In modern aircraft manufacturing, automated drilling technologies are crucial for enhancing assembly efficiency and quality. However, due to structural constraints and limited workspace, the rate of fully automated drilling across entire aircraft remains low. Current automation is primarily applied to open areas such as wing surfaces and external sections, while regions like bottom areas, narrow spaces, and other inaccessible scenarios still rely heavily on manual drilling. Manual drilling demands high skill from workers, leading to issues such as intense labor, delivery pressure, and quality risks for high-value products. These challenges highlight the urgent need to improve automation levels, particularly in confined spaces where large robotic systems cannot operate. To address this, we have developed a compact end effector designed for aircraft assembly drilling, which can be mounted on product tooling to enable automated drilling through human-machine collaboration. This end effector features a lightweight and compact design, facilitating easy deployment in restricted areas. By integrating an embedded control system, it provides visual guidance for normal alignment and allows one-click drilling and countersinking. In this article, we present the design scheme of the compact end effector, detail the design and verification of key parameters, implement the selection of critical components, and validate the precision and stability through drilling experiments. The results demonstrate that our design meets operational requirements, achieving automated drilling in aircraft assembly through human-machine cooperation.
The compact end effector is strategically planned to integrate multiple functional modules into a cohesive unit. It consists of a drilling execution unit, a normal guidance and alignment module, a human-operated handle, control buttons, and an interactive interface. The drilling execution unit includes a pneumatic spindle, a feed cylinder, a countersink depth control module, a chip removal pipeline, and a base mount. This end effector combines normal detection and automatic chip removal capabilities, enabling integrated drilling and countersinking in a single operation. The normal guidance module comprises a normal sensor, an embedded control system, and a display screen. The embedded system reads data from the normal sensor, calculates real-time deviations in the end effector’s orientation, and presents this information graphically on the interface. Operators can adjust the end effector’s posture based on visual cues, ensuring alignment within specified tolerances before drilling. This digital approach eliminates reliance on operator experience, enhancing accuracy and consistency. Process parameters are stored in the embedded system, allowing for automated execution once alignment is confirmed. The end effector simplifies operations, improves efficiency, and boosts automation in aviation assembly through seamless human-machine interaction.
To ensure robust performance, the key functional modules of the end effector were meticulously designed and verified. The drilling execution module utilizes a pneumatic spindle with a power rating of 1.8 kW and a maximum torque of 2.2 N·m. For drilling a 6 mm diameter hole in 7075 aluminum alloy (hardness 150 HB) using a carbide tool, we computed axial forces, cutting torque, cutting speed, and power consumption across different motor speeds and feed rates. The calculations are based on standard machining formulas, where axial force \( F_a \) and cutting torque \( T_c \) are derived from material properties and tool geometry. For instance, the axial force can be estimated using:
$$ F_a = K_f \cdot d \cdot f^{0.8} $$
where \( K_f \) is a material-specific constant, \( d \) is the drill diameter, and \( f \) is the feed rate. Similarly, cutting torque is given by:
$$ T_c = C_t \cdot d^{2} \cdot f^{0.8} $$
with \( C_t \) as a torque coefficient. The results for various combinations are summarized in Table 1, which aids in selecting appropriate parameters to meet drilling demands.
| Motor Speed (rpm) | Cylinder Feed Rate (mm/min) | Axial Force (N) | Cutting Torque (N·m) | Cutting Speed (m/min) | Cutting Power (kW) |
|---|---|---|---|---|---|
| 3000 | 300 | 584.82 | 0.72 | 211.22 | 0.84 |
| 3000 | 500 | 759.13 | 1.09 | 181.10 | 1.09 |
| 5000 | 300 | 347.74 | 0.41 | 260.04 | 0.59 |
| 5000 | 500 | 508.55 | 0.62 | 223.36 | 0.77 |
The normal alignment method employs a multi-point sensing technique to determine surface orientation. From a micro-geometric perspective, any point \( M(x, y, z) \) on a spatial surface \( \Sigma \) has a neighboring micro-surface \( \Delta \Sigma \) that approximates a plane \( \Delta S \). Thus, the normal direction at \( M \) can be represented by that of \( \Delta S \). Sensors are arranged at coordinates \( (x_1, y_1, z_1) \), \( (x_2, y_2, z_2) \), \( (x_3, y_3, z_3) \), and \( (x_4, y_4, z_4) \) on the measurement plane. Vectors are formed between sensor pairs:
$$ \mathbf{s}_1\mathbf{s}_2 = (x_2 – x_1, y_2 – y_1, z_2 – z_1) $$
$$ \mathbf{s}_1\mathbf{s}_3 = (x_3 – x_1, y_3 – y_1, z_3 – z_1) $$
$$ \mathbf{s}_2\mathbf{s}_4 = (x_4 – x_2, y_4 – y_2, z_4 – z_2) $$
$$ \mathbf{s}_3\mathbf{s}_4 = (x_4 – x_3, y_4 – y_3, z_4 – z_3) $$
The normal vector \( \mathbf{v} \) of the workpiece surface is computed as the average of two cross products:
$$ \mathbf{v} = \frac{\mathbf{v}_1 + \mathbf{v}_2}{2} $$
where
$$ \mathbf{v}_1 = \mathbf{s}_1\mathbf{s}_3 \times \mathbf{s}_1\mathbf{s}_2 $$
$$ \mathbf{v}_2 = \mathbf{s}_2\mathbf{s}_4 \times \mathbf{s}_3\mathbf{s}_4 $$
If \( \mathbf{v} = (a, b, c) \), and the tool spindle’s normal vector is \( (1, 0, 0) \), rotations around the Z and Y axes by angles \( \alpha \) and \( \beta \) are required to align them. This is expressed by the rotation matrix equation:
$$ \begin{bmatrix} a \\ b \\ c \end{bmatrix} = R_Y(\beta) R_Z(\alpha) \begin{bmatrix} 1 \\ 0 \\ 0 \end{bmatrix} $$
Here, \( R_Z(\alpha) \) and \( R_Y(\beta) \) are standard 3D rotation matrices. The deviations \( \alpha \) and \( \beta \) are graphically displayed on the screen, with the Z-axis representing \( \alpha \) and the Y-axis representing \( \beta \). Operators adjust the end effector until the dot on the screen centers within tolerance zones, ensuring precise normal alignment. This visual feedback mechanism enhances accuracy and simplifies the process for users.
Experimental validation was conducted by mounting the compact end effector on tooling and drilling holes in a 5 mm thick test piece made of 2A12-T4 aluminum alloy. The drilling parameters are listed in Table 2, which includes speeds, feeds, and clamping forces optimized for quality output.
| Parameter Name | Value |
|---|---|
| Drilling Speed (rpm) | 4000 |
| Linear Speed (m/min) | 53 |
| Clamping Force (N) | 200 |
| Countersinking Speed (rpm) | 2000 |
| Feed Rate (mm/min) | 250 |
After drilling, 30 holes were numbered and measured for diameter, normal deviation, and countersink depth using a coordinate measuring machine and a depth gauge. To minimize errors, depth measurements were taken twice per hole. The data, presented in Table 3, show that the maximum normal deviation is 0.2601 mm, and the countersink depth variation is 0.022 mm, both within acceptable limits for assembly standards.
| Sequence Number | Hole Diameter (mm) | Normal Deviation (mm) | Countersink Depth (mm) – First | Countersink Depth (mm) – Second |
|---|---|---|---|---|
| 1 | 5.9342 | 0.1202 | 1.721 | 1.723 |
| 2 | 5.9415 | 0.1155 | 1.716 | 1.716 |
| 3 | 5.9488 | 0.1587 | 1.710 | 1.708 |
| 4 | 5.9509 | 0.2174 | 1.704 | 1.707 |
| 5 | 5.9306 | 0.2017 | 1.717 | 1.716 |
| 6 | 5.9421 | 0.0558 | 1.721 | 1.723 |
| 7 | 5.9381 | 0.2480 | 1.731 | 1.729 |
| 8 | 5.9255 | 0.0915 | 1.719 | 1.717 |
| 9 | 5.9234 | 0.0751 | 1.715 | 1.715 |
| 10 | 5.9286 | 0.1014 | 1.717 | 1.715 |
| 11 | 5.9378 | 0.2331 | 1.727 | 1.724 |
| 12 | 5.9228 | 0.0603 | 1.708 | 1.708 |
| 13 | 5.9339 | 0.1143 | 1.714 | 1.711 |
| 14 | 5.9191 | 0.0463 | 1.710 | 1.708 |
| 15 | 5.9281 | 0.1649 | 1.715 | 1.711 |
| 16 | 5.9260 | 0.0809 | 1.714 | 1.712 |
| 17 | 5.9457 | 0.0860 | 1.718 | 1.714 |
| 18 | 5.9263 | 0.0339 | 1.718 | 1.716 |
| 19 | 5.9268 | 0.0679 | 1.717 | 1.713 |
| 20 | 5.9242 | 0.1231 | 1.712 | 1.710 |
| 21 | 5.9185 | 0.1903 | 1.709 | 1.705 |
| 22 | 5.9102 | 0.0264 | 1.717 | 1.709 |
| 23 | 5.9174 | 0.1946 | 1.714 | 1.709 |
| 24 | 5.9210 | 0.2181 | 1.712 | 1.714 |
| 25 | 5.9211 | 0.1811 | 1.728 | 1.724 |
| 26 | 5.9197 | 0.0317 | 1.719 | 1.715 |
| 27 | 5.9230 | 0.0281 | 1.711 | 1.707 |
| 28 | 5.9253 | 0.0984 | 1.712 | 1.708 |
| 29 | 5.9262 | 0.1128 | 1.716 | 1.712 |
| 30 | 5.9389 | 0.2601 | 1.723 | 1.725 |
In conclusion, our compact end effector demonstrates significant advantages in aircraft assembly drilling. By retrofitting existing tooling and mounting the end effector onto it, we enable position adjustments via gear racks, facilitating human-machine collaborative drilling without occupying additional space. This approach is particularly suitable for confined areas like wing sections. The lightweight design of the end effector ensures precision in hole diameter and countersink depth, while the digital normal alignment guidance provides stable, high-accuracy orientation independent of operator skill. Experimental results confirm that the drilling quality and stability meet production requirements, making this end effector a viable solution for broader application in aircraft manufacturing. Future work may focus on optimizing the end effector for diverse materials and complex curvatures, further enhancing its versatility in automated assembly environments.