Cold spray additive manufacturing (CSAM) is a cutting-edge high-speed additive manufacturing process enabling the production of high-strength components without relying on traditional high-temperature methods. Unlike other techniques, CSAM produces oxide-free deposits and preserves the feedstock’s original characteristics without adversely affecting the substrate. This makes it ideal for industries requiring materials that maintain structural integrity. This paper explores strategies for improving material quality, focusing on nozzle design, particle size distribution, and fine-tuning of process parameters such as gas pressure, temperature, and spray distance. These factors are key to achieving efficient deposition and optimal bonding, which enhance the mechanical properties of the final products. Challenges in CSAM, including porosity control and achieving uniform coating thickness, are discussed, with solutions offered through the advancements in machine learning (ML). ML algorithms analyze extensive data to predict optimal process parameters, allowing for more precise control, reduced trial-and-error, and improved material usage. Advances in material strength, such as enhanced tensile strength and corrosion resistance, are also highlighted, making CSAM applicable to sectors like aerospace, defense, and automotive. The ability to produce high-performance, durable components positions CSAM as a promising additive-manufacturing technology. By addressing these innovations, this study offers insights into optimizing CSAM processes, guiding future research and industrial applications toward more efficient and high-performing manufacturing systems.

CSAM is a solid-state process for depositing metal or metal-based composite materials in which the fine particles of metal or composite material are accelerated to supersonic velocity, making successful bonding feasible due to the high-impact velocity and heavy plastic deformation, all without the melting of the feedstock material. This review examines the basic CSAM mechanism, including deposition dynamics, bonding mechanism, dynamic recrystallization, residual stress evolution, and post-spray heat treatments which affect microstructural and mechanical properties. Although controlled by a few key factors like particle velocity, strain rate, and temperature rise, the bonding efficiency itself refines the grains through dynamic recrystallization, hence improving coating strength and performance. The predominating compressive residual stresses that enhance fatigue resistance and mitigation strategies to improve coating durability by post-spray annealing and laser peening are discussed. This review, by providing an overview of material behavior, optimization techniques, and advanced modeling approaches, underlines the CSAM potential for high-performance applications in aerospace, biomedical industries, and machinery. It further underlines its importance for the advancement of manufacturing innovation and materials science.