CN113536464B - Dimension control method and dimension control system based on artificial intelligence - Google Patents
Dimension control method and dimension control system based on artificial intelligence Download PDFInfo
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Abstract
本发明提供了一种基于人工智能的尺寸控制方法及尺寸控制系统，属于尺寸控制领域。该尺寸控制方法包括：以各种情况下的目标类产品的全周期的尺寸信息、相关的标准信息和知识库作为输入信息以及对应的尺寸问题、调整方案以及尺寸性能预测结果作为输出信息根据人工智能算法建立所述目标类产品的人工智能尺寸预测模型；将属于所述目标类产品的目标产品的尺寸信息输入所述人工智能尺寸预测模型，以得出所述目标产品的尺寸问题、调整方案以及尺寸性能预测结果；将所述目标产品的尺寸问题、调整方案以及尺寸性能预测结果发送至相应的尺寸控制单元。本发明的尺寸控制方法及尺寸控制系统能够提高尺寸问题预测的效率。
The invention provides a size control method and a size control system based on artificial intelligence, which belong to the field of size control. The dimensional control method includes: taking the full-cycle dimensional information of target products under various circumstances, relevant standard information and knowledge bases as input information and corresponding dimensional problems, adjustment plans and dimensional performance prediction results as output information based on manual An intelligent algorithm establishes an artificial intelligence size prediction model of the target product; inputs the size information of the target product belonging to the target product into the artificial intelligence size prediction model to obtain the size problem and adjustment plan of the target product and dimensional performance prediction results; sending the dimensional problems, adjustment plans and dimensional performance prediction results of the target product to the corresponding size control unit. The size control method and size control system of the present invention can improve the efficiency of size problem prediction.
Description
Technical Field
The invention belongs to the field of size control, and particularly relates to an artificial intelligence-based size control method and a size control system.
Background
Along with the impact of new potential vehicle making, the traditional vehicle enterprise has to find breakthroughs as soon as possible in the aspects of shortening the whole vehicle research and development period and bringing zero problems into the production line.
The traditional vehicle manufacturing mode has complex and changeable size flow, small standard to be followed by the size work, empirical size knowledge and problem solving. For a number of reasons, it is difficult to adapt conventional size solutions to the requirements of modern vehicle construction, and there is a need to design an efficient size solution.
Disclosure of Invention
It is an object of a first aspect of the present invention to provide an artificial intelligence based size control method capable of improving efficiency of size problem prediction.
It is a further object of the invention to visualize the size predictions.
It is an object of a second aspect of the present invention to provide an artificial intelligence based size control system that can improve the efficiency of size problem prediction.
In particular, the present invention provides an artificial intelligence based size control method comprising:
setting up an artificial intelligent size prediction model of the target product according to an artificial intelligent algorithm by taking full-period size information, related standard information and a knowledge base of the target product under various conditions as input information and corresponding size problems, adjustment schemes and size performance prediction results as output information;
inputting the size information of the target product belonging to the target product into the artificial intelligent size prediction model to obtain the size problem, the adjustment scheme and the size performance prediction result of the target product;
and sending the size problem, the adjustment scheme and the size performance prediction result of the target product to a corresponding size control unit.
Optionally, after the step of inputting the dimension information of the target product belonging to the target product class into the artificial intelligence dimension prediction model to obtain the dimension problem, the adjustment scheme and the dimension performance prediction result of the target product, the method further includes:
and displaying the size problem, the adjustment scheme and the size performance prediction result of the target product.
Optionally, after the step of sending the size problem, the adjustment scheme, and the size performance prediction result of the target product to the corresponding size control unit, the method further includes:
the size control unit performs corresponding pre-adjustment according to the adjustment scheme.
Optionally, the full-period size information includes size design information, size control information, size verification information, and size assurance information.
Optionally, the standard information includes dimension workflow standardization information for standardizing each dimension work, enterprise standards, and industry standards.
Optionally, the knowledge base includes expertise information related to solving the size problem.
Optionally, the dimensional performance prediction result includes a dimensional qualification rate and an appearance quality parameter.
In particular, the invention also provides an artificial intelligence-based size control system which is characterized by comprising a controller and a size control unit which are in communication connection, wherein the controller comprises a memory and a processor, a control program is stored in the memory, and the control program is executed by the processor and is used for controlling the size according to any one of the above size control methods.
Optionally, the size control system further comprises:
and the visualization unit is connected with the controller and is used for receiving and displaying the size problem, the adjustment scheme and the size performance prediction result of the target product.
Optionally, the size control unit is configured to perform corresponding pre-adjustment according to the adjustment scheme.
According to the invention, an artificial intelligent size prediction model is constructed through big data and an artificial intelligent algorithm, namely, based on a complete standard size flow, a comprehensive size knowledge base and standard workings, an accurate artificial intelligent size prediction model is established based on historical data, on one hand, the model can intelligently output a size problem reason and an adjustment scheme, on the other hand, the size performance level can be predicted according to given production conditions and states, and the intellectualization of product size problem analysis is realized, so that a designer can conveniently know related size problems before production, timely adjustment is performed, improvement of product development efficiency is facilitated, and rework cost is saved.
Further, the invention receives the size problem, the adjustment scheme and the size performance prediction result output by the artificial intelligent size prediction model through the visualization unit, and displays the information, so that a designer can know the problem in time, and the solution and the prediction result are convenient for the designer to carry out professional judgment and targeted adjustment by combining the prediction information.
The above, as well as additional objectives, advantages, and features of the present invention will become apparent to those skilled in the art from the following detailed description of a specific embodiment of the present invention when read in conjunction with the accompanying drawings.
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Some specific embodiments of the invention will be described in detail hereinafter by way of example and not by way of limitation with reference to the accompanying drawings. The same reference numbers will be used throughout the drawings to refer to the same or like parts or portions. It will be appreciated by those skilled in the art that the drawings are not necessarily drawn to scale. In the accompanying drawings:
FIG. 1 is a flow chart of an artificial intelligence based dimensional control method according to one embodiment of the invention;
FIG. 2 is a flow chart of an artificial intelligence based dimensional control method according to another embodiment of the invention;
FIG. 3 is a block diagram of a connection of an artificial intelligence based dimensional control system according to one embodiment of the invention;
FIG. 4 is a block diagram of a connection of an artificial intelligence based dimensional control system according to another embodiment of the invention.
Detailed Description
FIG. 1 is a flow chart of an artificial intelligence based dimensional control method according to one embodiment of the invention. As shown in fig. 1, in one embodiment, the size control method includes:
step S100, an artificial intelligent size prediction model of the target product is established according to an artificial intelligent algorithm by taking full-period size information, related standard information and a knowledge base of the target product under various conditions as input information and corresponding size problems, adjustment schemes and size performance prediction results as output information. Alternatively, the target class product may be a vehicle. In one embodiment, the full-period size information includes size design information, size control information, size verification information, and size assurance information. For example, for a whole vehicle, its dimensional design information includes positioning design information, tolerance design, and robustness design information; the size control information comprises part size control information, tooling size control information and whole vehicle size control information; the dimension verification information comprises positioning rationality verification information, assembly rationality verification information, dimension physical verification information and the like, and the dimension assurance information comprises assembly sequence assurance information, dimension related process assurance information, process part tolerance information and positioning assurance information. The standard information includes size workflow standardization information for standardizing each size job, enterprise standards, and industry standards. The knowledge base includes expertise information related to solving the size problem. The dimension work standardization is to standardize the stations and procedures related to the dimension from design, verification, mass production and the like of the whole vehicle. By inputting a large amount of data and self-learning the model, an accurate artificial intelligent size prediction model can be established.
Step S200, inputting the size information of the target product belonging to the target product into an artificial intelligent size prediction model to obtain the size problem, the adjustment scheme and the size performance prediction result of the target product. Optionally, the dimensional performance prediction result includes a dimensional yield and an appearance quality parameter. For example, the size qualification rate of the white car body, and appearance quality parameters include parameters such as gaps, break differences, fillets, parallelism and the like.
Step S300, the size problem, the adjustment scheme, and the size performance prediction result of the target product are sent to the corresponding size control unit 20.
According to the embodiment, the artificial intelligence size prediction model is constructed through big data and an artificial intelligence algorithm, namely, based on a complete standard size flow, a comprehensive size knowledge base and standard workings, an accurate artificial intelligence size prediction model is established based on historical data, on one hand, the model can intelligently output a size problem reason and an adjustment scheme, on the other hand, the size performance level can be predicted according to given production conditions and states, the intellectualization of product size problem analysis is realized, and therefore a designer can conveniently know related size problems before production, timely adjustment is carried out, improvement of product development efficiency is facilitated, and rework cost is saved.
FIG. 2 is a flow chart of an artificial intelligence based dimensional control method according to another embodiment of the invention. In another embodiment, as shown in fig. 2, step S200 further includes:
step S250, displaying the size problem, the adjustment scheme and the size performance prediction result of the target product.
The visual unit 30 is used for receiving the size problem, the adjustment scheme and the size performance prediction result output by the artificial intelligence size prediction model, and displaying the information, so that a designer can know the problem in time, and the solution and the prediction result are convenient for the designer to carry out professional judgment and targeted adjustment by combining the prediction information. The visualization unit 30 may be a unit that performs display in a centralized manner, which is provided separately, or may be a display that performs display on each size control unit 20.
As shown in fig. 2, in this embodiment, step S300 further includes:
in step S400, the size control unit 20 performs corresponding pre-adjustment according to the adjustment scheme. In this embodiment, the dimension control unit 20 may perform pre-adjustment before production according to an adjustment scheme, for example, the distance between two holes does not meet the precision requirement, and the processing equipment (i.e., the dimension control unit 20) corresponding to the two holes is subjected to programming trimming, so as to ensure that the distance between the two holes meets the design requirement as much as possible during the formal production.
FIG. 3 is a block diagram of a connection of an artificial intelligence based dimensional control system in accordance with one embodiment of the invention. The present invention also provides an artificial intelligence based size control system, as shown in fig. 3, which in one embodiment comprises a communicatively coupled controller 10 and a size control unit 20. The controller 10 comprises a memory and a processor, wherein a control program is stored in the memory, which control program, when executed by the processor, is according to the size control method in any one of the embodiments or combinations of embodiments described above. The processor may be a central processing unit (central processing unit, CPU for short), or a digital processing unit or the like. The processor transmits and receives data through the communication interface. The memory is used for storing programs executed by the processor. The memory is any medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, and can be a combination of multiple memories. The above-described computer program may be downloaded from a computer readable storage medium to a corresponding computing/processing device or downloaded to a computer or an external memory device via a network (e.g., the internet, a local area network, a wide area network, and/or a wireless network).
In this embodiment, an artificial intelligence size prediction model is embedded in the controller 10 of the size control system, and based on a complete and standardized size flow, and the working of a comprehensive size knowledge base and standards, an accurate artificial intelligence size prediction model is established based on historical data, and the model can intelligently output the reasons and adjustment schemes of size problems on the one hand, and can predict the size performance level according to given production conditions and states on the other hand. The size control system can complete size prediction, and achieves intellectualization of product size problem analysis, so that designers can know related size problems before production conveniently, timely adjustment is carried out, improvement of product development efficiency is facilitated, and reworking cost is saved.
The size control system is also used for transmitting the size problem, the adjustment scheme and the size performance prediction result of the target product to the corresponding size control unit 20, thereby completing the driving of the whole size production.
FIG. 4 is a block diagram of a connection of an artificial intelligence based dimensional control system according to another embodiment of the invention. In another embodiment, as shown in fig. 4, the size control system further comprises a visualization unit 30. The visualization unit 30 is connected to the controller 10, and is configured to receive and display the size problem, the adjustment scheme, and the size performance prediction result of the target product.
The visual unit 30 is used for receiving the size problem, the adjustment scheme and the size performance prediction result output by the artificial intelligence size prediction model, and displaying the information, so that a designer can know the problem in time, and the solution and the prediction result are convenient for the designer to carry out professional judgment and targeted adjustment by combining the prediction information. The visualization unit 30 may be a unit that performs display in a centralized manner, which is provided separately, or may be a display that performs display on each size control unit 20.
In a further embodiment, the size control unit 20 is adapted to perform a corresponding pre-adjustment according to an adjustment scheme. The pre-adjustment of the size control unit 20 can ensure that the size meets the design requirement as much as possible during the formal production, so as to avoid the problems of reworking and other size trimming.
By now it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been shown and described herein in detail, many other variations or modifications of the invention consistent with the principles of the invention may be directly ascertained or inferred from the present disclosure without departing from the spirit and scope of the invention. Accordingly, the scope of the present invention should be understood and deemed to cover all such other variations or modifications.
Claims (9)
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07152810A (en) * | 1993-11-26 | 1995-06-16 | Toshiba Corp | Environment model creating device |
| CN106182765A (en) * | 2016-07-05 | 2016-12-07 | 上海交通大学 | 3D printer model scale error Forecasting Methodology based on support vector machine |
| CN108445835A (en) * | 2018-04-24 | 2018-08-24 | 华中科技大学 | A kind of Dimension Measurement prediction technique of numerically-controlled machine tool |
| US10120963B1 (en) * | 2017-05-05 | 2018-11-06 | Globalfoundries Inc. | Figurative models calibrated to correct errors in process models |
| CN109933852A (en) * | 2019-02-14 | 2019-06-25 | 东软集团股份有限公司 | Predict method, apparatus, storage medium and the electronic equipment of vehicle dimension deviation |
| KR102219026B1 (en) * | 2020-11-27 | 2021-02-23 | (주) 토즈 | Ship design error prediction system through model learning |
| CN112733435A (en) * | 2020-12-29 | 2021-04-30 | 东风汽车集团有限公司 | Whole vehicle size matching deviation prediction method based on multi-model fusion |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6915244B2 (en) * | 2000-01-31 | 2005-07-05 | Kabushiki Kaisha Kobe Seiko Sho (Kobe Steel, Ltd.) | Method for predicting an amount of dimensional accuracy defect at the time of press-forming metal sheet |
| US10146225B2 (en) * | 2017-03-02 | 2018-12-04 | GM Global Technology Operations LLC | Systems and methods for vehicle dimension prediction |
-
2021
- 2021-07-21 CN CN202110823255.8A patent/CN113536464B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07152810A (en) * | 1993-11-26 | 1995-06-16 | Toshiba Corp | Environment model creating device |
| CN106182765A (en) * | 2016-07-05 | 2016-12-07 | 上海交通大学 | 3D printer model scale error Forecasting Methodology based on support vector machine |
| US10120963B1 (en) * | 2017-05-05 | 2018-11-06 | Globalfoundries Inc. | Figurative models calibrated to correct errors in process models |
| CN108445835A (en) * | 2018-04-24 | 2018-08-24 | 华中科技大学 | A kind of Dimension Measurement prediction technique of numerically-controlled machine tool |
| CN109933852A (en) * | 2019-02-14 | 2019-06-25 | 东软集团股份有限公司 | Predict method, apparatus, storage medium and the electronic equipment of vehicle dimension deviation |
| KR102219026B1 (en) * | 2020-11-27 | 2021-02-23 | (주) 토즈 | Ship design error prediction system through model learning |
| CN112733435A (en) * | 2020-12-29 | 2021-04-30 | 东风汽车集团有限公司 | Whole vehicle size matching deviation prediction method based on multi-model fusion |
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