Optimization strategies for robotic additive and subtractive manufacturing of large and high thin-walled aluminum structures

Abstract

Wire and arc additive manufacturing (WAAM) based on gas metal arc welding (GMAW) is a potential technology for fabricating large-scale metallic structures due to its high deposition rate, high energy efficiency, and low cost. It can produce near net-shape components by depositing metallic material layer by layer using a welding process. This paper presents a robotic additive and subtractive manufacturing system. In manufacturing large and high thin-walled structures, a critical issue is the unevenness of the layers. The accumulation of layers with poor flatness leads to significant differences in the heights of different positions in a layer, making it unable to continue the multi-layer material depositing process. The objective of this research is to investigate optimization strategies for manufacturing large and high thin-walled metallic structures with the robotic additive and subtractive manufacturing system. Three optimization strategies are proposed to obtain flat layers, including deposition with weaving, arc igniting and arc extinguishing control, and local measuring and milling strategy. Experiments were designed to explore the effect of these strategies. The experimental results show that the combination of these strategies can improve the surface flatness of layers, reducing the differences in the heights of a layer. Using these strategies, a large and high thin-walled component is manufactured, demonstrating the potential for fabricating large metallic parts in a very short time by the robotic additive and subtractive manufacturing system. Besides, regression models were generated for establishing the relationship between process parameters and bead geometry in deposition with weaving.

Appendices

Appendix A: Robotic measuring

According to Eq. 8, when the process parameters are set, it is applicable to calculate the theoretical bead height h for a single layer. Then, for a certain layer (layer n), the theoretical height can be described as Eq. 9.

$$ \text{heigh}{t_{t}}(n) = n \cdot h $$

(9)

A laser displacement sensor is used to measure the height of the thin-walled structure. As shown in Fig. 22, suppose the distance between a measuring point and the bottom of the sensor is d, then calculate the measuring result Δd (obtained from the controller of the sensor) as Eq. 10

$$ {\Delta} d = d - {d_{0}} $$

(10)

where d₀ is a constant value (20 mm). As shown in Fig. 23, before the deposition of the first layer, the laser displacement sensor is placed above the baseplate. When the measuring result is zero, the distance between the baseplate and the bottom of the sensor is d₀, and we obtain the Z value of the measuring tool point of the robot, z₀. After depositing n layers, we set the Z value of the measuring tool point to be z₀ + height_t(n) and move the sensor in plane above the thin wall. Then, the measuring results are the errors between the actual and theoretical heights. The actual height at a sampling point of a deposited layer, height_a, can be obtained as Eq. 11

$$ \text{heigh}{t_{a}} = \text{heigh}{t_{t}}(n) - {\Delta} d $$

(11)

where Δd is the measured result at a sampling point.

Fig. 22

Distance measuring using laser displacement sensor

Fig. 23

Height measuring

Appendix B: Experimental data

Tables 7 and 8 show all the width and height of experimental beads with different parameters. Serial numbers used as test data to verify predictable accuracy of the regression models are as follows. {2, 8, 15, 16, 19, 21, 22, 24, 28, 29, 31, 32, 33, 34, 36, 38, 39, 41, 43, 50, 51, 53, 65, 68, 84, 86, 87, 109, 111, 112, 113, 117, 120, 124, 125, 127, 130, 131, 145, 146, 147, 151, 152, 157, 158, 159, 161, 168}.

Table 7 Weights and heights of deposited beads with different parameters— part 1

Table 8 Weights and heights of deposited beads with different parameters - part 2