Aircraft part production quality optimization method and system based on data analysis

Abstract

The invention relates to the technical field of intelligent manufacturing, and discloses an aircraft part production quality optimization method and system based on data analysis, and the method carries out the quality production through building an instrument monitoring module, a monitoring data calculation module, a monitoring early warning module and a monitoring data management module. The instrument monitoring module is divided into a tool detection data unit, a part detection data unit, a subassembly detection data unit and an aviation final assembly detection data unit, and the monitoring data calculation module is divided into a tool error unit, a part defect unit, a subassembly defect unit and an aviation final assembly defect unit. And calculating a tool error index Hxl, a part semi-finished product defect detection index Fiy, a part finished product defect detection index Fiz, a subassembly defect unqualified area Arj and an aviation final assembly completion index Net, and finally adjusting parameters of each module through the indexes, thereby realizing dynamic monitoring of the preparation process and control of part defects.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent manufacturing, and particularly to a method and system for optimizing the production quality of aircraft components based on data analysis. Background Art

[0002] In the production of aircraft components, although significant progress in numerical control technology, materials science, and quality control systems has greatly improved processing efficiency and product quality, traditional welding and joining technologies still have some defects. These defects directly affect the structural integrity and performance of the aircraft, so understanding these technical defects is the key to further optimizing production technology. Summary of the Invention

[0003] (1) Technical Problems to be Solved

[0004] In view of the deficiencies of the prior art, the present invention provides a method and system for optimizing the production quality of aircraft components based on data analysis, which have the advantages of perfect welding and defect-free connection, and solve the problems of welding and connection defects.

[0005] (2) Technical Solutions

[0006] To achieve the above object, the present invention provides the following technical solutions: A method for optimizing the production quality of aircraft components based on data analysis, including the following steps:

[0007] Step 1: Establish an instrument monitoring module, a monitoring data calculation module, a monitoring and warning module, and a monitoring data management module for quality production;

[0008] Step 2: Divide the instrument monitoring module into a tooling inspection data unit, a component inspection data unit, a subassembly inspection data unit, and an aircraft final assembly inspection data unit;

[0009] Step 3: Divide the monitoring data calculation module into a tooling error unit, a component defect unit, a subassembly defect unit, and an aircraft final assembly defect unit, and calculate the tooling error index Hxl, the component semi-finished product defect detection index Fiy, the component finished product defect detection index Fiz, the subassembly defect non-conforming area Arj, and the aircraft final assembly completion index Net;

[0010] Step 4: The monitoring and warning module compares the obtained tooling error index Hxl, the component semi-finished product defect detection index Fiy, the component finished product defect detection index Fiz, the subassembly defect non-conforming area Arj, and the aircraft final assembly completion index Net with a preset standard numerical curve. When the above indicators are lower than the predetermined standard, the monitoring and warning module will trigger a yellow warning signal;

[0011] Step 5. The monitoring data management module optimizes the inspection equipment parameters of the tooling inspection data unit, the component inspection data unit, the component inspection data unit and the aviation final assembly inspection data unit according to the conventional indicators of the tooling error index Hxl, the semi-finished component defect detection index Fiy, the finished component defect detection index Fiz, the sub-assembly defect unqualified area Arj and the aviation final assembly completion index Net.

[0012] Preferably, the aircraft parts production quality optimization system based on data analysis includes an instrument monitoring module, a monitoring data calculation module, a monitoring early warning module and a monitoring data management module;

[0013] The instrument monitoring module includes a tooling inspection data unit, a parts inspection data unit, a sub-assembly inspection data unit and an aviation final assembly inspection data unit. The tooling inspection data unit is connected to a laser scanner via a network to obtain tooling inspection data, and after numbering, is connected to the monitoring data calculation module via a wireless network. The parts inspection data unit is connected to an ultrasonic inspection device via a network to obtain parts inspection data, and after numbering, is connected to the monitoring data calculation module via a wireless network. The sub-assembly inspection data unit is connected to a magnetic particle inspection device via a network to obtain sub-assembly inspection data, and after numbering, is connected to the monitoring data calculation module via a wireless network. The aviation final assembly inspection data unit is connected to an acoustic emission inspection device via a network to obtain aviation final assembly inspection data and number them. The instrument monitoring module is connected to the monitoring data calculation module via a wireless network.

[0014] The monitoring data calculation module includes a tooling error unit, a component defect unit, a subassembly defect unit and an aviation final assembly defect unit. The tooling error unit calculates a tooling error index Hxl according to tooling inspection data. The component defect unit calculates a component semi-finished product defect detection index Fiy and a component finished product defect detection index Fiz according to component inspection data. The subassembly defect unit calculates a component defect unqualified area Arj according to component inspection data. The aviation final assembly defect unit calculates an aviation final assembly completion index Net according to aviation final assembly inspection data. The monitoring data calculation module is connected to a monitoring and early warning module via a wireless network.

[0015] The monitoring and early warning module compares the obtained tooling error index Hxl, component semi-finished product defect detection index Fiy, component finished product defect detection index Fiz, component defect unqualified area Arj and aviation assembly completion index Net with the preset standard value curve. When the above indicators are lower than the preset standards, the monitoring and early warning module will trigger a yellow warning signal;

[0016] The monitoring data management module optimizes the detection equipment parameters of the tooling detection data unit, the component detection data unit, the sub-assembly detection data unit, and the aviation general assembly detection data unit according to the conventional indicators of the tooling error index Hxl, the semi-finished component defect detection index Fiy, the finished component defect detection index Fiz, the unqualified area Arj of the sub-assembly defect, and the aviation general assembly completion index Net.

[0017] Preferably, the tooling detection data unit numbers the center point position of the tool and the corresponding position in the theoretical model according to the tooling detection data characteristics. The center point position number of the tool is P n (x n 、y n 、z n ), and the corresponding position number in the theoretical model of the tool is P t (x t 、y t 、z t ).

[0018] Preferably, the tooling error unit calculates the tooling error index Hxl according to the tooling detection data, and its calculation formula is:

[0019]

[0020] In the formula, Hxl represents the tooling error index, P n (x n 、y n 、z n ) represents the center point position of the tool, P t (x t 、y t 、z t ) represents the corresponding position in the theoretical model of the tool, m represents the total number of measurement points, represents the Euclidean distance between each measurement point and the corresponding point on the theoretical model.

[0021] Preferably, the component detection data unit numbers the ultrasonic wavelength of the semi-finished components with a production progress of 1 / 3, the ultrasonic sound velocity of the semi-finished components with a production progress of 1 / 3, the ultrasonic wavelength of the finished components, and the ultrasonic sound velocity according to the component detection data characteristics. The ultrasonic wavelength of the semi-finished components with a production progress of 1 / 3, the ultrasonic sound velocity of the semi-finished components with a production progress of 1 / 3, the ultrasonic wavelength of the finished components, and the ultrasonic sound velocity are numbered as I t 、λ t 、I n 、λ n .

[0022] Preferably, the component defect unit calculates the component semi-finished product defect detection index Fit and the component finished product defect detection index Fiz according to the component detection data, and the calculation formula is as follows:

[0023] Fiy=I t *λ t

[0024] In the formula, Fiy represents the component semi-finished product defect detection index, and I t 、λ t respectively represent the ultrasonic wavelength and ultrasonic sound velocity of the semi-finished component with a manufacturing progress of 1 / 3;

[0025] Fiz=I n *λ n

[0026] In the formula, Fiz represents the component finished product defect detection index, and I n 、λ n respectively represent the ultrasonic wavelength and ultrasonic sound velocity of the manufactured component.

[0027] Preferably, the sub-assembly detection data unit numbers the magnetic particle size aggregation area data of the sub-assembled component according to the sub-assembly detection data characteristics, and the magnetic particle size aggregation area data number of the sub-assembled component is J n .

[0028] Preferably, the sub-assembly defect unit calculates the sub-assembly defect unqualified area Arj according to the sub-assembly detection data, and the calculation formula is as follows:

[0029]

[0030] In the formula, Arj represents the sub-assembly defect unqualified area, J n represents the magnetic particle size aggregation area, and J m represents the critical point exceeding the standard of the magnetic particle size aggregation degree.

[0031] Preferably, the aviation general assembly detection data unit numbers the aviation general assembly defect expansion rate and stress level detected by the acoustic emission equipment according to the aviation general assembly detection data characteristics, and the aviation general assembly defect expansion rate and stress level numbers detected by the acoustic emission equipment are E and T.

[0032] Preferably, the aviation general assembly defect unit calculates the aviation general assembly completion index Net according to the aviation general assembly detection data, and the calculation formula is as follows:

[0033] Net=k*E*T

[0034] In the formula, Net represents the total aircraft assembly completion index, E and T respectively represent the defect expansion rate and stress level of aircraft general assembly detected by the acoustic emission equipment, and k represents the proportionality constant.

[0035] Compared with the prior art, the present invention provides a method and system for optimizing the production quality of aircraft parts based on data analysis, and has the following beneficial effects:

[0036] 1. By calculating the tooling error index Hxl, the present invention helps to evaluate abnormal information of the tooling equipment and auxiliary tools required before manufacturing aircraft parts, provides a basis for the emergency warning signal lamp of the monitoring and warning module to light up, and at the same time adjusts the scanning accuracy or data acquisition frequency of the laser scanner in the tooling detection data unit according to the conventional information fed back by the tooling error index Hxl to ensure the capture of correct tooling error data. After the parameter adjustment, the monitoring and warning module and the monitoring data management module will continuously monitor the change of the tooling error index, and then verify the effectiveness of the laser scanner parameter adjustment through the application effect in actual production.

[0037] 2. The monitoring data management module of the present invention analyzes the defect detection index Fiy of semi-finished parts to determine the common defect types and frequencies of semi-finished parts during the production process, so as to adjust the improvement direction or carry out defect compensation measures at the 1 / 3 progress of semi-finished parts. At the same time, according to the index of the defect detection index Fiy of semi-finished parts, the frequency and sensitivity of ultrasonic detection in the parts detection data unit are optimized to improve the monitoring defect accuracy at the 1 / 3 progress of semi-finished parts.

[0038] 3. The monitoring data management module of the present invention calculates according to the defective area Arj of sub-assembly and the total aircraft assembly completion index Net to realize the dynamic monitoring of the defective positions of sub-assembly connections, which helps to feedback the excessive data to the monitoring and warning module in the first time, so that the relevant staff can repair the defects of the splicing parts or adjust the parameters of the splicing equipment used to improve the splicing process. The present invention connects the instrument monitoring module and the monitoring data management module through wireless network to coordinate the collaborative work of the assembly process and the detection equipment, ensure the continuity of the assembly work, and thus improve the overall quality and efficiency of aircraft assembly. Brief Description of the Drawings

[0039] Figure 1 It is a schematic structural diagram of the present invention;

[0040] Figure 2 It is a flowchart of the method steps of the present invention. Detailed Embodiments

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0042] Please refer to Figure 1-2 , a method for optimizing the production quality of aircraft parts based on data analysis, comprising the following steps:

[0043] Step 1: Establish an instrument monitoring module, a monitoring data calculation module, a monitoring warning module, and a monitoring data management module to perform quality production;

[0044] Step 2: Divide the instrument monitoring module into a tooling inspection data unit, a parts inspection data unit, a sub-assembly inspection data unit, and an aircraft general assembly inspection data unit;

[0045] Step 3: Divide the monitoring data calculation module into a tooling error unit, a parts defect unit, a sub-assembly defect unit, and an aircraft general assembly defect unit, and calculate the tooling error index Hxl, the parts semi-finished product defect detection index Fiy, the parts finished product defect detection index Fiz, the sub-assembly defect non-conforming area Arj, and the aircraft general assembly completion index Net;

[0046] Step 4: The monitoring warning module compares the obtained tooling error index Hxl, the parts semi-finished product defect detection index Fiy, the parts finished product defect detection index Fiz, the sub-assembly defect non-conforming area Arj, and the aircraft general assembly completion index Net with a preset standard value curve. When the above indicators are lower than the predetermined standard, the monitoring warning module will trigger a yellow warning signal;

[0047] Step 5: The monitoring data management module optimizes the detection equipment parameters of the tooling inspection data unit, the parts inspection data unit, the sub-assembly inspection data unit, and the aircraft general assembly inspection data unit according to the conventional indicators of the tooling error index Hxl, the parts semi-finished product defect detection index Fiy, the parts finished product defect detection index Fiz, the sub-assembly defect non-conforming area Arj, and the aircraft general assembly completion index Net.

[0048] A system for optimizing the production quality of aircraft parts based on data analysis, comprising an instrument monitoring module, a monitoring data calculation module, a monitoring warning module, and a monitoring data management module;

[0049] The instrument monitoring module includes a tooling inspection data unit, a parts inspection data unit, a sub-assembly inspection data unit and an aviation final assembly inspection data unit. The tooling inspection data unit is connected to a laser scanner through a network to obtain tooling inspection data, and after numbering, it is connected to the monitoring data calculation module through a wireless network. The parts inspection data unit is connected to an ultrasonic inspection device through a network to obtain parts inspection data, and after numbering, it is connected to the monitoring data calculation module through a wireless network. The sub-assembly inspection data unit is connected to a magnetic particle inspection device through a network to obtain sub-assembly inspection data, and after numbering, it is connected to the monitoring data calculation module through a wireless network. The aviation final assembly inspection data unit is connected to an acoustic emission inspection device through a network to obtain aviation final assembly inspection data and number it. The instrument monitoring module is connected to the monitoring data calculation module through a wireless network.

[0050] The monitoring data calculation module includes a tooling error unit, a component defect unit, a subassembly defect unit and an aviation final assembly defect unit. The tooling error unit calculates a tooling error index Hxl according to tooling inspection data. The component defect unit calculates a component semi-finished product defect inspection index Fiy and a component finished product defect inspection index Fiz according to component inspection data. The subassembly defect unit calculates a component defect unqualified area Arj according to component inspection data. The aviation final assembly defect unit calculates an aviation final assembly completion index Net according to aviation final assembly inspection data. The monitoring data calculation module is connected to the monitoring and early warning module via a wireless network.

[0051] The monitoring and early warning module compares the obtained tooling error index Hxl, component semi-finished product defect detection index Fiy, component finished product defect detection index Fiz, component defect unqualified area Arj and aviation assembly completion index Net with the preset standard value curve. When the above indicators are lower than the preset standards, the monitoring and early warning module will trigger a yellow warning signal;

[0052] The monitoring data management module optimizes the inspection equipment parameters of the tooling inspection data unit, the component inspection data unit, the component inspection data unit and the aviation final assembly inspection data unit according to the conventional indicators of the tooling error index Hxl, the semi-finished component defect detection index Fiy, the finished component defect detection index Fiz, the sub-assembly defect unqualified area Arj and the aviation final assembly completion index Net.

[0053] The tooling inspection data unit numbers the center point position of the tool and the corresponding position in the theoretical model according to the tooling inspection data characteristics. The center point position of the tool is numbered as P n (x n ,y n 、z n ), the corresponding position number in the theoretical model of the tool is P t (x t ,y t 、zt )。

[0054] The fixture error unit calculates the fixture error index Hxl based on the fixture inspection data, and its calculation formula is:

[0055]

[0056] In the formula, Hxl represents the fixture error index, P n (x n , y n , z n ) represents the center point position of the tool, P t (x t , y t , z t ) represents the corresponding position in the theoretical model of the tool, m represents the total number of measurement points, represents the Euclidean distance between each measurement point and the corresponding point on the theoretical model.

[0057] The advantages are as follows: By calculating the fixture error index Hxl, it helps to evaluate the abnormal information of the fixture equipment and auxiliary tools required before manufacturing aviation components, provides a basis for the emergency warning signal light of the monitoring and early warning module to light up. At the same time, according to the conventional information fed back by the fixture error index Hxl, the scanning accuracy or data acquisition frequency of the laser scanner in the fixture inspection data unit is adjusted to ensure the capture of correct fixture error data. After the parameter adjustment, the monitoring and early warning module and the monitoring data management module will continuously monitor the change of the fixture error index, and then verify the effectiveness of the laser scanner parameter adjustment through the application effect in actual production.

[0058] The component inspection data unit numbers the ultrasonic wavelength of the semi-finished components with a manufacturing progress of 1 / 3, the ultrasonic sound speed of the semi-finished components with a manufacturing progress of 1 / 3, the ultrasonic wavelength and ultrasonic sound speed of the finished components according to the characteristics of the component inspection data. The ultrasonic wavelength of the semi-finished components with a manufacturing progress of 1 / 3, the ultrasonic sound speed of the semi-finished components with a manufacturing progress of 1 / 3, the ultrasonic wavelength and ultrasonic sound speed of the finished components are numbered as I t , λ t , I n , λ n 。

[0059] The component defect unit calculates the component semi-finished product defect detection index Fiy and the component finished product defect detection index Fiz according to the component inspection data, and its calculation formula is:

[0060] Fiy = I t *λ t

[0061] In the formula, Fiy represents the component semi-finished product defect detection index, It and λ t respectively represent the ultrasonic wavelength and ultrasonic sound velocity of semi-finished parts with a production progress of 1 / 3.

[0062] The advantages are as follows: The monitoring data management module analyzes the defect detection index Fiy of semi-finished parts to determine the common defect types and frequencies during the production process of semi-finished parts, so as to adjust the improvement direction or take defect compensation measures at the 1 / 3 progress of semi-finished parts. At the same time, according to the index of the defect detection index Fiy of semi-finished parts, the frequency and sensitivity of ultrasonic detection in the component detection data unit are optimized to improve the accuracy of monitoring defects at the 1 / 3 progress of semi-finished parts.

[0063] Fiz = I n *λ n

[0064] In the formula, Fiz represents the defect detection index of finished components, and I n and λ n respectively represent the ultrasonic wavelength and ultrasonic sound velocity of the manufactured components.

[0065] The advantages are as follows: The monitoring data management module establishes a closed-loop quality management system for finished products by analyzing the feedback of the defect detection index Fiz of finished components, incorporates the feedback of the defect detection index Fiz of finished products into the quality standard control process, and continuously optimizes the parameters of manufacturing equipment to reduce the outflow rate of finished product defects.

[0066] The sub-assembly detection data unit numbers the magnetic particle grain size aggregation area data of the sub-assembled components according to the sub-assembly detection data characteristics. The magnetic particle grain size aggregation area data of the sub-assembled components is numbered as J n .

[0067] The sub-assembly defect unit calculates the sub-assembly defect non-conforming area Arj according to the sub-assembly detection data. The calculation formula is:

[0068]

[0069] In the formula, Arj represents the sub-assembly defect non-conforming area, and J n represents the magnetic particle grain size aggregation area, and J m represents the critical point exceeding the standard of magnetic particle grain size aggregation degree.

[0070] The aviation general assembly detection data unit numbers the defect propagation rate and stress level of aviation general assembly detected by the acoustic emission equipment according to the aviation general assembly detection data characteristics. The defect propagation rate and stress level of aviation general assembly detected by the acoustic emission equipment are numbered as E and T.

[0071] The aviation general assembly defect unit calculates the aviation general assembly completion index Net according to the aviation general assembly detection data. The calculation formula is:

[0072] Net = k * E * T

[0073] In the formula, Net represents the overall aircraft assembly completion index, E and T respectively represent the aircraft assembly defect expansion rate and stress level detected by the acoustic emission device, and k represents the proportionality constant.

[0074] The advantages are as follows: The monitoring data management module realizes the dynamic monitoring of the defect positions of the sub-assembly connections based on the calculation of the unqualified area Arj of the sub-assembly defects and the overall aircraft assembly completion index Net, which helps to feedback the excessive data to the monitoring and early warning module in the first time, enabling the relevant staff to repair the defects of the splicing part or adjust the parameters of the splicing equipment used to improve the splicing process. The present invention connects the instrument monitoring module and the monitoring data management module through a wireless network to coordinate the collaborative work of the assembly process and the detection equipment, ensuring the continuity of the assembly work, thereby improving the overall quality and efficiency of aircraft assembly.

[0075] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing the production quality of aircraft parts based on data analysis, characterized in that: The following steps are involved: Step 1: Establish instrument monitoring module, monitoring data calculation module, monitoring early warning module and monitoring data management module to carry out quality production; Step 2: Divide the instrument monitoring module into a tooling inspection data unit, a component inspection data unit, a sub-assembly inspection data unit, and an aviation final assembly inspection data unit; Step 3: Divide the monitoring data calculation module into tooling error unit, component defect unit, subassembly defect unit and aviation final assembly defect unit, and calculate the tooling error index Hxl, component semi-finished product defect detection index Fiy, component finished product defect detection index Fiz, subassembly defect unqualified area Arj and aviation final assembly completion index Net; Step 4: The monitoring and early warning module compares the obtained tooling error index Hxl, component semi-finished product defect detection index Fiy, component finished product defect detection index Fiz, component defect unqualified area Arj and aviation assembly completion index Net with the preset standard value curve. When the above indicators are lower than the preset standards, the monitoring and early warning module will trigger a yellow warning signal; Step 5. The monitoring data management module optimizes the inspection equipment parameters of the tooling inspection data unit, the component inspection data unit, the component inspection data unit and the aviation final assembly inspection data unit according to the conventional indicators of the tooling error index Hxl, the semi-finished component defect detection index Fiy, the finished component defect detection index Fiz, the sub-assembly defect unqualified area Arj and the aviation final assembly completion index Net.

2. Aircraft parts production quality optimization system based on data analysis, characterized by: It includes instrument monitoring module, monitoring data calculation module, monitoring early warning module and monitoring data management module; The instrument monitoring module includes a tooling inspection data unit, a parts inspection data unit, a sub-assembly inspection data unit and an aviation final assembly inspection data unit. The tooling inspection data unit is connected to a laser scanner via a network to obtain tooling inspection data, and after numbering, is connected to the monitoring data calculation module via a wireless network. The parts inspection data unit is connected to an ultrasonic inspection device via a network to obtain parts inspection data, and after numbering, is connected to the monitoring data calculation module via a wireless network. The sub-assembly inspection data unit is connected to a magnetic particle inspection device via a network to obtain sub-assembly inspection data, and after numbering, is connected to the monitoring data calculation module via a wireless network. The aviation final assembly inspection data unit is connected to an acoustic emission inspection device via a network to obtain aviation final assembly inspection data and number them. The instrument monitoring module is connected to the monitoring data calculation module via a wireless network. The monitoring data calculation module includes a tooling error unit, a component defect unit, a subassembly defect unit and an aviation final assembly defect unit. The tooling error unit calculates a tooling error index Hxl according to tooling inspection data. The component defect unit calculates a component semi-finished product defect detection index Fiy and a component finished product defect detection index Fiz according to component inspection data. The subassembly defect unit calculates a component defect unqualified area Arj according to component inspection data. The aviation final assembly defect unit calculates an aviation final assembly completion index Net according to aviation final assembly inspection data. The monitoring data calculation module is connected to a monitoring and early warning module via a wireless network. The monitoring and early warning module compares the obtained tooling error index Hxl, component semi-finished product defect detection index Fiy, component finished product defect detection index Fiz, component defect unqualified area Arj and aviation assembly completion index Net with the preset standard value curve. When the above indicators are lower than the preset standards, the monitoring and early warning module will trigger a yellow warning signal; The monitoring data management module optimizes the detection equipment parameters of the tooling inspection data unit, the component inspection data unit, the component inspection data unit and the aviation final assembly inspection data unit according to the conventional indicators of the tooling error index Hxl, the semi-finished component defect detection index Fiy, the finished component defect detection index Fiz, the sub-assembly defect unqualified area Arj and the aviation final assembly completion index Net.

3. The aircraft parts production quality optimization system based on data analysis according to claim 2, characterized in that: The tool detection data unit numbers the center point position of the tool and the corresponding position in the theoretical model according to the tool detection data characteristics. The center point position of the tool is numbered P n (x n ,y n 、z n ), the corresponding position number in the theoretical model of the tool is P t (x t ,y t 、z t ).

4. The aircraft parts production quality optimization system based on data analysis according to claim 3 is characterized by: The tooling error unit calculates the tooling error index Hxl according to the tooling detection data, and the calculation formula is: In the formula, Hxl represents the tooling error index, P n (x n ,y n 、z n ) represents the center point of the tool, P t (x t ,y t 、z t ) represents the corresponding position in the theoretical model of the tool, m represents the total number of measurement points, Represents the Euclidean distance between each measured point and the corresponding point on the theoretical model.

5. The aircraft parts production quality optimization system based on data analysis according to claim 1, characterized in that: The component detection data unit numbers the ultrasonic length of the semi-finished component with a manufacturing progress of 1 / 3, the ultrasonic sound velocity of the semi-finished component with a manufacturing progress of 1 / 3, and the ultrasonic length and ultrasonic sound velocity of the manufactured component according to the component detection data characteristics, and the ultrasonic length of the semi-finished component with a manufacturing progress of 1 / 3, the ultrasonic sound velocity of the semi-finished component with a manufacturing progress of 1 / 3, and the ultrasonic length and ultrasonic sound velocity of the manufactured component are numbered I t , t ,I n , n .

6. The aircraft parts production quality optimization system based on data analysis according to claim 5, characterized in that: The component defect unit calculates the component semi-finished product defect detection index Fiy and the component finished product defect detection index Fiz according to the component detection data, and the calculation formula is: Girl=I t *λ t In the formula, Fiy represents the defect detection index of semi-finished parts, I t , t They represent the ultrasonic length and ultrasonic speed of the semi-finished parts with a manufacturing progress of 1 / 3 respectively; Fiz=I n *l n In the formula, Fiz represents the defect detection index of finished parts, I n , n They respectively represent the ultrasonic length and ultrasonic speed of the manufactured parts.

7. The aircraft parts production quality optimization system based on data analysis according to claim 1, characterized in that: The assembly inspection data unit numbers the magnetic powder particle size gathering area data of the assembled component according to the assembly inspection data characteristics, and the magnetic powder particle size gathering area data of the assembled component is numbered J. n .

8. The aircraft parts production quality optimization system based on data analysis according to claim 7 is characterized by: The assembly defect unit calculates the assembly defect unqualified area Arj according to the assembly inspection data, and the calculation formula is: In the formula, Arj represents the unqualified area of ​​component defects, J n Indicates the magnetic powder particle size aggregation area, J m Indicates the critical point where the magnetic powder particle size aggregation exceeds the standard.

9. The aircraft parts production quality optimization system based on data analysis according to claim 1, characterized in that: The aviation assembly inspection data unit numbers the aviation assembly defect growth rate and stress level detected by the acoustic emission equipment according to the aviation assembly inspection data characteristics, and the aviation assembly defect growth rate and stress level detected by the acoustic emission equipment are numbered E and T.

10. The aircraft parts production quality optimization system based on data analysis according to claim 9, characterized in that: The aviation assembly defect unit calculates the aviation assembly completion index Net based on the aviation assembly inspection data, and the calculation formula is: Net=k*E*T In the formula, Net represents the aviation assembly completion index, E and T represent the aviation assembly defect expansion rate and stress level detected by acoustic emission equipment, respectively, and k represents the proportional constant.

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