] The display unit 14 is constructed using any display device such as a liquid crystal display or an organic EL (electroluminescence) display.

[0099] The communication unit 15 is constructed using a communication module that corresponds to any communication method such as Bluetooth (registered trademark) or Wi-Fi.

[0100] The communication unit 15 sends the control parameters 31 stored in the storage unit 12 to the production unit 2. If the production unit 2 receives the control parameters 31 from the control parameter generation device 1, the storage unit 41 uses the received new control parameters 31 to overwrite the stored control parameters 31. That is, the control parameters 31 are updated.

[0101] In addition, the communication unit 15 sends a control signal to the production unit 2 to execute the representative action or evaluation action. If the production unit 2 receives the control signal from the control parameter generation device 1, the control unit 42 controls the drive unit 43 based on the control signal and the control parameters 31 read from the storage unit 41, thereby executing the representative action or evaluation action.

[0102] Figure 6 This is a flowchart showing the processes performed by the information processing unit 11.

[0103] First, in step SP01, the update unit 24 sets the initial value of the control parameter 31. The initial value can be a predetermined value, a value input by the user using the input unit 13, or a value calculated by the update unit 24 using a calculation method input by the user using the input unit 13. The initial value of the control parameter 31 set by the update unit 24 is stored in the storage unit 12 and sent to the production unit 2 by the communication unit 15. The production unit 2 stores the received initial value of the control parameter 31 in the storage unit 41.

[0104] Next, in step SP02, the selection unit 21 sets the initial value of an integer variable representing the number of actions X. The selection unit 21 sets the initial value of the integer variable to 1 as the number of actions X for the first stage, referring to selection rule 32. Furthermore, although this embodiment describes an example where the initial value of the integer variable is 1, the initial value can be any integer between 1 and N-1, and is not necessarily limited to 1. Additionally, the initial value of the integer variable can also be specified by the user through operation input using the input unit 13.

[0105] Next, in step SP03, the information processing unit 11 performs control parameter optimization processing.

[0106] Figure 7 It is a flowchart showing the details of the control parameter optimization process.

[0107] First, in step SP031, the selection unit 21 selects X representative actions from all N actions by referring to selection rule 32. Specifically, the selection unit 21 selects action 2 as the representative action for the first stage.

[0108] Next, in step SP032, the control unit 22 generates a control signal that instructs the production device 2 to execute the representative action selected by the selection unit 21. The control signal generated by the control unit 22 is sent to the production device 2 by the communication unit 15. If the production device 2 receives the control signal, the control unit 42 controls the drive unit 43 based on the control signal and the control parameters 31 read from the storage unit 41, thereby executing the representative action containing X actions. If the production device 2 executes X actions, the sensor 3 sends X measurement data 33 corresponding to the X actions contained in the representative action to the control parameter generation device 1. The communication unit 15 receives the X measurement data 33 sent from the sensor 3, stores the X measurement data 33 in the storage unit 12, and inputs it to the information processing unit 11.

[0109] Next, in step SP033, the acquisition unit 23 acquires X measurement data 33 from the communication unit 15, each corresponding to one of the X actions contained in the representative action.

[0110] Next, in step SP034, the update unit 24 calculates the evaluation value of the evaluation index for each of the X measurement data 33 acquired by the acquisition unit 23. In this embodiment, the update unit 24 calculates the settling time for each of the X measurement data 33.

[0111] Next, in step SP035, the update unit 24 uses the inference model 34 to perform optimization that shortens the longest settling time among the X settling times related to the X measurement data 33, thereby updating the control parameter 31. The updated control parameter 31 is stored in the storage unit 12 and sent to the production unit 2 by the communication unit 15. The production unit 2 stores the received updated control parameter 31 in the storage unit 41.

[0112] Next, in step SP036, the production unit 26 generates waveforms based on the measurement data 33 of the time series related to each of the X actions. It generates an overlay image by overlapping the X waveforms related to the X actions and then generates an operation screen containing this overlay image. For example, the production unit 26 uses the longest settling time among the X settling times as an evaluation value related to the representative action, and generates image data containing the evaluation result representing that evaluation value. Furthermore, the output unit 25 inputs the operation screen data generated by the production unit 26 to the display unit 14, causing the display unit 14 to display the operation screen.

[0113] Reference Figure 6 In step SP04, following step SP03, the control unit 22 determines whether the prescribed representative action termination condition is met. The target value of the evaluation value in each stage can be set as the representative action termination condition, as can the upper limit of the number of repetitions of the optimization process in each stage, or the upper limit of the execution time of the optimization process in each stage. For example, if the target value of the evaluation value is set as the representative action termination condition, the control unit 22 determines that the representative action termination condition is not met if the evaluation value of the most recent representative action (the longest settling time among X settling times) exceeds the target value, and determines that the representative action termination condition is met if the evaluation value of the most recent representative action is below the target value.

[0114] If the representative action termination condition is not met (step SP04: No), then in step SP05, the control unit 22 determines whether the prescribed evaluation execution conditions are met. The evaluation execution conditions include the condition that a certain amount of time has elapsed since the reference time. The reference time includes the start time of the execution of the first representative action in each stage and the start time of the execution of the last evaluation action. The control unit 22 has a timer that resets its value at the reference time. When the timer's value reaches or exceeds a threshold, it determines that a certain amount of time has elapsed since the reference time. Additionally, the evaluation execution conditions include the condition that the number of times the representative actions in each stage have been executed has reached a certain number. The control unit 22 has a counter that resets its value before the execution of the first representative action in each stage begins, and increments the counter each time a representative action is executed. When the counter's value reaches or exceeds a threshold, the control unit 22 determines that the number of times the representative actions in each stage have been executed has reached a certain number.

[0115] If the evaluation execution conditions are not met (step SP05: No), the processing after step SP03 is executed.

[0116] If the evaluation execution conditions are met (step SP05: Yes), then in step SP06, the information processing unit 11 performs evaluation result output processing. The processing in step SP06 is equivalent to the evaluation result output processing performed during the period when the representative actions of each stage are executed.

[0117] Figure 8 This is a flowchart showing the details of the evaluation result output processing.

[0118] First, in step SP061, the control unit 22 sets the evaluation action conditions for performing the evaluation action.

[0119] The evaluation action conditions include action specification information, which specifies the action to be performed among all N actions. The evaluation action can also be all actions. By having production unit 2 perform all actions as the evaluation action, accurate comprehensive evaluation can be performed. Alternatively, the evaluation action can be the difference between all actions and the nearest representative action of that evaluation action. By having production unit 2 perform the difference between all actions and the nearest representative action of that evaluation action as the evaluation action, the accuracy of the comprehensive evaluation can be maintained, and the efficiency of the evaluation action can be improved. Furthermore, the evaluation action can also be a pre-defined action from all actions. By having production unit 2 perform a pre-defined action from all actions as the evaluation action, the efficiency of the evaluation action can be improved.

[0120] Furthermore, the evaluation action conditions include setting information for the value of control parameter 31 when performing the evaluation action. Alternatively, the latest control parameter 31 stored in the storage unit 41 at the current time point can be used directly as the control parameter 31 when performing the evaluation action. Or, the control parameter 31 for the next evaluation action can be set based on multiple evaluation values ​​related to multiple representative actions performed during the period from the execution time of the previous evaluation action to the current time point. For example, the control unit 22 determines the optimal evaluation value from multiple evaluation values ​​related to multiple representative actions performed during the period from the execution time of the previous evaluation action to the current time point, and sets the control parameter 31 set when performing the representative action corresponding to the optimal evaluation value as the control parameter 31 for the next evaluation action. This improves the evaluation accuracy of the comprehensive evaluation performed by performing the evaluation action.

[0121] Next, in step SP062, the control unit 22 generates a control signal that instructs the production unit 2 to perform the evaluation actions set in step SP061. The control signal generated by the control unit 22 is sent to the production unit 2 by the communication unit 15. If the production unit 2 receives the control signal, the control unit 42 controls the drive unit 43 based on the control signal and the control parameters 31 read from the storage unit 41, thereby performing the evaluation actions. If the production unit 2 performs the evaluation actions, the sensor 3 sends measurement data 33 corresponding to each action included in the evaluation actions to the control parameter generation device 1. The communication unit 15 receives the measurement data 33 sent from the sensor 3, stores the measurement data 33 in the storage unit 12, and inputs it to the information processing unit 11.

[0122] Next, in step SP063, the acquisition unit 23 acquires measurement data 33 corresponding to each action included in the evaluation action from the communication unit 15.

[0123] Next, in step SP064, the manufacturing unit 26 calculates the evaluation value of the evaluation index for each measurement data 33 acquired by the acquisition unit 23. In this embodiment, the manufacturing unit 26 calculates the settling time for each measurement data 33 and takes the longest settling time among the multiple settling times related to the multiple measurement data 33 as the evaluation value related to this evaluation operation.

[0124] Next, in step SP065, the production unit 26 generates waveforms based on the time series measurement data 33 related to each action included in the evaluation action. It generates an overlay image by overlaying multiple waveforms related to the multiple actions included in the evaluation action, and then generates an operation screen containing this overlay image. For example, the production unit 26 uses the longest settling time among multiple settling times as the evaluation value related to the current evaluation action, and generates image data containing the evaluation result representing this evaluation value. Furthermore, the output unit 25 inputs the data from the operation screen generated by the production unit 26 to the display unit 14, causing the display unit 14 to display the operation screen.

[0125] Reference Figure 6 In step SP07, following step SP06, the control unit 22 determines whether the prescribed optimization termination conditions are met. The optimization termination condition can be set as a target value of the evaluation value related to the evaluation action, an upper limit on the total number of iterations of optimization processes related to all stages up to the current time point, or an upper limit on the execution time of optimization processes related to all stages up to the current time point. For example, if the target value of the evaluation value is set as the optimization termination condition, the control unit 22 determines that the optimization termination condition is not met if the evaluation value (maximum settling time) of the most recent evaluation action exceeds the target value, and determines that the optimization termination condition is met if the evaluation value of the most recent evaluation action is below the target value.

[0126] If the optimization termination condition is not met (step SP07: No), the processing after step SP03 is executed.

[0127] If the optimization termination condition is met (step SP07: Yes), the optimization process for control parameter 31 ends. Even if the representative action reaches its final stage, the optimization process will end if the evaluation result of the comprehensive evaluation obtained by performing the evaluation action meets the optimization termination condition, thus shortening the time required for optimization.

[0128] If the representative action termination condition is met in step SP04 (step SP04: Yes), then in step SP08, the selection unit 21 determines whether the number of actions X contained in the representative action is equal to the total number of actions N.

[0129] When X equals N (step SP08: Yes), it means the action has reached the final stage (in Figure 3 In the example, this is stage 8, therefore, the optimization process for control parameter 31 ends.

[0130] If X is less than N (step SP08: No), it means the action has not yet reached the final stage. Therefore, in step SP09, the selection unit 21 updates X by referring to selection rule 32. That is, the selection unit 21 transitions from the current stage to the next stage and selects X representative actions from all N actions.

[0131] Next, in step SP10, the control unit 22 determines whether the prescribed evaluation execution conditions are met. The evaluation execution conditions include the condition that a certain amount of time has elapsed since the reference time. The reference time includes the start time of the previous evaluation action. The control unit 22 has a timer; it resets the timer's value at the reference time, and determines that a certain amount of time has elapsed since the reference time when the timer's value reaches or exceeds a threshold.

[0132] If the evaluation execution conditions are not met (step SP10: No), the processing after step SP03 is executed.

[0133] If the evaluation execution conditions are met (step SP10: Yes), then in step SP11, the information processing unit 11 performs evaluation result output processing. The processing in step SP11 is equivalent to the evaluation result output processing performed during the transition from one stage to the next. Details of the evaluation result output processing in step SP11 are provided by... Figure 8 The flowchart shown is an example. Alternatively, the following structure can be used: the decision-making process in step SP10 is omitted, and step SP11 is always executed if X is updated.

[0134] Next, in step SP12, the control unit 22 determines whether the prescribed optimization termination condition is met. The details of the optimization termination condition in step SP12 are the same as those in step SP07.

[0135] If the optimization termination condition is not met (step SP12: No), the processing after step SP03 is executed.

[0136] If the optimization termination condition is met (step SP12: Yes), the optimization process for control parameter 31 ends. Even if the representative action reaches its final stage, the optimization process will end if the evaluation result of the comprehensive evaluation obtained by performing the evaluation action meets the optimization termination condition, thus shortening the time required for optimization.

[0137] Figure 9 This is a simplified illustration of an example of an operation screen 100 created in step SP036 based on the result of a representative action.

[0138] The operation screen 100 includes an overlay image 101, which overlays multiple waveforms K (K1 to K4) representing actions on a time axis. Waveform K is an example of waveform information. The overlay image 101 includes an upper limit value ThH and a lower limit value ThL within an allowed range.

[0139] Additionally, the operation screen 100 includes an overlay image 102, which overlays multiple evaluation values ​​calculated based on multiple waveforms K (K1 to K4) related to multiple (four in this example) representative actions on a time axis. The evaluation values ​​are an example of waveform information. Figure 9 In the example, the evaluation value is the settling time P (P1~P4). The settling time P1 corresponding to waveform K1 and the settling time P2 corresponding to waveform K2 are below the target settling time, thus achieving the target performance. The settling time P3 corresponding to waveform K3 and the settling time P4 corresponding to waveform K4 exceed the target settling time, thus failing to achieve the target performance.

[0140] In the creation of the overlapping images 101 and 102, the production unit 26 differentiates the display formats of waveforms (waveforms K1, K2 and settling times P1, P2) that have achieved the target values ​​for the evaluation criteria from those of waveforms (waveforms K3, K4 and settling times P3, P4) that have not achieved the target values. For example, the production unit 26 uses blue to color waveforms K1, K2 and settling times P1, P2, and uses red to color waveforms K3, K4 and settling times P3, P4.

[0141] In addition, the operation screen 100 includes a waveform display selection bar. The waveform display selection bar includes a first input field 103 for selecting waveform information that has achieved the target value of the evaluation index from among multiple waveform information, and a second input field 104 for selecting waveform information that has not achieved the target value.

[0142] Users can input selection information (checkmarks) into the first input field 103 and the second input field 104 using the input unit 13. The selection information input from the input unit 13 is processed by the processing unit 27.

[0143] In the creation of the overlay images 101 and 102, when selection information is entered into the first input field 103, the creation unit 26 includes the waveform information (waveforms K1, K2 and settling times P1, P2) that has achieved the target value from among the multiple waveform information in the overlay images 101 and 102. On the other hand, when no selection information is entered into the first input field 103, the creation unit 26 does not include the waveform information (waveforms K1, K2 and settling times P1, P2) that has achieved the target value from among the multiple waveform information in the overlay images 101 and 102.

[0144] Furthermore, during the creation of the overlapping images 101 and 102, when selection information is entered into the second input field 104, the creation unit 26 includes the waveform information (waveforms K3, K4 and settling times P3, P4) that did not achieve the target value from among the multiple waveform information in the overlapping images 101 and 102. On the other hand, when no selection information is entered into the second input field 104, the creation unit 26 does not include the waveform information (waveforms K3, K4 and settling times P3, P4) that did not achieve the target value from among the multiple waveform information in the overlapping images 101 and 102.

[0145] exist Figure 9 In the example shown, selection information was entered into both the first input field 103 and the second input field 104. Therefore, the overlapping images 101 and 102 contain waveforms K1 to K4 and setting times P1 to P4.

[0146] Additionally, the operation screen 100 includes an evaluation index selection bar. This evaluation index selection bar includes a first input field 105 for selecting a first evaluation index (setup time in this example) as the evaluation index, and a second input field 106 for selecting a second evaluation index (torque deviation in this example) as the evaluation index. Furthermore, it may also include input fields for selecting other evaluation indexes such as overshoot amount.

[0147] Users can input selection information (checkmarks) into the first input field 105 and the second input field 106 using the input unit 13. The selection information input from the input unit 13 is processed by the processing unit 27.

[0148] In the creation of waveform K, when selection information is entered into the first input field 105, the production unit 26 creates waveform K based on multiple measurement data 33 of time series related to the first evaluation index (set time) measured by position sensors during the execution of each action representing the action.

[0149] On the other hand, when selection information is entered into the second input field 106, waveform K is generated based on multiple measurement data 33 of time series related to the second evaluation index (torque deviation) measured by torque sensors during the execution of each action representing the action.

[0150] exist Figure 9 In the example shown, selection information was entered in the first input field 105, therefore, the settling time was used as an evaluation metric.

[0151] Furthermore, in the overlay image 101, if the user moves the mouse pointer over any waveform K using the operation input of the input unit 13, the selection information of waveform K will be processed by the receiving unit 27. The production unit 26 displays a tooltip 107 for changing the representative action near the selected waveform K. The tooltip 107 includes: adding an item, which is checked by the user when they want to add the selected waveform K to the representative action in the next stage; and deleting an item, which is checked by the user when they want to delete the selected waveform K from the representative action in the current stage. The selection unit 21 changes the representative action based on the selection information input in the tooltip 107.

[0152] Furthermore, in the overlay image 102, if the user moves the mouse pointer to any set time P using the operation input of the input unit 13, the selection information of the set time P will be received by the receiving unit 27. The production unit 26 will highlight (e.g., display in thick lines) the waveform K corresponding to the selected set time P in the overlay image 101.

[0153] Figure 10 This is a simplified illustration of an example of an operation screen 200 created in step SP065 based on the results of the evaluation action.

[0154] The operation screen 200 includes an overlay image 201, which overlays multiple waveforms L (L1 to L5) associated with multiple (five in this example) evaluation actions on the time axis. Waveform L is an example of waveform information. The overlay image 201 includes an upper limit value ThH and a lower limit value ThL within the allowed range.

[0155] Additionally, the operation screen 200 includes an overlay image 202, which superimposes multiple evaluation values ​​calculated based on multiple waveforms L (L1 to L5) associated with multiple (five in this example) evaluation actions on a time axis. The evaluation values ​​are an example of waveform information. Figure 10 In the example, the evaluation value is the settling time Q(Q1~Q5). The settling times Q1~Q5 corresponding to waveforms L1~L5 all exceed the target settling time, and the target performance is not achieved.

[0156] In the creation of waveform L, the production unit 26 generates multiple waveforms for each evaluation action by having the production device 2 execute each action multiple times. In the creation of overlapping images 201 and 202, the production unit 26 selects the waveform information with the best evaluation value from among the multiple waveform information related to each action. The production unit 26 generates overlapping images 201 and 202 by overlapping multiple optimal waveform information (waveforms L1 to L5 and setpoint times Q1 to Q5) related to multiple actions.

[0157] Similar to the operation screen 100, in the production of the overlapping images 201 and 202, the production unit 26 makes the display form of the waveform information that has achieved the target value of the evaluation index different from the display form of the waveform information that has not achieved the target value.

[0158] Additionally, the operation screen 200 includes a waveform display selection bar. The waveform display selection bar includes a first input field 203 for selecting waveform information that has achieved the target value of the evaluation index from among multiple waveform information, and a second input field 204 for selecting waveform information that has not achieved the target value.

[0159] Users can input selection information (checkmarks) into the first input field 203 and the second input field 204 by using the input unit 13. The selection information input from the input unit 13 is processed by the processing unit 27.

[0160] In the creation of the overlapping images 201 and 202, when selection information is entered into the first input field 203, the creation unit 26 includes the waveform information that has achieved the target value from among the multiple waveform information in the overlapping images 201 and 202. On the other hand, when no selection information is entered into the first input field 203, the creation unit 26 does not include the waveform information that has achieved the target value from among the multiple waveform information in the overlapping images 201 and 202.

[0161] Furthermore, during the creation of the overlapping images 201 and 202, when selection information is entered into the second input field 204, the creation unit 26 includes the waveform information (waveforms L1 to L5 and setpoint times Q1 to Q5) that did not achieve the target value from among the multiple waveform information in the overlapping images 201 and 202. On the other hand, when no selection information is entered into the second input field 204, the creation unit 26 does not include the waveform information (waveforms L1 to L5 and setpoint times Q1 to Q5) that did not achieve the target value from among the multiple waveform information in the overlapping images 201 and 202.

[0162] exist Figure 10 In the example shown, no selection information was entered in the first input field 203, and selection information was entered in the second input field 204. Therefore, the overlapping images 201 and 202 contain waveform information (waveforms L1 to L5 and set times Q1 to Q5) that did not achieve the target value.

[0163] Additionally, when selection information is entered in the second input field 204, the production department 26 also includes the selection items 204A and 204B for waveforms that have not been achieved in the operation screen 200. If the user wants to display the waveform L of an action that has not achieved the target value even once up to the current time point, the user enters a checkmark for selection item 204A. If the user wants to display the waveform information of an action whose evaluation value at the current time point is "worst 5", the user enters a checkmark for selection item 204B. Figure 10 In the example, selection information was input into selection item 204B. Therefore, the waveform information (waveforms L1 to L5 and settling times Q1 to Q5) of the action with an evaluation value of "worst 5" at the current time point is included in the overlapping images 201 and 202. Furthermore, the number of actions selected through selection item 204B is not limited to "worst 5". In addition to selection items 204A and 204B, selection items based on other viewpoints can be further added.

[0164] Additionally, the operation screen 200 includes an evaluation index selection bar. This bar includes a first input field 205 for selecting a first evaluation index (setup time in this example) and a second input field 206 for selecting a second evaluation index (torque deviation in this example). Furthermore, it may also include input fields for selecting other evaluation indexes such as overshoot.

[0165] Users can input selection information (checkmarks) into the first input field 205 and the second input field 206 respectively by using the operation input of the input unit 13. The selection information input from the input unit 13 is processed by the processing unit 27.

[0166] In the creation of waveform L, when selection information is entered into the first input field 205, the production unit 26 creates waveform L based on multiple measurement data 33 of time series related to the first evaluation index (set time) measured by the position sensor during the execution of each action of the evaluation action.

[0167] On the other hand, when selection information is entered in the second input field 206, waveform L is generated based on multiple measurement data 33 of time series related to the second evaluation index (torque deviation) measured by torque sensors during the execution of each action of the evaluation action.

[0168] exist Figure 10 In the example shown, selection information was entered in the first input field 205, therefore, the settling time was used as an evaluation metric.

[0169] Furthermore, in the overlay image 201, if the user moves the mouse pointer over any waveform L using the operation input of the input unit 13, the selection information of waveform L will be received by the receiving unit 27. The production unit 26 will display a prompt box 207 near the selected waveform L, which explains the detailed action corresponding to the selected waveform L. The prompt box 207 includes information indicating the date on which the measurement data 33 was obtained with the execution of the action, information indicating the number of adjustments for the action, and information indicating the performance display of the action (in this example, the set time).

[0170] Furthermore, in the overlay image 202, if the user moves the mouse pointer to any set time Q using the operation input of the input unit 13, the selection information of the set time Q will be received by the receiving unit 27. The production unit 26 will highlight (e.g., display in thick lines) the waveform L corresponding to the selected set time Q in the overlay image 201.

[0171] According to the control parameter generation apparatus 1 of this embodiment, the information processing unit 11 generates overlapping images 101, 102, 201, and 202 by overlapping multiple waveform information related to multiple actions, and generates operation screens 100 and 200 including the overlapping images 101, 102, 201, and 202. In this way, multiple waveform information is displayed overlappingly on the display unit 14, thereby providing useful information to the user in a clear and understandable manner. Furthermore, one of the overlapping images 101 and 102 can be omitted, and one of the overlapping images 201 and 202 can also be omitted.

[0172] The following describes various modifications related to the embodiments of this disclosure. These modifications can be applied in any combination.

[0173] (First variation)

[0174] Figure 11This is a simplified representation of the overlapping images 101 and 102 involved in the first variation. The production unit 26 produces an overlapping image 101 containing multiple waveforms K and a graphic G1 represented by vertical lines. The graphic G1 is used to represent the evaluation value corresponding to the waveform with the worst evaluation value among the multiple waveforms K (in this example, the longest settling time P). The output unit 25 inputs the data of the operation screen 100 produced by the production unit 26 to the display unit 14, causing the display unit 14 to display the operation screen 100. Furthermore, the graphic G1 used to represent the worst evaluation value is not limited to overlapping multiple waveforms related to multiple actions contained in the representative action; it may also be overlapping multiple waveforms related to multiple actions contained in the evaluated action, multiple waveforms related to multiple actions contained in all actions, or multiple waveforms related to any multiple actions. In addition, the operation screen 100 may also be a simple screen without user operation.

[0175] According to this variation, the overlay image 101 includes a graphic G1, which represents the evaluation value corresponding to the waveform information with the worst evaluation value among multiple waveform information regarding the evaluation index. Therefore, the user can immediately identify the worst evaluation value among the multiple evaluation values ​​corresponding to multiple waveform information, thus improving user convenience.

[0176] (Second variation)

[0177] Figure 12 This is a simplified representation of the overlapping images 101 and 102 involved in the second variation. The production unit 26 produces an overlapping image 101 containing multiple waveforms K and graphics G1 and G2 represented by vertical lines. Graphic G1 represents the evaluation value corresponding to the waveform with the worst evaluation value among the multiple waveforms K (in this example, the longest settling time P). Graphic G2 represents the evaluation value corresponding to the evaluation action whose worst evaluation value (in this example, the longest settling time Q) among the multiple evaluation actions performed up to the current time point is the best evaluation action. The evaluation action can also be all actions. The output unit 25 inputs the data of the operation screen 100 produced by the production unit 26 to the display unit 14, causing the display unit 14 to display the operation screen 100.

[0178] Figure 13 This is a simplified representation of the overlapping images 201 and 202 involved in the second variation. Figure 12In the overlay image 101 shown, if a user clicks the mouse by moving the mouse pointer over graphic G2 using the input unit 13, the selection information for graphic G2 will be received by the receiving unit 27. The production unit 26 produces overlay images 201 and 202, which correspond to the evaluation action whose worst evaluation value among multiple waveforms L has been optimal among multiple evaluation actions performed up to the current time point. Overlay image 201 includes multiple waveforms L and graphic G2. Overlay image 202 includes multiple evaluation values ​​(in this example, multiple setpoint times Q) corresponding to the multiple waveforms L. Figure 13 The image shows the waveform L and settling time Q associated with the four evaluation actions. However, if the evaluation actions are all actions, the overlapping images 201 and 202 may also include the waveform L and settling time Q associated with all actions.

[0179] According to this variation, users can easily compare the evaluation value of the representative action with the best evaluation value up to the current time, thus improving user convenience.

[0180] (3rd variation)

[0181] Figure 14 This is a simplified representation of the overlapping images 101 and 102 involved in the third variation. Figure 9 , 11 In the overlay image 101 shown in Figures 1 and 12, if a user clicks the mouse while moving the mouse pointer over any waveform K using the operation input of the input unit 13, the selection information of that waveform K will be received by the receiving unit 27. The production unit 26 reads past measurement data 33 related to the action corresponding to the selected waveform K from the storage unit 12 and produces overlay images 101 and 102 that overlay multiple waveform information related to the action. Overlay image 101 includes multiple waveforms K related to the action and a graphic G3 represented by vertical lines. Graphic G3 is a graphic representing the evaluation value corresponding to the waveform with the best evaluation value (in this example, the minimum settling time P) among the multiple waveforms K related to the action. The output unit 25 inputs the data of the operation screen 100 produced by the production unit 26 to the display unit 14, causing the display unit 14 to display the operation screen 100.

[0182] According to this modified example, overlapping images 101 and 102 related to a specific action corresponding to the waveform K selected by the user are displayed in the display unit 14, thereby improving the convenience for the user.

[0183] (4th variation)

[0184] Figure 15This is a simplified representation of the overlapping images 101 and 102 involved in the fourth variation. In the aforementioned overlapping images 102 and 202, multiple evaluation values ​​are represented on the time axis by plotting circles. However, if the number of evaluation values ​​increases, the multiple circles will overlap each other, resulting in decreased recognizability. Therefore, the production unit 26 uses curve W to produce the overlapping image 102, which uses the height of the peaks to represent the frequency distribution of the multiple evaluation values. In addition, curve W can also use the color category or the grayscale intensity, etc., instead of the height of the peaks to represent the frequency distribution.

[0185] According to this variation, the recognizability of overlapping images 102 and 202 containing multiple evaluation values ​​can be improved.

[0186] (5th variation)

[0187] Figure 16 This is a simplified representation of the overlapping image 101. In the above description, the update unit 24 performed optimization to shorten the longest settling time among the settling times corresponding to each action included in the representative action. Here, the target settling time for each action varies depending on the movement distance, etc., in each action. For example, as... Figure 16 As shown, the target settling time Tb associated with the waveform Ka of actions with longer movement distances is shorter than that associated with the waveform Kb of actions with shorter movement distances.

[0188] Therefore, the target timing of each action is pre-stored in the storage unit 12. In the production of the overlapping images 101 and 201, the production unit 26 shifts or scales the waveform K of each action in the time axis direction so that the target timing of each action is consistent on the time axis.

[0189] Figure 17 This is a simplified illustration of the first example of the overlapping image 101 involved in the fifth variation. The fabrication unit 26 shifts the waveform Kb on the time axis (in this example, shifting it to the right) in such a way that the target set time Tb is consistent with the target set time Ta, thereby causing the waveform Kb1 to overlap the waveform Ka instead of the waveform Kb.

[0190] Figure 18 This is a simplified illustration of the second example of the overlapping image 101 involved in the fifth variation. The production unit 26 scales the waveform Kb on the time axis (in this example, scaling to the right) so that the target tuning time Tb is consistent with the target tuning time Ta, thereby causing the waveform Kb2 to overlap the waveform Ka instead of the waveform Kb.

[0191] According to this modified example, waveform information after offset or scaling of the target value of the evaluation index according to each action can be displayed. Therefore, the waveform information with the worst evaluation value (i.e., the waveform information that is the object of update of the update unit 24) can be appropriately determined, and the convenience for the user can be improved.

[0192] Industrial availability

[0193] This disclosure can be widely applied to systems for generating control parameters, etc.

Claims

1. An information processing method for optimizing the control parameters in a device that performs an action based on multiple control parameters, characterized in that, Information Processing Department To cause the device to perform multiple actions included in all the actions that the device is capable of performing. Obtain multiple time-series measurement data related to specified evaluation indicators, measured during the execution of each of the multiple actions. A waveform is generated based on the multiple measurement data related to each action. An overlapping image is created by overlaying the multiple waveform information related to the multiple actions. An operation screen containing the overlapping image is then generated. The operation screen is displayed on the display unit by inputting the data from the operation screen to the display unit.

2. The information processing method according to claim 1, characterized in that, The multiple actions are all the actions, or multiple representative actions selected from all the actions.

3. The information processing method according to claim 2, characterized in that, The system accepts input of selection information, which is used to select one waveform from the plurality of waveforms contained in the operation screen displayed on the display unit. Based on the selection information, the representative action is changed.

4. The information processing method according to claim 1, characterized in that, The multiple waveform information refers to multiple waveforms related to the multiple actions, or multiple evaluation values ​​calculated based on the multiple waveforms.

5. The information processing method according to claim 1, characterized in that, In the creation of the overlapping image, the display form of the waveform information that achieves the target value of the evaluation index is different from the display form of the waveform information that does not achieve the target value.

6. The information processing method according to claim 1, characterized in that, The operation screen also includes: a first input field, used to select and display the waveform information that has achieved the target value of the evaluation index from the plurality of waveform information; And the second input field is used to select and display the waveform information when the target value is not achieved. In the creation of the overlapping image, When selection information is entered in the first input field, the waveform information that achieves the target value from among the multiple waveform information is included in the overlapping image. When selection information is entered in the second input field, the waveform information that does not achieve the target value among the plurality of waveform information is included in the overlapping image.

7. The information processing method according to claim 1, characterized in that, The operation screen also includes a first input field for selecting a first evaluation indicator as the evaluation indicator, and a second input field for selecting a second evaluation indicator as the evaluation indicator. In the creation of the waveform, When selection information is entered in the first input field, the waveform is generated based on the multiple measurement data of the time series related to the first evaluation index, measured during the execution of each action. When selection information is entered in the second input field, the waveform is generated based on the multiple measurement data of the time series related to the second evaluation index measured during the execution of each action.

8. The information processing method according to claim 1, characterized in that, In the creation of the waveform, multiple waveforms are generated for each action by having the device perform each action multiple times. In the creation of the overlapping image, Select the waveform information with the best evaluation value for the evaluation index from among multiple waveform information related to each action. The overlapping image is created by overlaying multiple optimal waveform information related to the multiple actions.

9. The information processing method according to claim 1, characterized in that, In the creation of the overlapping image, Based on the target value of each action with respect to the evaluation index, the waveform information associated with each action is shifted or scaled in the time axis direction.

10. An information processing method for optimizing the control parameters in a device that performs an action based on multiple control parameters, characterized in that, Information Processing Department The device is instructed to perform multiple actions. Obtain multiple time-series measurement data related to specified evaluation indicators, measured during the execution of each of the multiple actions. A waveform is generated based on the multiple measurement data related to each action. An overlapping image is created by overlaying the multiple waveform information related to the multiple actions, and a picture containing the overlapping image is generated. By inputting the data of the screen to the display unit, the display unit displays the screen. The overlapping image contains a graphic representing the evaluation value of the waveform information with the worst evaluation value for the evaluation index among the plurality of waveform information.

11. An information processing apparatus for optimizing the control parameters in an apparatus for performing actions based on multiple control parameters, characterized in that... include: The control unit instructs the device to perform multiple actions included in all the actions that the device is capable of performing; The acquisition unit acquires multiple measurement data related to a specified evaluation index, obtained during the execution of each of the multiple actions; The production department generates waveforms based on the multiple measurement data related to each action, generates an overlapping image by overlapping multiple waveform information related to the multiple actions, and generates an operation screen containing the overlapping image. as well as The output unit inputs the data from the operation screen to the display unit, causing the display unit to display the operation screen.

12. A program that causes an information processing device to perform processing, the information processing device being used to optimize the control parameters in a device that performs an action based on a plurality of control parameters, the program being characterized in that, The process, To cause the device to perform multiple actions included in all the actions that the device is capable of performing. Obtain multiple time-series measurement data related to specified evaluation indicators, measured during the execution of each of the multiple actions. A waveform is generated based on the multiple measurement data related to each action. An overlapping image is created by overlaying the multiple waveform information related to the multiple actions. An operation screen containing the overlapping image is then generated. The operation screen is displayed on the display unit by inputting the data from the operation screen to the display unit.

Images