CN110716509B - Production system with quality measurement and mechanism diagnosis functions, driver and method thereof - Google Patents
Production system with quality measurement and mechanism diagnosis functions, driver and method thereof Download PDFInfo
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Abstract
The present disclosure relates to a production system with quality measurement and mechanism diagnosis functions, and a driver and a method thereof, wherein the production system is a layered data processing architecture, and the driver comprises a real system driving module and a virtual system driving module. The real system driving module generates real operation parameter information of the mechanism. The virtual system driving module establishes at least one virtual mechanism model in a system identification mode. The virtual system driving module comprises a quality measurement and mechanism diagnosis parameter processing module, and is used for generating mechanism simulation operation parameter information according to a processing strategy of the controller, the mechanism real operation parameter information and the virtual mechanism model, and realizing the quality measurement, the mechanism diagnosis and/or the adjustment of the processing strategy through the mechanism real operation parameter information and the mechanism simulation operation parameter information.
Description
Technical Field
The present disclosure relates to manufacturing systems, and more particularly to a manufacturing system with quality measurement and mechanism diagnosis functions, and a driver and a method thereof.
Background
To achieve this goal, all the semi-finished products and the finished products must be inspected completely during the production process, but in order to do so, a large number of measurement machines must be purchased, and a large amount of production time is consumed. In view of cost and time, the quality of the finished product is monitored by a spot check method, but this method cannot achieve a comprehensive quality control. Therefore, in order to economically achieve the objective of full inspection, Virtual Measurement (VM) technology is complied with and applied to a production system having production equipment.
The virtual measurement technique is widely applied to production equipment for products such as semiconductors, panels, or solar energy, and under the condition that the products are not actually measured or can not be actually measured, the operation parameters of the production equipment for producing the processed products are used for estimating the quality of the processed products, so as to predict the quality of the processed products on line and in real time, thereby achieving the effect of full inspection, so that the abnormity of the processed products can be found in real time, and the major loss can be avoided.
However, the conventional virtual measurement technique cannot achieve both immediacy and accuracy, i.e., if the virtual measurement value is to be output in real time, the accuracy of the virtual measurement value is not high, and if the accuracy of the virtual measurement value is to be ensured, the virtual measurement value cannot be output in real time. In addition, the conventional virtual measurement technique can only predict the virtual measurement value, but cannot provide a confidence index of the virtual measurement value, i.e., the user cannot confirm the reliability of the virtual measurement value and cannot be applied with care. Moreover, the physical characteristics of the same type of machines or manufacturing facilities are still different, and in order to maintain the estimation accuracy of the virtual measurement, the virtual prediction model must be constructed according to the machine or equipment characteristic data of each machine or manufacturing facility, and if the virtual measurement technique is introduced to each machine or manufacturing facility of the whole plant, it will consume a lot of labor and cost. To solve the above problems, a fully automated virtual measurement server and method are developed and applied.
The fully automatic virtual measurement technique is to generate a two-stage virtual measurement value to take both immediacy and accuracy into account. The first stage estimation step is to estimate and obtain the first stage virtual measurement value of a specific finished product immediately after the process parameters of the finished product are obtained, so as to meet the requirement of immediacy. The estimation step of the second stage is to recalculate the virtual measurement value of the second stage of the sampled and measured finished product after the actual measurement value of the sampled and measured finished product is obtained by the measuring equipment, so as to be used for retraining and training, thereby meeting the requirement of accuracy. The full-automatic virtual measurement technique can also generate a confidence index (reliability index) and a global similarity index (global similarity index) of the first-stage virtual measurement value and the second-stage virtual measurement value to estimate the reliability of the virtual measurement value.
Although the existing virtual measurement technique can combine immediacy and accuracy, the following problems still exist. Since the conventional virtual measurement technology usually utilizes a pure numerical analysis method such as neural network and multiple regression calculation when establishing a virtual estimation model of a processed product, which cannot actually reflect the physical mechanism state of a processing machine, the accuracy of virtual measurement still cannot be effectively improved, if a more accurate virtual measurement result needs to be obtained, a large number of additional sensors need to be installed on the machine or production equipment to obtain process or processing parameter data by using the additional sensors to establish and measure the virtual estimation model, however, the sensors all need to be wired to a local server, so that not only wiring construction is difficult, but also the transmission path is long, and the hardware architecture cost is further increased. Moreover, since the conventional virtual measurement technology can only predict the quality of the processed product and cannot distinguish or know the reason of the quality of the processed product, when the processed product is found to be bad, the machine or the production equipment cannot adjust and improve the process or the processing parameters in real time. In addition, in a production system including a machine tool, since variation factors such as external interference and self-aging of a mechanism affect the quality of a processed product, the conventional virtual measurement technology cannot separate the variation factors such as external interference and self-aging of the mechanism, so that the estimation accuracy of the product quality is reduced, and the degradation degree and the replacement or maintenance time of the mechanism cannot be known. Furthermore, the conventional virtual measurement technique uses a centralized architecture operation, in other words, all measurement and analysis are implemented in the local server, so that the sensors additionally installed on the machine or the production equipment must directly transmit the acquired process or process parameter data to the local server for data processing and calculation through the local server.
Therefore, there is a need for an improved production system, driver and method thereof to solve the above problems of the prior art.
Disclosure of Invention
The present disclosure is directed to a production system with quality measurement and mechanism diagnosis functions, and a driver and a method thereof, so as to solve the disadvantages of the conventional production system, such as high hardware cost, increased computational burden and reduced efficiency, inability to separate the influence of external interference and mechanism aging on product quality, low product quality estimation accuracy, and inability to know the mechanism degradation degree and replacement or maintenance time.
Another objective of the present disclosure is to provide a production system, a driver thereof and a method thereof, so as to achieve the functions of product quality measurement and monitoring, mechanism health diagnosis and degradation prediction, and intelligent control.
Another objective of the present disclosure is to provide a production system and a driver thereof, which have the functions of modeling, controlling, measuring and diagnosing, can implement hierarchical data processing to reduce data transmission and operation burden, simplify wiring, improve efficiency, and can perform product quality prediction, provide external interference measurement, improve prediction accuracy, monitor productivity of production equipment, adjust processing strategies according to mechanism variations to optimize productivity, provide mechanism health diagnosis and aging prediction of production equipment, and reduce hardware and measurement costs.
To achieve the above object, the present disclosure provides a driver for a production apparatus, which is controlled by a controller of the production apparatus to drive a motor of the production apparatus to operate, so that the production apparatus performs a system identification mode, a processing mode to produce at least one processed product or an idle operation mode. The driver comprises a real system driving module and a virtual system driving module. The real system driving module is constructed under a processing mode and generates real operation parameter information of a mechanism according to a processing strategy of the controller and an external force interference. The virtual system driving module comprises a quality measurement and mechanism diagnosis parameter processing module, wherein the quality measurement and mechanism diagnosis parameter processing module establishes at least one virtual mechanism model in a system identification mode, and generates mechanism simulation operation parameter information according to a processing strategy of a controller, mechanism real operation parameter information and at least one virtual mechanism model in a processing mode or a no-load operation mode, wherein the quality measurement, the mechanism diagnosis and/or the adjustment of the processing strategy are realized by providing the mechanism real operation parameter information and the mechanism simulation operation parameter information to the controller.
To achieve the above objective, the present disclosure further provides a production system, which includes a production device, a local server, and a quality measurement and mechanism diagnosis module. The production equipment executes a system identification mode, a processing mode to produce at least one processed product or an idle running mode. The production equipment comprises at least one motor, at least one sensor, at least one controller and at least one driver. The sensor is configured to sense at least one operating parameter of the motor and a mechanism corresponding to the motor. The controller is configured to output a processing strategy. The driver is connected with the motor and the controller, receives at least one operation parameter sensed by the sensor, receives the processing strategy and drives the motor to operate according to the processing strategy. The driver comprises a real system driving module and a virtual system driving module. The real system driving module generates real operation parameter information of the mechanism in the processing mode according to the processing strategy of the controller and an external force interference. The virtual system driving module comprises a quality measurement and mechanism diagnosis parameter processing module, wherein the quality measurement and mechanism diagnosis parameter processing module establishes at least one virtual mechanism model in a system identification mode, and generates mechanism simulation operation parameter information according to a processing strategy of a controller, mechanism real operation parameter information and at least one virtual mechanism model in a processing mode or a no-load operation mode. The local server is connected with the controller. The quality measurement and mechanism diagnosis module is configured in at least one of the controller and the local server, and receives and realizes the quality measurement, the mechanism diagnosis and/or the adjustment of the processing strategy according to the real mechanism operating parameter information and the mechanism simulation operating parameter information.
To achieve the above objective, the present disclosure further provides a method for operating a production system, wherein the production system includes a production apparatus, a local server, and a quality measurement and mechanism diagnosis module, the production apparatus includes at least one motor, at least one sensor, at least one controller, and at least one driver, the driver includes a real system driver module and a virtual system driver module, and the quality measurement and mechanism diagnosis module is configured in at least one of the controller and the local server. The operation method of the production system comprises the following steps: (S1) executing the manufacturing apparatus in a system authentication mode, and enabling the driver to establish at least one virtual mechanism model of the virtual system driver module; (S2) causing the controller to generate a processing strategy and provide the processing strategy to the driver to drive the motor to operate; (S3) executing the manufacturing apparatus in a processing mode, and enabling the real system driving module of the driver to generate a real mechanism operating parameter information due to the processing strategy of the controller and an external force disturbance, and enabling the virtual system driving module of the driver to generate a simulated mechanism operating parameter information, wherein the real mechanism operating parameter information includes a motor driving command and a motor operating parameter information, and the simulated mechanism operating parameter information includes an estimated external force disturbance; and (S4) outputting at least one processed product from the manufacturing equipment, wherein the quality measurement and mechanism diagnosis module performs quality measurement of the processed product according to the motor operation parameter information and the estimated external force interference.
Drawings
Fig. 1 is a schematic diagram of an architecture of a production system according to a preferred embodiment of the present disclosure.
FIG. 2 is a block diagram of an exemplary manufacturing facility of the manufacturing system shown in FIG. 1.
Fig. 3 is a schematic diagram of the driver shown in fig. 1.
Fig. 4 is a detailed architecture diagram of the actuator shown in fig. 3.
Fig. 5 is a first exemplary architecture diagram of a production system implementing quality measurement and mechanism diagnostics according to the present disclosure.
Fig. 6 is a second exemplary architecture diagram of a production system implementing quality measurement and mechanism diagnostics according to the present disclosure.
FIG. 7 is a flow chart of steps of a method of operation performed by the disclosed production system.
Fig. 8 is a flowchart of sub-steps included in step S12 shown in fig. 7.
FIG. 9 is a flow chart of steps performed by another embodiment of a method of operation performed by the disclosed production system.
FIG. 10 is a diagram illustrating an exemplary configuration of a tool station to which the disclosed manufacturing system is applied.
Wherein the reference numerals are as follows:
1: production system
2: production equipment
3: local server
4: cloud server
20. 201,202, 20 n: motor with a stator having a stator core
20 a: mechanism corresponding to motor
21. 211,212, 21 n: driver
21 a: real system driving module
21 b: virtual system driver module
21 c: quality measurement and mechanism diagnosis parameter processing module
22: sensor device
23. 231, 23 n: controller
R1: real operating parameter information of mechanism
R2: mechanism simulation operation parameter information
K1: virtual mechanism drive unit
K2: real mechanism drive unit
K3: external force estimation unit
P: controlled body
M0: first virtual mechanism model
M1: second virtual mechanism model
M2: third virtual mechanism model
p: control instruction
C: processing strategy
TL, TLx, TLy: external force interference
TLest, TLestx, TLesty: predicting external force interference
u 0: first drive instruction
up: second drive instruction
u1, u1x, u1 y: motor drive command
y1, y1x, y1 y: motor operating parameter information
y 0: first simulated operating parameter information
y 2: second simulated operating parameter information
y3, y3x, y3 y: third simulation run parameter information
231: interpretation and trajectory interpolation module
232. 31: quality measurement and mechanism diagnostic module
233. 32: finished product quality measuring unit
234. 33: mechanism health diagnosis and deterioration estimation unit
235. 34: non-defective product determination and confidence index unit
236. 35: machining parameter adjustment unit
L1: first-stage data processing device
L2: second-level data processing device
L3: third-level data processing device
L4: fourth-level data processing apparatus
L5: fifth-stage data processing device
21 x: x driver
21 y: y driver
S1-S7, S11-S13, S21-S22, S41-S42, S61-S63, S71-S73: procedure step
S121 to S123: procedure step
Detailed Description
Some exemplary embodiments that incorporate the features and advantages of the present disclosure will be described in detail in the specification which follows. It is to be understood that the disclosure is capable of various modifications in various embodiments without departing from the scope of the disclosure, and that the description and drawings are to be regarded as illustrative in nature, and not as restrictive.
Referring to fig. 1, fig. 2 and fig. 3, wherein fig. 1 is a schematic diagram of a production system according to a preferred embodiment of the present disclosure, fig. 2 is a schematic diagram of an exemplary production facility of the production system shown in fig. 1, and fig. 3 is a schematic diagram of a driver shown in fig. 1. As shown, the production system 1 of the present disclosure includes at least one production device 2 and a local server (local server) 3. The production apparatus 2 may be, but is not limited to, a tool machine having at least one axis, such as a milling machine or the like, and the production apparatus 2 may selectively perform a system identification mode, a machining mode or a dry run mode. When the production apparatus 2 is equipped with a processing tool (e.g., a cutting blade) and started, the production apparatus 2 may first execute the system authentication mode. When the production device 2 executes the processing mode, the production device 2 performs the processing operation and produces at least one processed product. When the production apparatus 2 executes the idling mode (when the processing tool is temporarily removed from the production apparatus 2), the production apparatus 2 executes the same command as the processing mode but cannot produce a processed product.
The production apparatus 2 comprises at least one motor 20, at least one driver 21, at least one sensor 22 and at least one controller 23. The motor 20 and the corresponding mechanism 20a of the motor are configured to drive a processing tool to perform a processing operation on a workpiece. The driver 21 is electrically connected to a corresponding motor 20 to drive the motor 20. The sensor 22 is configured to sense at least one operating parameter of the motor 20 and the mechanism 20a corresponding to the motor, and provide the operating parameter to the driver 21. The controller 23 is electrically connected to a corresponding driver 21 to control the driver 21 to drive the corresponding motor 20.
In the present embodiment, the motor 20 is a main core mechanism in the machining operation of the production facility 2, so that the machining state and quality of the machined product produced by the production facility 2 are actually related to the corresponding operation state of the motor 20, and the motor 20 can be operated when the production facility 2 executes the system discrimination mode, the machining mode, or the idling mode. The sensor 22 is configured to sense and acquire at least one motor operation parameter, such as a rotation speed, a displacement, an electric energy and/or a vibration amount, when the motor 20 or the mechanism 20a corresponding to the motor 20 is running, wherein the sensor 22 is built in the corresponding motor 20 and/or the mechanism 20a corresponding to the motor (as shown in fig. 1 and 2) or the driver 21, but not limited thereto, and may also be built in other mechanisms of the production equipment 2. Alternatively, the sensor 22 may be disposed in an external manner in other mechanical components of the production equipment 2. The controller 23 may generate a machining strategy C (or machining trajectory strategy) according to the control command issued by the user to control the driver 21. In some embodiments, the controller 23 may also perform data storage, evaluation, and diagnostic analysis. The driver 21 drives the motor 20 to perform the corresponding processing operation according to the processing strategy C generated by the controller 23, and the driver 21 provides the real mechanism operating parameter information R1 and the simulated mechanism operating parameter information R2 of the production equipment 2 to the controller 23 after performing data processing according to the operating parameter information of the motor 20 and the mechanism 20a corresponding to the motor and the processing strategy C provided by the sensor 22, so that the controller 23 can store the operating parameter information of the production equipment 2, and realize product quality estimation, mechanism health diagnosis and degradation prediction and adjust the processing strategy C of the controller 23 of the production equipment 2 according to the operating parameter information of the production equipment 2. The local server 3 is connected to the controller 23, and in some embodiments, the local server 3 may obtain and store the operation parameter information of the production equipment 2 through the controller 23 of the production equipment 2, and implement product quality estimation, mechanism health diagnosis and degradation prediction, and adjust the processing strategy C of the controller 23 of the production equipment 2 according to the operation parameter information of the production equipment 2.
In some embodiments, as shown in fig. 1, the manufacturing apparatus 2 includes a plurality of motors 201,202, …,20n, a plurality of drivers 211,212, …,21n, a plurality of sensors 22, and a plurality of controllers 231, …,23n, where n is a positive integer greater than or equal to 2. Each driver 21 is electrically connected to a corresponding motor 20 to drive the corresponding motor 20 to operate. The sensor 22 is configured to sense at least one operation parameter of the corresponding motor 20 and provide the operation parameter to the corresponding driver 21, wherein the sensor 22 is preferably disposed at the corresponding motor 20 and/or the mechanism 20a corresponding to the motor. Each controller 23 is electrically connected to a corresponding driver 21 to control the corresponding driver 21 to drive the corresponding motor 20 for processing operation. The functions and actions of the motor 20, the driver 21, the sensor 22 and the controller 23 are the same as those of the previous embodiment, and are not described herein again.
Referring to fig. 1 to 3, in the present embodiment, each driver 21 is configured to have a Model (Model) function, a Control (Control) function, a Measure (Measure) function, and a Diagnosis (Diagnosis) data providing function (MCMD). Each driver 21 includes a real system driver module 21a and a virtual system driver module 21b, wherein the virtual system driver module 21b includes a quality measurement and mechanism diagnosis parameter processing module 21 c. The real system driver module 21a of the driver 21 executes the system identification mode, the processing mode or the idle mode in response to the control of the controller 23, and generates a real mechanism operating parameter information R1 in the processing mode according to a processing strategy C of the controller 23 and an external force disturbance TL. The virtual system driving module 21b of the driver 21 includes a quality measurement and mechanism diagnosis parameter processing unit 21C, the virtual system driving module 21b is configured to establish at least one virtual mechanism model in a system identification mode, and the quality measurement and mechanism diagnosis parameter processing module 21C generates a mechanism simulation operation parameter information R2 in a processing mode and/or a dry running mode according to the processing strategy C of the controller 23, the mechanism real operation parameter information R1 and the at least one virtual mechanism model, so that the driver 21 can provide the mechanism real operation parameter information R1 and the mechanism simulation operation parameter information R2 to the controller 23 or the local server 3, thereby enabling the controller 23 or the local server 3 to change or vary parameters according to the self-variation or variation between parameters of the mechanism real operation parameter information R1 and the mechanism simulation operation parameter information R2, the product quality estimation, the facility health diagnosis and the deterioration prediction are realized, and the processing strategy C of the controller 23 of the production facility 2 is adjusted to optimize the processing quality.
Fig. 4 is a detailed architecture diagram of the actuator shown in fig. 3. As shown in fig. 1 to 4, in the present embodiment, the real system driving module 21a of the driver 21 includes a real mechanism driving unit K2 and a controlled body P. The quality measurement and mechanism diagnosis parameter processing module 21c of the virtual system driving module 21b of the driver 21 includes a virtual mechanism driving unit K1, an external force estimation unit K3, and at least one virtual mechanism model. The controlled object P is established according to the motor 20 or the mechanism 20a corresponding to the motor driven by the driver 21, so that the controlled object P can reflect the real mechanism operating parameter R1 of the production equipment 2, and the real mechanism operating parameter R1 actually varies with long-time operation (mechanism aging of the production equipment 2) and/or external interference, and further, the motor 20 and the mechanism 20a corresponding to the motor actually have external interference when operating in the machining mode, so that the controlled object P will receive the actual external interference TL when the motor 20 and the mechanism 20a corresponding to the motor operate in the machining mode.
In the present embodiment, the quality measurement and mechanism diagnosis parameter processing module 21c of the actuator 21 includes a plurality of virtual mechanism models, preferably three virtual mechanism models, such as a first virtual mechanism model M0, a second virtual mechanism model M1 and a third virtual mechanism model M2. The first virtual mechanism model M0 is established in the system identification mode of the production facility 2 according to the operation parameters of the corresponding motor 20 sensed by the sensor 22, and the first virtual mechanism model M0 is a model of the controlled object P (i.e., the motor 20 and the mechanism 20a corresponding to the motor) simplified without external interference, so that the first virtual mechanism model M0 is a model reflecting the main mechanism components of the controlled object P and is established by using the operation parameters of the corresponding motor 20 sensed by the sensor 22, so that the first virtual mechanism model M0 can reflect the physical quantity parameters, such as power parameters and electric energy parameters, of the controlled object P. The second virtual mechanism model M1 and the third virtual mechanism model M2 are synchronously built according to the first virtual mechanism model M0, so that the first virtual mechanism model M0, the second virtual mechanism model M1 and the third virtual mechanism model M2 are substantially the same model and have the same physical quantity parameters, wherein the second virtual mechanism model M1 may further receive an estimated external force disturbance TLest.
In the above embodiment, when the production equipment 2 starts to operate, the production equipment 2 first executes the system identification mode, so that the virtual system driving module 21b of the driver 21 constructs and completes the first virtual mechanism model M0, the second virtual mechanism model M1 and the third virtual mechanism model M2 according to the operating parameters of the corresponding motor 20 sensed by the sensor 22 in the system identification mode. It should be noted that the aforementioned system authentication mode is executed only when the production apparatus 2 starts operating.
In the embodiment, the virtual mechanism driving unit K1 receives the processing strategy C generated by the controller 23, and outputs the first driving command u0 to control the first virtual mechanism model M0 in the system identification mode, wherein the first driving command u0 includes but is not limited to at least a portion of a position command, a speed specification, and a current command, so that the first virtual mechanism model M0 performs a simulation operation according to the processing strategy C, and further generates the first simulated operation parameter information y0, wherein the first simulated operation parameter information y0 may reflect the operation parameter information of the controlled object P in the system identification mode without external interference, such as reflecting the position and the angular velocity provided by the encoder of the motor 20, and may also reflect other operation parameter information of the mechanism 20a corresponding to the motor.
The real machine drive unit K2 is to receive the machining strategy C generated by the controller 23 and output a second drive command up, wherein the second drive command up includes, but is not limited to, at least a part of a position command, a velocity specification, a current command. The second driving command up of the real mechanism driving unit K2 is further combined with the first driving command u0 to form a motor driving command u1, so that the controlled object p is controlled by the motor driving command u1 to operate according to the processing strategy C of the controller 23, thereby generating motor operation parameter information y 1. In the present embodiment, the motor driving command u1 and the motor operation parameter information y1 constitute the real mechanism operation parameter information R1 of the real system driving module 21 a. Meanwhile, the second virtual machine model M1 and the third virtual machine model M2 are also controlled by the motor drive command u1 to perform simulation operation, so that the second virtual machine model M1 generates second simulation operation parameter information y2, and the third virtual machine model M2 generates third simulation operation parameter information y3, wherein the second simulation operation parameter information y2 is generated in the machining mode, and the third simulation operation parameter information y3 is generated in the idle mode.
The external force estimation unit K3 is configured to estimate the external force interference condition received by the controlled object p in the processing mode according to the motor operation parameter information y1 and the second simulated operation parameter information y2, so as to generate the estimated external force interference tle correspondingly, and provide the estimated external force interference tle to the second virtual mechanism model M1. In this embodiment, the second virtual mechanism model M1 may generate the adjusted second simulated operation parameter information y2 according to the motor driving command u1 and the predicted external force disturbance tle and feed back the adjusted second simulated operation parameter information y2 to the external force estimation unit K3. In the present embodiment, the predicted external force disturbance tle and the third simulated operation parameter information y3 constitute the mechanism simulated operation parameter information R2 of the virtual system driving module 21 b.
In the above embodiment, since the first virtual mechanism model M0 is a simplified model of the controlled object P and has a physical mechanism meaning, the first simulated operation parameter information y0 can be used to simulate the operation parameter information of the controlled object P in the system identification mode without external force interference, such as the speed and position of the mechanism 20a corresponding to the motor 20 and the motor. The motor operation parameter information y1 reflects the operation parameter information of the controlled object P in actual operation, i.e., the operation parameter information of the motor 20 and the mechanism 20a corresponding to the motor, so that the operation parameter information reflected by the motor operation parameter information y1 is substantially equal to the operation parameter information of the motor 20 and the mechanism 20a corresponding to the motor sensed by the sensor 22. The second simulated operation parameter information y2 simulates the operation information of the controlled object P in the processing mode and receives the predicted external force interference tle, and since the second virtual mechanism model M1 and the controlled object P are controlled by the motor driving command u1, if there is a difference between the motor operation parameter information y1 and the second simulated operation parameter information y2, it indicates that there is a difference between the actual external force interference TL and the predicted external force interference tle, so that the external force estimation unit K3 can adjust the predicted external force interference tle by using the second simulated operation parameter information y2 of the second virtual mechanism model M1, so that the predicted external force interference tle accurately reflects the actual external force interference TL received by the motor 20 and the mechanism 20a corresponding to the motor in the processing mode. Therefore, the controller 23 or the local server 3 can utilize the estimated external force interference tle provided by the virtual system driving module 21b of the driver 21 and the motor operation parameter information y1 provided by the real system driving module 21a of the driver 21 to measure and estimate the processing status or quality of the processed product generated by the production equipment 2, or even adjust the processing strategy C correspondingly according to the external force interference, so as to optimize the processing quality. The third simulated operation parameter information y3 simulates the operation parameter information of the controlled object P in the idle operation mode, and since the third virtual mechanism model M2 and the controlled object P are simultaneously controlled by the motor driving command u1 and the controlled object P does not receive the actual external force interference TL in the idle operation mode, if there is a difference between the motor operation parameter information y1 and the third simulated operation parameter information y3, it indicates that there is a difference between the controlled object P and the third virtual mechanism model M2 in the physical quantity parameter, and the difference in the physical quantity parameter reflects the operation parameter variation of the controlled object P due to the mechanism aging, so that the controller 23 or the local server 3 can use the third simulated operation parameter information y3 provided by the virtual system driving module 21b of the driver 21 to implement the mechanism health diagnosis or the degradation (aging) estimation of the motor 20 of the production facility 2 or the mechanism 20a corresponding to the motor, or even adjusting the processing strategy C according to the mechanism variation to optimize the processing quality. In addition, the third simulated operation parameter information y3 can also be used to periodically update the first virtual machine model M0, the second virtual machine model M1, and the third virtual machine model M2, so as to ensure the correctness of the diagnosis, and further to make the control of the motor 20 more accurate, thereby optimizing the processing quality of the production equipment 2.
As can be seen from the above, the virtual system driver module 21b of the actuator 21 establishes virtual mechanism models that reflect the physical quantity parameters of the controlled object P, i.e., the first virtual mechanism model M0, the second virtual mechanism model M1, and the third virtual mechanism model M2, so that the actuator 21 has a function of establishing the models. In addition, due to the establishment of the second virtual mechanism model M1, the influence of the external disturbance factor of the production equipment 2 in the processing mode on the processing condition and quality can be estimated by using the second simulated operation parameter information y2 of the second virtual mechanism model M1 of the actuator 21, so that the actuator 21 has a measurement function. Furthermore, the virtual mechanism models M0, M1, M2, the virtual mechanism driving unit K1, the real mechanism driving unit K2 and the external force estimation unit K3 of the actuator 21 cooperate with each other to provide the real mechanism operating parameter information R1(u1, y1) and the simulated mechanism operating parameter information R2(TLest, y3) to dynamically adjust the processing strategy C of the controller 23, thereby precisely controlling the operation of the motor 20, so that the actuator 21 has a control function. Furthermore, the third simulated operation parameter information y3 of the third virtual mechanism model M2 of the drive 21 can be provided to the controller 23 or the local server 3, so that the controller 23 or the local server 3 can perform mechanism health diagnosis and degradation prediction for the production equipment 2, and thus the drive 21 has a function of providing diagnostic data.
In some embodiments, the first simulated operation parameter information y0 is fed back to the virtual mechanism driving unit K1, the real mechanism driving unit K2 and the external force estimation unit K3. The motor operation parameter information y1 is fed back to the real mechanism driving unit K2 and the external force estimation unit K3. The second simulation operation parameter information y2 is fed back to the external force estimation unit K3. Through the feedback control, the simulation operation parameter information of the simulation physical mechanism of the driver 21 can be more accurate, thereby improving the accuracy of quality measurement and mechanism diagnosis of the production system 1.
In other embodiments, when the production equipment 2 is a multi-axis machining device, the production equipment 2 may correspondingly include a plurality of motors 20 and a plurality of drivers 21, and each driver 21 may cooperate with a corresponding motor 20 to control the operation of one of the multiple axes of the production equipment 2.
In some embodiments, as shown in fig. 1, the production system 1 further includes a cloud server 4, the cloud server 4 may be connected to the local server 3 through, for example, a communication network, and the cloud server 4 may receive, via the communication network, the mechanism real operation parameter information R1 and the mechanism simulation operation parameter information R2 of the production equipment 2 acquired by the local server 3 via the driver 21, and record, manage and analyze the information.
In some embodiments, the driver 21 is pre-configured with an algorithm, and the control structure of the driver 21 can establish the virtual mechanism models M0, M1, M2 according to the operation parameter information of the motor 20 or the mechanism 20a corresponding to the motor sensed by the sensor 22 and the algorithm, wherein the algorithm uses the following equations:
Jpωrm+Bωrm+TL＝Te
(Rs+jωeLs+Lsp)is+jωeφF＝vs
where J and B are inertia and viscosity coefficient of the motor 20, respectively, p ═ d/dt is a differential operator, and ω isrmAnd omegaeThe mechanical and electrical rotational speeds, T, of the motor 20, respectivelyLAnd TeThe external load force applied to the motor 20 and its own electromagnetic torque, LsAnd RsInductance and resistance, i, respectively, of the stator of the motor 20sAnd vsRespectively, the current and voltage, phi, of the stator of the motor 20FIs the flux of the motor 20 and j is an imaginary number. As can be seen from the above, the virtual mechanism models M0, M1, and M2 actually include physical quantities reflecting the power parameters and the electric energy parameters of the corresponding motors 20 and the mechanisms 20a corresponding to the motors by the above algorithm. Of course, the virtual machine models M0, M1, M2 may also include other physical parameters in addition to power parameters and electrical energy parameters. It should be emphasized that the algorithms of the present disclosure are not limited to the foregoing equations, and other suitable algorithms and equations may be incorporated by reference.
Of course, the number of the virtual mechanism models of the actuator 21 is not limited to three, and in other embodiments, if other factors or states besides the external force interference estimation and the mechanism health diagnosis need to be estimated and determined, the control structure of the actuator 21 may further establish a fourth virtual mechanism model or more virtual mechanism models to achieve the desired estimation and determination functions.
In some embodiments, in addition to the built-in sensor 22 of the production equipment 2, an additional sensor, such as an accelerometer, may be added, and the operation parameters sensed by the additional sensor are applied to the establishment of the control structure of the driver 21, so that the simulated operation parameter information provided by the first virtual mechanism model M0, the second virtual mechanism model M1 and the third virtual mechanism model M2 may be more accurate.
Fig. 5 is a first exemplary architecture diagram of a production system implementing quality measurement and mechanism diagnostics according to the present disclosure. As shown in fig. 1 to 5, in some embodiments, the controller 23 of the production equipment 2 includes an interpretation and trajectory interpolation module 231 and a quality measurement and mechanism diagnosis module 232, wherein the quality measurement and mechanism diagnosis module 232 includes a finished product quality measurement unit 233 and a mechanism health diagnosis and degradation estimation unit 234. The interpretation and trajectory interpolation module 231 of the controller 23 receives the control command p from the user, and interprets and interpolates the control command p to generate a processing strategy C and provide the strategy C to the driver 21. The finished product quality measuring unit 233 of the controller 23 receives the motor driving command u1 and the motor operating parameter information y1 of the mechanism real operating parameter information R1 provided from the driver 21, and receives the estimated external force disturbance TLest of the mechanism virtual operating parameter information R2, and stores them. The finished product quality measuring unit 233 may measure and estimate the quality of the finished product by using a characteristic extraction method, a model estimation method, and the like according to the historical data of the motor operating parameter information y1, and/or may measure and estimate the quality of the finished product and perform an unexpected detection according to the variation of the estimated external force disturbance TLest. The mechanism health diagnosis and deterioration estimation unit 234 of the controller 23 receives and stores the third simulated operation parameter data y3 of the mechanism simulated operation parameter information R2 provided by the driver 21. The health diagnosis and degradation estimation unit 234 performs the health diagnosis and degradation estimation according to the variation of the third simulated operating parameter data y 3.
In some embodiments, the quality measurement and mechanism diagnosis module 232 of the controller 23 may further include a good quality determination and confidence index unit 235 for receiving the output information of the finished product quality measurement unit 233 and/or the output information of the mechanism health diagnosis and degradation estimation unit 234, and performing a good quality determination and providing a confidence index according to the above information, thereby providing the measurement and determination results for the user to review. In some embodiments, the quality measurement and mechanism diagnosis module 232 of the controller 23 further includes a processing parameter adjustment unit 236, which receives the output information of the finished product quality measurement unit 233 and/or the output information of the mechanism health diagnosis and degradation estimation unit 234, selectively adjusts the processing parameters according to the above information, and transmits the adjusted processing parameters to the interpretation and position interpolation module 231 for interpretation and position interpolation to generate the adjusted processing strategy C, and outputs the adjusted processing strategy C to the driver 21. Thereby, the driver 21 can dynamically adjust the output operation parameters to drive the motor 20 for processing operation, thereby optimizing the processing quality.
Fig. 6 is a second exemplary architecture diagram of a production system implementing quality measurement and mechanism diagnostics according to the present disclosure. As shown in fig. 1-4 and 6, in some embodiments, the controller 23 of the production system 1 includes an interpretation and trajectory interpolation module 231. The interpretation and trajectory interpolation module 231 of the controller 23 receives the control command p from the user, and interprets and interpolates the control command p to generate a processing strategy C and provide the strategy C to the driver 21. The local server 3 includes a quality measurement and mechanism diagnosis module 31, wherein the quality measurement and mechanism diagnosis module 31 includes a finished product quality measurement unit 32 and a mechanism health diagnosis and degradation estimation unit 33. The finished product quality measuring unit 32 of the local server 3 receives the motor driving command u1 and the motor operating parameter information y1 from the mechanism real operating parameter information R1 of the driver 21 and the estimated external force disturbance TLest of the mechanism virtual operating parameter information R2 via the controller 23, and stores them. The finished product quality measuring unit 32 of the local server 3 may measure the quality of the finished product by using the characteristic extraction, model estimation, and the like according to the historical data of the motor operating parameter information y1, and/or may measure and estimate the quality of the finished product and perform the accident detection according to the variation of the estimated external force disturbance TLest. The facility health diagnosis and deterioration estimation unit 33 of the local server 3 receives the third simulated operation parameter data y3 derived from the facility simulated operation parameter information R2 of the drive 21 via the controller 23 and stores it. The health diagnosis and degradation estimation unit 33 performs the health diagnosis and degradation estimation according to the variation of the third simulated operating parameter data y 3.
In some embodiments, the quality measurement and mechanism diagnosis module 31 of the local server 3 may further include a good product determination and confidence index unit 34, which receives the output information of the processed product quality measurement unit 32 and/or the output information of the mechanism health diagnosis and degradation estimation unit 33, and determines the quality of the processed product according to the received information and provides a confidence index, so as to provide the measurement and determination results for the user to review. In some embodiments, the quality measurement and mechanism diagnosis module 31 of the local server 3 further includes a processing parameter adjusting unit 35, which receives the output information of the finished product quality measurement unit 32 and/or the output information of the mechanism health diagnosis and degradation estimation unit 33, selectively adjusts the processing parameters according to the above information, and transmits the adjusted processing parameters to the interpretation and position interpolation module 231 of the controller 23 for interpretation and position interpolation, so as to generate the adjusted processing strategy C, and output the adjusted processing strategy C to the driver 21. Thereby, the driver 21 can dynamically adjust the output operation parameters to drive the motor 20 for processing operation, thereby optimizing the processing quality.
It should be emphasized that the quality measuring unit of the quality measuring and mechanism diagnosing module, the mechanism health diagnosing and degradation estimating unit, the non-defective product determining and confidence index unit, the processing parameter adjusting unit, etc. may be built in the controller 23 as shown in fig. 5 to cooperate with the driver 21 to realize the quality measuring and mechanism diagnosing functions of the production system 1. Of course, the quality measurement unit of the finished product, the health diagnosis and degradation estimation unit of the mechanism, the non-defective product determination and confidence index unit, and the processing parameter adjustment unit of the quality measurement and mechanism diagnosis module may also be built in the local server 3 as shown in fig. 6, so as to cooperate with the driver 21 and the controller 23 to realize the quality measurement and mechanism diagnosis functions of the production system 1. Alternatively, in some embodiments, some of the units of the quality measurement unit of the quality measurement and mechanism diagnosis module, the mechanism health diagnosis and degradation estimation unit, the good product determination and confidence index unit, and the processing parameter adjustment unit may be built in the controller 23, and the rest of the units may be built in the local server 3, so as to cooperate with the driver 21 to implement the quality measurement and mechanism diagnosis functions of the production system 1.
In accordance with the concept of the present disclosure, the production system 1 of the present disclosure may perform an operation method, which is briefly described as follows. FIG. 7 is a flow chart of steps of a method of operation performed by the disclosed production system. As shown in fig. 1 to 7, step S1 is executed to enable the production facility 2 to perform the system authentication mode once at the time of startup. In this embodiment, the execution of the system authentication mode by the production apparatus 2 may include the following sub-steps. First, step S11 is executed to drive the production system 1 to start. Then, step S12 is executed to drive the production facility 2 to execute the system identification mode, so that the driver 21 establishes the first virtual mechanism model M0, the second virtual mechanism model M1 and the third virtual mechanism model M2 of the virtual system driving module 21b, and obtains the motor driving command u1, the motor operating parameter information y1 and the third simulation operating parameter information y3 of the driver 21. In this step, the algorithm described above may be used to establish the first virtual mechanism model M0, and the second virtual mechanism model M1 and the third virtual mechanism model M2 are synchronously established according to the first virtual mechanism model M0, but not limited thereto. In this step, the real mechanism driving unit K2 of the real system driving module 21a generates the motor driving command u1, and the controlled entity P of the real system driving module 21a generates the motor operation parameter information y1 according to the motor driving command u 1. The second virtual mechanism model M1 generates second simulated operation parameter information y2 according to the motor driving command u1 and an estimated external force disturbance TLest, and the external force estimation unit K3 of the virtual system driving module 21b generates the estimated external force disturbance TLest in response to the motor operation parameter information y1 and the second simulated operation parameter information y2, and provides the estimated external force disturbance TLest to the second simulated mechanism model M1. The third virtual machine model M2 generates the third simulated operation parameter information y3 in response to the motor driving command u 1.
Then, step S13 is executed, and the drive 21 verifies whether the first virtual machine model M0 is completely built using the motor operating parameter information y1 and the third simulated operating parameter information y 3. In this step, the driver 21 verifies whether the first virtual machine model M0 is completely built according to whether the difference between the motor operating parameter information y1 and the third simulated operating parameter information y3 is smaller than a predetermined range. When the difference between the motor simulated operation parameter information y1 and the third simulated operation parameter information y3 is smaller than a preset range, it is verified that the first virtual mechanism model M0 conforms to the simplified model of the controlled object P and the building is completed, and on the contrary, when the difference between the motor simulated operation parameter information y1 and the third simulated operation parameter information y3 is larger than or equal to the preset range, it is verified that the first virtual mechanism model M0 does not conform to the simplified model of the controlled object P and the building fails. When the verification result of step S13 is no, step S12 is re-executed. On the contrary, when the verification result of step S13 is yes, it represents that the control architecture of the driver 21 is already established, that is, the first virtual mechanism model M0, the second virtual mechanism model M1, the third virtual mechanism model M2, the controlled object P, the virtual mechanism driving unit K1, the real mechanism driving unit K2 and the external force estimation unit K3 are all established.
After the system identification mode is executed, step S2 is executed to enable the controller 23 to generate the machining strategy C and provide the machining strategy C to the driver 21 to drive the motor 20 to operate. In this step, the following substeps may be included. First, step S21 is executed to start the operation of the production apparatus 2. Thereafter, step S22 is executed, the controller 23 generates a processing strategy C according to the control command p issued by the user, and provides the processing strategy C to the driver 21 to drive the motor 20 to operate. In some embodiments, as in step S22, when there is a mechanism variation in the production equipment 2, for example, caused by external interference or mechanism aging, the processing strategy C generated by the controller 23 may be adjusted accordingly.
After the step S2, step S3 is executed to enable the production equipment 2 to be operated in the machining mode, and enable the real system driving module 21a of the driver 21 to generate a mechanism real operation parameter information R1 in response to the machining strategy C of the controller 23 and an external force disturbance TL, and enable the virtual system driving module 21b of the driver 21 to generate a mechanism simulated operation parameter information R2, wherein the mechanism real operation parameter information R1 includes the motor driving command u1 and the motor operation parameter information y1, and the mechanism simulated operation parameter information R2 includes the estimated external force disturbance TLest.
After step S3, step S4 is executed to enable the production system 1 to perform the machining estimation operation. In this step, the production equipment 2 outputs the processed product, and the quality measurement and mechanism diagnosis modules 232 and 31 perform the quality measurement operation of the processed product according to the motor operation parameter information y1 and the estimated external force interference tle, thereby achieving the purpose of estimating the processing quality of the processed product in real time and achieving full inspection. In this step, when the quality measurement result of the processed product meets the standard, step S3 is performed. The step S4 may include the following sub-steps. First, step S41 is executed to cause the production facility 2 to output the finished product. Then, step S42 is executed, the quality measurement and mechanism diagnosis module 232,31 performs the quality measurement operation of the processed product according to the motor operation parameter information y1 and the predicted external force interference tle, so as to predict whether the processed product meets the standard.
After step S3, step S6 may be executed to enable the production system 1 to perform a machining sampling operation. In step S6, the machining spot check operation includes the following substeps. First, step S61 is executed, and when the number of the finished products output by the production equipment 2 reaches the first preset value X, the finished products are taken out for sampling inspection. In this step, the finished product is taken out and then physically measured by a measuring device, so that the quality of the finished product can be accurately judged. After the step S61, the step S62 is executed, and the quality measurement and mechanism diagnosis module 232,31 determines whether the mechanism of the production equipment 2 has a variation according to the estimated external force disturbance tle, wherein if the determination result is no, the step S3 is executed. If the result of the determination is yes, step S63 is executed, and the processing parameter adjustment units 236 and 35 of the quality measurement and mechanism diagnosis modules 232 and 31 determine whether the production facility 2 can continue to process by adjusting the processing strategy C. If the determination result is yes, the machining parameter adjustment units 236 and 35 perform the adjustment of the machining strategy C, and re-perform step S22 to cause the controller to re-generate the machining strategy C. When the judgment result is no, step S5 is executed to drive the production apparatus 2 to a halt.
After step S2, step S7 may be executed to enable the production facility 2 to execute the idle mode. In this step, the idle mode may include the following substeps. First, step S71 is executed to execute the idling mode, so that the production facility 2 is operated but the finished product is not produced, and the virtual system driving module 21b of the driver 21 generates the third simulated operation parameter information y3 of the mechanism simulated operation parameter information R2 in accordance with the motor driving command u 1. The step S71 can be executed each time the number of the finished products outputted by the production equipment 2 reaches the second preset value Y. Next, step S72 is executed to enable the mechanism health diagnosis and degradation estimation units 234 and 33 of the quality measurement and mechanism diagnosis modules 232 and 31 to perform mechanism diagnosis according to the third simulated operation parameter information y3 to determine whether the mechanism of the production equipment 2 is degraded. When the determination result is no, step S3 is executed. If the determination result is yes, step S73 is executed to enable the processing parameter adjustment units 236 and 35 of the quality measurement and mechanism diagnosis modules 232 and 31 to determine whether the production facility 2 can continue to be processed by adjusting the processing strategy C. If the determination result is yes, the machining parameter adjustment units 236 and 35 perform the adjustment of the machining strategy C, and re-perform step S2 to cause the controller 23 to re-generate the machining strategy C. When the judgment result is no, step S5 is executed to drive the production apparatus 2 to a stop. In the embodiment, since the aging of the production equipment 2 is a slow-changing process, it is not necessary to use a too fast sampling update rate, but the processed products are continuously and rapidly generated, so that a faster sampling update rate is required, so the second preset value Y is greater than the first preset value X, in other words, the production equipment 2 can perform a processing sampling inspection operation every time the number of the continuously produced processed products reaches the first preset value X, and can perform an idle running mode every time the number of the continuously produced processed products reaches the second preset value Y, wherein the second preset value Y is greater than the first preset value X, and X and Y are both positive integers.
In the present embodiment, when the step S42 is executed, if the quality measurement result of the processed product does not meet the standard, the steps S62 to S63 or the steps S71 to S73 are executed in sequence according to the actual application requirement. In some embodiments, when the step S42 is executed, if the quality measurement result of the processed product does not meet the standard, the step S62 may be selectively executed according to the setting, so that the quality measurement and mechanism diagnosis module 232,31 determines whether the mechanism of the production equipment 2 is mutated according to the estimated external force disturbance tlesst, wherein when the determination result is negative, the step S3 is executed. If the result of the determination is yes, step S63 is executed, and the processing parameter adjustment units 236 and 35 of the quality measurement and mechanism diagnosis modules 232 and 31 determine whether the production facility 2 can continue to process by adjusting the processing strategy C. If the determination result is yes, the machining parameter adjustment units 236 and 35 perform the adjustment of the machining strategy C, and re-perform step S22 to cause the controller to re-generate the machining strategy C. When the judgment result is no, step S5 is executed to drive the production apparatus 2 to a halt.
In other embodiments, when step S42 is executed, if the quality measurement result of the processed product does not meet the standard, step S71 may be selectively executed according to the setting, a run-empty mode is executed, the production equipment 2 is operated but the processed product is not produced, and the virtual system driving module 21b of the driver 21 generates the third simulated operation parameter information y3 of the mechanism simulated operation parameter information R2 according to the motor driving command u 1. Next, step S72 is executed to enable the mechanism health diagnosis and degradation estimation units 234 and 33 of the quality measurement and mechanism diagnosis modules 232 and 31 to perform mechanism diagnosis according to the third simulated operation parameter information y3 to determine whether the mechanism of the production equipment 2 is degraded. When the determination result is no, step S3 is executed. If the determination result is yes, step S73 is executed to enable the processing parameter adjustment units 236 and 35 of the quality measurement and mechanism diagnosis modules 232 and 31 to determine whether the production facility 2 can continue to be processed by adjusting the processing strategy C. If the determination result is yes, the machining parameter adjustment units 236 and 35 perform the adjustment of the machining strategy C, and re-perform step S2 to cause the controller 23 to re-generate the machining strategy C. When the judgment result is no, step S5 is executed to drive the production apparatus 2 to a stop.
In fig. 7, a relatively thick flow line indicates a flow of an operation method performed by the production system 1 when the production system 1 performs a processing sampling operation (step S6) and then does not need to perform step S5 to stop the production equipment 2 (representing that there is no variation in the mechanism of the production equipment 2 or that the processing strategy is adjustable although there is variation and the production equipment 2 continues to process), or when the production system 1 performs an idle operation mode (step S7) and then does not need to perform step S5 to stop the production equipment 2 (representing that there is no aging in the mechanism of the production equipment 2 or that the processing strategy is adjustable although there is aging and the production equipment 2 continues to process), under the condition that the quality measurement result of the processed product meets the standard.
Please refer to fig. 8, which is a flowchart illustrating the sub-steps included in step S12 shown in fig. 7. In some embodiments, step S12 further includes the following substeps S121 to S123. First, step S121 is executed to drive the production facility 2 to execute the system identification mode, so that the driver 21 obtains a state bode (bode) diagram of the motor 20 and the mechanism 20a corresponding to the motor. Next, step S122 is executed to determine the number of operating parameters of the motor 20 and the main components of the mechanism 20a corresponding to the motor. Then, step S123 is executed to obtain initial values of the operating parameters of the motor 20 and the mechanism 20a corresponding to the motor by fitting a state bode plot with the frequency domain responses of the operating parameters of the main mechanism components of the mechanism 20a corresponding to the motor 20 and the motor, and to obtain a motor driving command u1, motor operating parameter information y1, and third simulated operating parameter information y3 of the control structure of the driver 21 by creating the first virtual mechanism model Mo and the second virtual mechanism model M1 and the third virtual mechanism model M2 with the initial values of the operating parameters. After step S122, step S13 is executed.
FIG. 9 is a flow chart of steps performed by another embodiment of a method of operation performed by the disclosed production system. In the present embodiment, the operation method executed by the production system 1 is similar to the operation method shown in fig. 7, but when step S42 is executed, if the quality measurement result of the processed product is not compliant with the standard, one of the following two steps can be selected according to the practical application requirement to execute, the first is that when the quality measurement result is not compliant with the standard, step S62 is executed to determine whether the mechanism of the production equipment 2 is altered to determine whether the reason that the quality measurement result of the processed product is not compliant with the standard is the mechanism of the production equipment 2 is altered, wherein when the determination result of step S62 is no, steps S71-S72 are executed in sequence to determine whether the mechanism of the production equipment 2 is aged through step S72, and further determine whether the reason that the quality measurement result of the processed product is not compliant with the standard is the aging mechanism of the production equipment 2, wherein when the determination result of step S72 is no, execution of step S5 forces the production apparatus 2 to stop. The second is to execute steps S71 to S72 in sequence when the quality measurement result is not in accordance with the standard, so as to determine whether the mechanism of the production equipment 2 is aged through step S72, and further to determine whether the reason why the quality measurement result of the processed product is not in accordance with the standard is aged, wherein if the determination result of step S72 is no, step S62 is further executed, whether the mechanism of the production equipment 2 is mutated, so as to determine whether the reason why the quality measurement result of the processed product is not in accordance with the standard is mutated, wherein if the determination result of step S62 is no, step S5 is executed to stop the production equipment 2. By the method of the embodiment, quality measurement, mechanism diagnosis and/or adjustment of the processing strategy can be realized according to actual use requirements, and when the quality measurement result of the processed finished product does not meet the standard, the reason why the processed finished product does not meet the standard is tried to be found by judging whether the mechanism of the production equipment 2 has variation or not and judging whether the mechanism of the production equipment 2 is aged, so that the production equipment 2 is driven to stop when the reason cannot be found.
In fig. 9, a relatively thick flow line indicates that the quality measurement result of the finished product in step S42 does not meet the standard, and whether the mechanism of the production facility 2 is mutated in step S62 and whether the mechanism of the production facility 2 is aged in step S72 cannot find the reason why the finished product does not meet the standard, and then the flow when the production facility 2 is stopped in step S5 is executed, and indicates that the quality measurement result of the finished product in step S42 does not meet the standard, and although whether the mechanism of the production facility 2 is mutated in step S62 or whether the mechanism of the production facility 2 is aged in step S72 and the reason why the finished product may not meet the standard is found, it is determined that the production facility 2 cannot continue to be processed by adjusting the processing strategy C in step S63 or step S73 (i.e., step S63 or step S73), and then the flow when step S5 is executed to drive the production apparatus 2 to stop.
In accordance with the concepts of the present disclosure, the production system 1 of the present disclosure is a hierarchical data processing architecture. In the embodiment, since the data amount sensed by the sensor 22 in the conventional technique is very huge, and the bandwidth of information transmission is limited, all data can be uploaded to the server only by reducing the data precision, so as to avoid the deficiency caused by the collective data processing architecture used in the conventional virtual measurement technique, the production system 1 of the present disclosure employs a hierarchical architecture for operation. In detail, the sensor 22 disposed in the motor 20 and the mechanism 20a corresponding to the motor is configured as a first-stage data processing device L1, wherein the sensor 22 can use a sensor with a higher sampling rate (i.e. higher resolution) to perform sensing to obtain the required operation parameter data, and the sensor 22 itself performs data processing, and after obtaining the required operation parameter data, the obtained characteristic operation parameter data can be transmitted to a second-stage data processing device L2, i.e. the driver 21, with a lower update rate. For example, after the sensor 22 senses the operation parameter data of the motor 20 and the mechanism 20a corresponding to the motor at 50KHz, the sensed operation parameter information can be processed into 20KHz information according to the information required by the driver 21 to establish the virtual mechanism models M0, M1, and M2, and then transmitted to the driver 21, so that the driver 21 establishes the virtual mechanism models M0, M1, and M2. Similarly, the second-stage data processing device L2 processes the received operation parameter data into, for example, a motor driving command u1, motor operation parameter information y1, predicted external force disturbance TLest, third simulation operation parameter information y3, and transmits the data to the third-stage data processing device L3, i.e., the controller 23, at a lower update rate. Then, the controller 23 processes the received operation parameter information, and transmits the data to the fourth level data processing device L4, i.e. the local server 3, at a lower update rate, and so on, by adopting a layered data processing architecture in the production system 1, not only the sensor 22 can operate at an ultra-high sampling rate to improve the sensing accuracy, but also the transmission line of the sensor 22 is not required to be directly wired to the local server 3 and transmit the data to the local server 3, but the operation parameter information is transmitted to the driver 21 and the controller 23 with close distances to process, so that the transmission line of the sensor 22 can be shortened. Furthermore, the data processing devices of the respective layers share the information processing, so that the performance of each data processing device can be effectively utilized, and thus, the local server 3 does not need to have a strong processing performance and a huge storage memory as in the conventional technology, thereby greatly reducing the hardware cost. In addition, since the production system 1 can directly utilize the sensor 22 originally existing or built in the production equipment 2 itself, and establish the virtual mechanism models M0, M1, M2 having relationship with the motor 20 and having physical quantity significance in the driver 21, so that the controller 23 or the local server 3 utilizes the real system driving module 21a and the virtual mechanism models M0, M1, M2 of the virtual system driving module 21b to generate the real mechanism operating parameter information R1 (such as the motor driving command u1, the motor operating parameter information y1) and the mechanism simulation operating parameter information R2 (such as the estimated external force disturbance TLest and the third simulation operating parameter information y3) to perform the quality measurement, the mechanism health diagnosis and the degradation estimation of the finished product, it is not necessary to additionally install a large number of sensors on the production equipment 2, so that the testing cost can be greatly reduced, because the virtual mechanism models M0, M1, and M2 have the meaning of the physical quantities of the motors 20 and the mechanisms 20a corresponding to the motors, more accurate simulation operation parameter information can be provided, so that the controller 23 or the local server 3 can accurately distinguish the reasons of poor finished products, and the processing strategies of the controller 23 can be correspondingly adjusted and improved. In some embodiments, the cloud server 4 may be configured as a fifth-level data processing device L5, which may encode information at a lower sampling rate.
FIG. 10 is a diagram illustrating an exemplary configuration of a tool station for use in the disclosed manufacturing system. In some embodiments, the production equipment 2 of the production system 1 of the present disclosure can be applied to a 2D milling machine, wherein the 2D milling machine is an XY two-axis machining machine, and therefore the X driver 21X and the Y driver 21Y are used to respectively represent the motor 20 in the control X axis and the motor 20 in the control Y axis. For convenience of explanation, the reference numerals of the respective elements described below are represented by subscript X indicating the relevant elements and information on the X axis, and subscript Y indicating the relevant elements and information on the Y axis. Referring to fig. 1 to 6 and 8, first, the interpretation and trajectory interpolation module 231 of the controller 23 interprets the G code of the control command p issued by the user as the G code, and interpolates the trajectory according to the interpretation result to plan the motion trajectories of the two XY axes of the production equipment 2, thereby providing the corresponding processing strategy C to the X driver 21X and the Y driver 21Y. When the X driver 21X and the Y driver 21Y drive the corresponding motor 20 to operate according to the processing strategy C, the X driver 21X receives the actual external force interference TLx, and generates and outputs a motor driving command u1X, motor operating parameter information Y1X, third simulated operating parameter information Y3X, and estimated external force interference TLestx, and the Y driver 21Y receives the actual external force interference tley, and generates and outputs a motor driving command u1Y, motor operating parameter information Y1Y, third simulated operating parameter information Y3Y, and estimated external force interference TLesty. Then, the controller 23 or the local server 3 of the production facility 2 may perform feature extraction, model prediction, and accident detection through the quality measurement units 233 and 32 (shown in fig. 5 and 6) of the quality measurement and mechanism diagnosis modules 232 and 31 according to the information such as the motor operation parameter information y1x, the predicted external force interference TLestx, the motor operation parameter information y1y, and the predicted external force interference TLesty. In some embodiments, the measurement of the processing condition and the quality of the processed product can be realized by measuring the dimension error of the processed product. Since the operation and principle of the finished product quality measuring units 233,32 are as described in the foregoing embodiments, detailed description thereof is omitted. The controller 23 or the local server 3 of the production facility 2 may implement the facility aging diagnosis and estimation of the production facility 2 or the facility aging index estimation of the production facility 2 through the facility health diagnosis and degradation estimation units 234 and 33 (as shown in fig. 5 and fig. 6) of the quality measurement and facility diagnosis modules 232 and 31 according to the information of the third simulated operation parameter information y3x, the third simulated operation parameter information y3y, and the like. Since the operation and principle of the mechanism health diagnosis and degradation estimation units 234,33 are as described in the previous embodiments, the detailed description thereof is omitted. Then, the good product determination and confidence index units 235,34 of the quality measurement and mechanism diagnosis modules 232,31 of the controller 23 or the local server 3 may determine whether the processed product is good or not and provide a confidence index reflecting the reliability of the estimation according to the output information of the processed product quality measurement units 233,32 and the output information of the mechanism health diagnosis and degradation estimation units 234, 33. Finally, in some embodiments, the processing parameter adjusting units 236 and 35 of the quality measurement and mechanism diagnosis modules 232 and 31 of the controller 23 or the local server 3 correspondingly adjust the processing strategy C according to the output information of the non-defective product determination and confidence index units 235 and 34, or directly according to the output information of the processed product quality measuring units 233 and 32, and according to the output information of the mechanism health diagnosis and degradation estimation units 234 and 33, so that the controller 23 receives the adjusted processing strategy C and performs interpretation and trajectory interpolation operations again to re-plan the motion trajectories of the two XY axes of the production equipment 2, thereby driving the X driver 21X and the Y driver 21Y to operate through the adjusted processing strategy C.
In summary, the present disclosure provides a production system, a driver and a method thereof to achieve the functions of product quality measurement and monitoring, mechanism health diagnosis and degradation prediction, and intelligent control. The production system and the driver thereof have the functions of model, control, measurement, diagnosis and the like, can realize layered data processing to reduce data transmission and operation burden, simplify wiring and improve efficiency, can predict product quality in real time, provide external force interference measurement, improve prediction accuracy, realize production equipment capacity monitoring, adjust a processing strategy according to mechanism variation to optimize capacity, provide mechanism health diagnosis and aging prediction of production equipment, and reduce hardware and measurement cost.
Claims (18)
1. A driver for a production apparatus to drive a motor of the production apparatus to operate according to control of a controller of the production apparatus, so that the production apparatus performs a system identification mode, performs a processing mode to produce a processed product, or performs an idle operation mode, the driver comprising:
a real system driving module, configured in the processing mode, for generating a mechanism real operation parameter information according to a processing strategy of the controller and an external force interference; and
a virtual system driving module, including a quality measurement and mechanism diagnosis parameter processing module, the quality measurement and mechanism diagnosis parameter processing module establishes at least one virtual mechanism model in the system identification mode, and generates a mechanism simulation operation parameter information according to the processing strategy of the controller, the mechanism real operation parameter information and the at least one virtual mechanism model in the processing mode or the idle operation mode, wherein the quality measurement, the mechanism diagnosis and/or the adjustment of the processing strategy are realized by providing the mechanism real operation parameter information and the mechanism simulation operation parameter information to the controller,
wherein, this real system drive module includes:
a real mechanism driving unit for receiving the processing strategy of the controller and outputting a motor driving command in response to the processing strategy; and
a controlled body, which is established according to the motor and the mechanism corresponding to the motor, receives the motor driving instruction and the external force interference in the processing mode, and generates and outputs motor operation parameter information,
wherein the motor driving command and the motor operation parameter information are constructed as the real operation parameter information of the mechanism,
wherein the quality measurement and mechanism diagnosis parameter processing module of the virtual system driver module comprises:
a first virtual mechanism model which is established according to a main mechanism component model of the controlled body of the real system driving module in the system identification mode and reflects physical quantity parameters of the controlled body;
the virtual mechanism driving unit is used for receiving the processing strategy of the controller and outputting a first driving instruction so as to control the first virtual mechanism model to generate first simulated operation parameter information;
a second virtual mechanism model which is established according to the first virtual mechanism model and receives a predicted external force interference, wherein the second virtual mechanism module receives the motor driving instruction and correspondingly generates second simulated operation parameter information in the processing mode; and
a third virtual mechanism model, which is established according to the first virtual mechanism model and receives the motor driving command and correspondingly generates a third simulation operation parameter information in the idle running mode,
the real mechanism driving unit generates a second driving command according to the processing strategy, and the first driving command and the second driving command are combined to form the motor driving command.
2. The drive of claim 1, wherein the quality measurement and mechanism diagnostic parameter processing module of the virtual system driver module comprises:
an external force estimation unit configured in the processing mode, generating the estimated external force interference according to the second simulation operation parameter information and the motor operation parameter information, and providing the estimated external force interference to the second virtual mechanism model;
the estimated external force interference and the third simulation operation parameter information are constructed as simulation operation parameter information of the mechanism.
3. The drive of claim 2, wherein the quality measurement is performed based on the motor operating parameter information and the estimated external force disturbance, the mechanism diagnosis is performed based on the third simulated operating parameter information, and the adjustment of the machining strategy is performed in response to the results of the quality measurement and the mechanism diagnosis.
4. The driver as claimed in claim 2, wherein the first simulated operation parameter information is fed back to the virtual mechanism driving unit, the real mechanism driving unit and the external force estimation unit, the motor operation parameter information is fed back to the real mechanism driving unit and the external force estimation unit, and the second simulated operation parameter information is fed back to the external force estimation unit.
5. A production system, comprising:
a production apparatus configured to execute a system authentication mode, execute a processing mode to produce at least one processed product, or execute an idle mode, the production apparatus comprising:
at least one motor;
at least one sensor configured to sense at least one operating parameter of the motor and a mechanism corresponding to the motor; and
at least one controller configured to output a processing strategy;
at least one driver connected to the motor and the controller, receiving the at least one operation parameter sensed by the at least one sensor, receiving the processing strategy and driving the motor to operate according to the processing strategy, wherein the driver comprises:
a real system driving module configured in the processing mode to generate a mechanism real operation parameter information according to the processing strategy of the controller and an external force interference; and
a virtual system driving module, including a quality measurement and mechanism diagnosis parameter processing module, the quality measurement and mechanism diagnosis parameter processing module establishes at least one virtual mechanism model in the system identification mode, and generates a mechanism simulation operation parameter information according to the processing strategy of the controller, the mechanism real operation parameter information and the at least one virtual mechanism model in the processing mode or the idle operation mode;
a local server connected with the controller; and
a quality measurement and mechanism diagnosis module configured in at least one of the controller and the local server and receiving and implementing quality measurement, mechanism diagnosis and/or adjustment of the processing strategy according to the real mechanism operating parameter information and the mechanism simulation operating parameter information,
wherein, this real system drive module includes:
a real mechanism driving unit for receiving the processing strategy of the controller and outputting a motor driving command in response to the processing strategy; and
a controlled body, which is established according to the motor and the mechanism corresponding to the motor, receives the motor driving instruction and the external force interference in the processing mode, and generates and outputs motor operation parameter information,
wherein the motor driving command and the motor operation parameter information are constructed as the real operation parameter information of the mechanism,
wherein the quality measurement and mechanism diagnosis parameter processing module of the virtual system driver module comprises:
a first virtual mechanism model which is established according to a main mechanism component model of the controlled body of the real system driving module in the system identification mode and reflects physical quantity parameters of the controlled body;
the virtual mechanism driving unit is used for receiving the processing strategy of the controller and outputting a first driving instruction so as to control the first virtual mechanism model to generate first simulated operation parameter information;
a second virtual mechanism model which is established according to the first virtual mechanism model and receives a predicted external force interference, wherein the second virtual mechanism module receives the motor driving instruction and correspondingly generates second simulated operation parameter information in the processing mode; and
a third virtual mechanism model, which is established according to the first virtual mechanism model and receives the motor driving command and correspondingly generates a third simulation operation parameter information in the idle running mode,
the real mechanism driving unit generates a second driving command according to the processing strategy, and the first driving command and the second driving command are combined to form the motor driving command.
6. The production system of claim 5, wherein the quality measurement and mechanism diagnostic parameter processing module of the virtual system driver module comprises:
an external force estimation unit configured in the processing mode, generating the estimated external force interference according to the second simulation operation parameter information and the motor operation parameter information, and providing the estimated external force interference to the second virtual mechanism model;
the estimated external force interference and the third simulation operation parameter information are constructed as simulation operation parameter information of the mechanism; and
the first simulation operation parameter information is fed back to the virtual mechanism driving unit, the real mechanism driving unit and the external force estimation unit, the motor operation parameter information is fed back to the real mechanism driving unit and the external force estimation unit, and the second simulation operation parameter information is fed back to the external force estimation unit.
7. The production system of claim 6 wherein the quality measurement and mechanism diagnostic module comprises:
a finished product quality measuring unit for receiving the motor driving instruction and the motor operation parameter information of the mechanism real operation parameter information of the driver, receiving the estimated external force interference of the mechanism virtual operation parameter information, and measuring and estimating the quality of the finished product according to the motor operation parameter information and the estimated external force interference; and
and the mechanism health diagnosis and degradation estimation unit receives the third simulated operation parameter data of the mechanism simulated operation parameter information of the driver and carries out mechanism health diagnosis and degradation estimation according to the third simulated operation parameter data.
8. The production system of claim 7 wherein the quality measurement and mechanism diagnostic module further comprises:
a good product determination and confidence index unit for receiving an output information of the processed product quality measurement unit or the mechanism health diagnosis and degradation estimation unit, and performing a good product determination and providing a confidence index according to the output information; and
and the processing parameter adjusting unit is used for receiving the output information of the processed product quality measuring unit or the mechanism health diagnosis and degradation estimation unit and selectively adjusting the processing strategy according to the output information.
9. The manufacturing system of claim 5, wherein the controller comprises an interpretation and trajectory interpolation module configured to receive a control command from a user, interpret the control command and interpolate a position of the control command to generate the processing strategy and provide the processing strategy to the driver.
10. The manufacturing system of claim 5, wherein the manufacturing system includes a hierarchical data processing architecture, wherein the at least one sensor disposed on the motor is configured as a first level data processing device, the at least one driver is configured as a second level data processing device, the at least one controller is configured as a third level data processing device, and the local server is configured as a fourth level data processing device.
11. The production system of claim 5, further comprising a cloud server coupled to the local server for receiving and recording information provided by the local server.
12. A method of operating a production system according to any one of claims 5 to 11, wherein the production system comprises a production facility, a local server and a quality measurement and mechanism diagnosis module, the production facility comprising at least one motor, at least one sensor, at least one controller and at least one driver, the driver comprising a real system driver module and a virtual system driver module, the quality measurement and mechanism diagnosis module being configured in at least one of the controller and the local server, the method comprising the steps of:
(S1) executing the manufacturing apparatus in a system authentication mode, and enabling the driver to establish at least one virtual mechanism model of the virtual system driver module;
(S2) causing the controller to generate a processing strategy and provide the processing strategy to the driver to drive the motor to operate;
(S3) executing the manufacturing apparatus in a processing mode, and enabling the real system driving module of the driver to generate a real mechanism operating parameter information due to the processing strategy of the controller and an external force disturbance, and enabling the virtual system driving module of the driver to generate a simulated mechanism operating parameter information, wherein the real mechanism operating parameter information includes a motor driving command and a motor operating parameter information, and the simulated mechanism operating parameter information includes an estimated external force disturbance; and
(S4) the production equipment outputs at least one processed product, and the quality measurement and mechanism diagnosis module measures the quality of the processed product according to the motor operation parameter information and the estimated external force interference.
13. The method of claim 12, further comprising the step (S6) of performing a machining snapshot operation on the manufacturing system, wherein the machining snapshot operation comprises the following sub-steps:
(S61) when the number of the finished products output by the production equipment reaches a first preset value, taking the finished products for sampling inspection;
(S62) the quality measurement and mechanism diagnosis module determines whether the mechanism of the production equipment has variation according to the estimated external force interference, wherein if the determination result is negative, the step is executed (S3); and
(S63) when the determination result of the step (S62) is yes, a processing parameter adjustment unit of the quality measurement and mechanism diagnosis module determines whether the manufacturing equipment can continue to process by adjusting the processing strategy, wherein when the determination result is yes, the processing parameter adjustment unit performs the adjustment of the processing strategy and re-performs the step (S2) to make the controller re-generate the processing strategy.
14. The method of claim 13, further comprising the step (S7) of causing the production equipment to execute an idle mode, and the idle mode includes the substeps of:
(S71) executing the idle mode to operate the manufacturing equipment but not to manufacture the finished product, and enabling the virtual system driving module of the driver to generate a third simulated operation parameter information of the mechanism simulated operation parameter information according to the motor driving command;
(S72) making a mechanism health diagnosis and degradation estimation unit of the quality measurement and mechanism diagnosis module perform mechanism diagnosis according to the third simulated operation parameter information to determine whether the mechanism of the production equipment is aged, wherein if the determination result is no, the step is performed (S3); and
(S73) when the determination result of the step (S72) is yes, a processing parameter adjustment unit of the quality measurement and mechanism diagnosis module determines whether the manufacturing equipment can continue to process by adjusting the processing strategy, wherein when the determination result is yes, the processing parameter adjustment unit performs the adjustment of the processing strategy, and re-performs the step (S2) to cause the controller to re-generate the processing strategy.
15. The method of claim 14, wherein the step (S71) is performed whenever the number of the processed products outputted from the manufacturing equipment reaches a second preset value, and the second preset value is greater than the first preset value.
16. The method of claim 14, wherein the step (S5) is performed to stop the production equipment when the determination result of the step (S63) is negative and indicates that the machining strategy cannot be adjusted, and the step (S5) is performed to stop the production equipment when the determination result of the step (S73) is negative and indicates that the machining strategy cannot be adjusted.
17. The method of claim 14, wherein in the step (S4), when the quality measurement result of the processed product meets a criterion, the step (S3) is performed, and in the step (S4), when the quality measurement result of the processed product does not meet a criterion, the step (S62) is performed to determine whether or not the mechanism of the production equipment is deteriorated, and when the determination result of the step (S62) is NO, the steps (S71) and (S72) are performed in order to determine whether or not the mechanism of the production equipment is deteriorated by the step (S72), and when the determination result of the step (S72) is NO, the step (S5) is performed to stop the production equipment, or when the quality measurement result of the step (S4) is not met, the steps (S71) to (S72) are performed in order to determine whether or not the mechanism of the production equipment is deteriorated by the step (S72), and executing the step (S62) to determine whether or not the mechanism of the production facility has been altered when the determination result of the step (S72) is no, and executing the step (S5) to stop the production facility when the determination result of the step (S62) is no.
18. The method of operating a production system as claimed in claim 12, wherein the step (S1) includes the sub-steps of:
(S11) starting the production system;
(S12) the production equipment executes the system identification mode to make the driver establish a first virtual mechanism model, a second virtual mechanism model and a third virtual mechanism model of the at least one virtual mechanism model, wherein a real mechanism driving unit of the real system driving module generates the motor driving command, and a controlled object of the real system driving module generates the motor operation parameter information in response to the motor driving command, wherein the second virtual mechanism model generates a second simulated operation parameter information in response to the motor driving command and an estimated external force disturbance, an external force estimation unit of the virtual system driving module generates the estimated external force disturbance in response to the motor operation parameter information and the second simulated operation parameter information and provides the estimated external force disturbance to the second simulated mechanism model, wherein the third virtual mechanism model generates a third simulated operation parameter information in response to the motor driving command, thereby obtaining the motor driving instruction, the motor operation parameter information and the third simulation operation parameter information of the driver; and
(S13) verifying whether the first virtual machine model is completely built by using the motor operating parameter information and the third simulated operating parameter information, wherein if the verification result is negative, the step is executed (S12).
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| TW202006574A (en) | 2020-02-01 |
| CN110716509A (en) | 2020-01-21 |
| TWI692702B (en) | 2020-05-01 |
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