Additive manufacturing, particularly Directed Energy Deposition, is revolutionizing the way high-performance metal components are produced. Unlike traditional subtractive methods, where material is removed from a solid block, AM uses an additive process to build objects layer by layer. This offers several advantages, such as reduced waste, faster production times, and the ability to create complex geometries. DED, a popular form of metal AM, uses a focused energy source, typically a laser, to melt metal powders which are then deposited directly onto a substrate. The ability to tailor the material properties and shapes through this process makes DED especially valuable for industries requiring parts with excellent mechanical performance, such as aerospace, defense, and energy.
In this study, the focus is on optimizing the DED process using a hybrid blend of two distinct metal powders—nickel-based superalloy IN 718 and stainless steel SS316L. Each material has unique properties that make them desirable for specific applications. IN 718 is known for its excellent high-temperature strength and corrosion resistance, which is ideal for components exposed to extreme conditions, such as in jet engines or gas turbines. On the other hand, SS316L is widely used for its superior corrosion resistance and weldability, making it an essential material in industries like chemicals, food processing, and medical devices. However, when used alone, both materials have certain limitations in processing and performance. By combining these materials, the study aims to overcome those challenges and achieve better mechanical properties suited to demanding applications.
The study specifically explores three different mixing ratios of these materials: 25% SS316L and 75% IN 718, 50% of each, and 75% SS316L with 25% IN 718. The goal is to determine how varying the proportions of these materials affects key mechanical properties, such as tensile strength, elongation, and resistance to wear and corrosion. The research methodology involves a systematic approach using Taguchi-grey relational analysis, which combines two powerful optimization techniques. The Taguchi method is used to select the best process parameters, while grey relational analysis helps in adjusting the importance of factors based on their contribution to the desired outcome. This combined approach ensures that multiple quality objectives, such as cladding efficiency, deposition rate, and porosity, are simultaneously optimized.
Key parameters in the DED process that affect the quality of the final product include laser power, overlap ratio, powder feed rate, and scanning speed. These factors directly influence the cladding efficiency, deposition rate, and porosity of the deposited material, all of which are crucial for the performance and durability of the part. In this study, the Taguchi method helped narrow down the optimal parameter combinations for each of the three material blends. Afterward, grey relational analysis fine-tuned these parameters to ensure that the final products exhibited the best possible mechanical properties.
The results showed interesting trends across the different material ratios. The blend with 25% SS316L and 75% IN 718 exhibited the highest ultimate tensile strength of 499.37 MPa, making it the strongest of the three mixtures. Meanwhile, the 50% SS316L and 50% IN 718 mixture demonstrated the best elongation at 13.53%, indicating superior ductility. These findings highlight the impact that material composition can have on the final mechanical properties of parts produced through DED. Furthermore, the optimization of process parameters allowed for better control over factors such as porosity, which is a common challenge in AM processes and can negatively affect the structural integrity of parts.
To ensure the repeatability and reliability of the optimized parameters, verification experiments were conducted. These experiments confirmed that the optimized process settings yielded consistent results, demonstrating the effectiveness of the combined Taguchi-grey relational approach. Additional fine-tuning through one-factor-at-a-time experiments allowed for further refinement of the process, resulting in improved overall quality and performance of the parts.
The potential applications of this study are significant, particularly in industries that require high-performance materials capable of withstanding extreme conditions. By improving the mechanical properties of hybrid metal powders, this research contributes to the growing body of knowledge on AM and its potential for producing customized, high-quality components. The ability to fine-tune material properties through a DED process will be especially beneficial for sectors like aerospace, where both strength and temperature resistance are critical for the longevity and safety of components.
Looking forward, the findings of this study can lead to the development of more cost-effective, high-performance components for industries like aerospace and gas turbines. The hybrid blend of IN 718 and SS316L could reduce the need for expensive repairs and replacements of critical parts, making maintenance and operations more economical. This research, therefore, not only advances the field of additive manufacturing but also has practical implications for reducing costs and improving performance in industries where durability is paramount.
By providing a comprehensive analysis of the hybrid manufacturing process, this study offers valuable insights for the continued advancement of DED technology. The results contribute to a deeper understanding of how material compositions and process parameters can be optimized for specific performance outcomes, setting the stage for further innovations in metal additive manufacturing.
