Wire and arc-based additive manufacturing (WAAM) is a rapidly developing technology which employs a welding arc to melt metal wire for additive manufacturing purposes. During WAAM of thin-walled structures, as the wall height increases, the heat dissipation to the substrate is slowed down gradually and so is the solidification of the molten pool, leading to variation of the bead geometry. Though gradually reducing the heat input via adjusting the process parameters can alleviate this issue, as suggested by previous studies, it relies on experience to a large extent and inevitably sacrifices the deposition rate because the wire feed rate is directly coupled with the heat input. This study introduces for the first time an in-process active cooling system based on thermoelectric cooling technology into WAAM, which aims to eliminate the difference in heat dissipation between upper and lower layers. The case study shows that, with the aid of thermoelectric cooling, the bead width error is reduced by 56.8%, the total fabrication time is reduced by 60.9%, and the average grain size is refined by 25%. The proposed technique provides new insight into bead geometry regulation during WAAM with various benefits in terms of geometric accuracy, productivity, and microstructure.

This paper proposes a hybrid WAAM (wire arc additive manufacturing) and milling process (HWMP), and highlights its application in the fabrication of stiffened panels that have wide applications in aviation, aerospace, and automotive industries, etc. due to their light weight and strong load-bearing capability. In contrast to existing joining or machining methods, HWMP only deposits stiffeners layer-by-layer onto an existing thin plate, followed by minor milling of the irregular surfaces, which provides the possibility to significantly improve material utilization and efficiency without any loss of surface quality. In this paper, the key performances of HWMP in terms of surface quality, material utilization and efficiency are evaluated systematically, which are the results of the comprehensive effects of the deposition parameters (e.g., travel speed, wire-feed rate) and the milling parameters (e.g., spindle speed, tool-feed rate). In order to maximize its performances, the optimization is also performed to find the best combination of the deposition and the milling parameters. The case study shows that HWMP with the optimal process parameters improves the material utilization by 57% and the efficiency by 32% compared against the traditional machining method. Thus, HWMP is believed to be a more environmental friendly and sustainable method for the fabrication of stiffened panels or other similar structures.

The development of artificial intelligence (AI)-based industrial data-driven models is the driving force behind the digital transformation of manufacturing processes and the application of smart manufacturing. However, in real-world industrial applications, the intricate interplay among data quality, model accuracy, and generalizability poses significant challenges, hindering the effective deployment and scalability of data-driven models in complex manufacturing environments. To address this challenge, this paper proposes a universal Physics-informed Hybrid Optimization framework for Efficient Neural Intelligence (PHOENIX) in manufacturing, demonstrating its applicability in robotic welding scenarios. This framework systematically integrates physical principles into its input, model structure, and dynamic optimization processes, enabling proactive, real-time detection and predictive of welding instability. It achieves an accuracy of up to 98% for predictions within the next 50 ms and maintains an accuracy of 86% even for forecasts up to 1 s in advance. Through physics-informed data-driven modeling, the framework significantly reduces the dependence on high-cost data while maintaining the performance of the original model. By leveraging cloud-based optimization modules that integrate new data with historical experience, the framework enables autonomous model parameter optimization, ensuring its continuous adaptation to the complex and dynamic demands of industrial scenarios.

Transparent hard and brittle (THB) materials have generated significant interest due to their excellent properties, such as wide spectral transmittance, heat resistance, chemical inactivity and high mechanical strength. To further explore the application of THB materials, it is inevitable to be confronted with a range of joining THB materials and THB material–metals. Ultrafast (UF) laser microwelding enables a new means of joining THB materials and THB material–metals, due to a localized energy deposition method, which is dominated by nonlinear absorption. This process can realize high-quality micro-zone direct joining of THB materials or THB material–metals without the assistance of a light-absorbing intermediate layer. In this paper, we review the advances in UF laser microwelding of THB materials and THB material–metals considering the last two decades, from the analysis of the interaction mechanism between UF laser and matter to the key influencing factors and practical applications of this technology. Finally, the existing problems and the future research focus of UF laser microwelding technology of THB materials and THB material–metals are discussed.

Distortion induced by non-uniform thermal gradients is one of the major constraints in wire and arc additive manufacturing. A novel flexible multi-point support fixture (FMSF) featured by reconfigured working surface and controllable restraining force is developed as an in-process distortion control technique. FMSF allows the distortion to be suppressed by adjusting the restraining force imposed onto the substrate dynamically as the number of layers increases. Both simulations and experiments are conducted to verify its effectiveness and compare it with other common restraint forms including clamping and pre-springing. The multi-layer deposition results show that a reduction of 96.3% in angular distortion and 86.5% in longitudinal bending distortion are obtained with FMSF, which exhibits great superiority over clamping and pre-springing.