Fused deposition modeling (FDM) is widely applied in various fields due to its affordability and ease of use. However, it faces challenges such as achieving high surface quality, precise dimensional tolerance, and overcoming anisotropic mechanical properties. This review analyzes and compares the machinability of 3D-printed PLA, PETG, and carbon-fiber-reinforced PETG, focusing on surface roughness and burr formation. A Design of Experiments (DoE) with a full-factorial design was used, considering three factors: rotation speed, feed rate, and depth of cut. Each factor had different levels: rotational speed at 3000, 5500, and 8000 rpm; feed rate at 400, 600, and 800 mm/min; and depth of cut at 0.2, 0.4, 0.6, and 0.8 mm. Machinability was evaluated by roughness and burr height using a profilometer for all the materials under the same milling conditions. To evaluate the statistical significance of the influence of various processing parameters on surface roughness and burr formation in 3D-printed components made of three different materials—PLA, PETG, and carbon-fiber-reinforced PETG—an analysis of variance (ANOVA) test was conducted. This analysis investigated whether variations in rotational speed, feed rate, and depth of cut resulted in measurable and significant differences in machinability results. Results showed that milling parameters significantly affect roughness and burr formation, with optimal conditions for minimizing any misalignment highlighting the trade-offs in parameter selection. These results provide insights into the post-processing of FDM-printed materials with milling, indicating the need for a balanced approach to parameter selection based on application-specific requirements.

Fused Deposition Modeling (FDM) has evolved from a rapid prototyping technique to an established manufacturing process for various industrial applications, including aerospace, robotics, biomedical engineering, and food production. Despite its versatility, the surface quality and dimensional accuracy of FDM-printed parts remain significant challenges, limiting their applicability in high-performance and precision-driven industries. Some of the primary limitations of FDM are volumetric error, shape deviation, and surface roughness, which directly affect the mechanical properties and functional performance of printed components. Post-processing techniques are available to mitigate these problems. Among the available post-processing techniques, CNC machining has emerged as a viable solution for improving the surface finish and dimensional precision of FDM parts. The integration of subtractive CNC machining with additive FDM printing enables the development of hybrid manufacturing strategies, leveraging the design freedom of 3D printing while ensuring superior surface quality. This paper presents a comprehensive review of recent studies on CNC post-processing of FDM-printed parts, analyzing its impact on surface roughness, dimensional accuracy, and material properties. Additionally, key process parameters influencing the effectiveness of CNC machining are discussed.

Very sensitive structural health monitoring methods are needed to detect barely visible impact damage in composite materials. Based on extracting non-linear modulated components from the frequency response of the damaged system, vibro-acoustic modulation (VAM) has shown to be effective in identifying the presence of damage at its early stage. A decisive role in the success of this technique is played by the choice of the high-frequency probe and the low-frequency pump sinusoidal signals that simultaneously excites the system. This study explores how the position of the sensing transducer, with respect to the modal shape of the pump excitation, may influence the sensitivity of the VAM technique for impact damage detection in composite laminates. This aspect has been scarcely investigated in previous research works, as other studies have focused more on the role of the probe frequency. Here, VAM tests were performed on a composite beam by using a frequency-swept pump vibration simultaneously with a high frequency probe excitation. The results of the experimental tests indicate that the VAM technique is capable of clearly revealing the presence of impact damage only when the sensor is placed on appropriate locations, which are directly related to the shape of the deformation activated by the applied excitation. These results suggest the adoption of low frequency excitations that activate multiple modal shapes to improve the effectiveness and reliability of VAM approaches.

To detect the presence of damage, many structural health monitoring techniques exploit the nonlinear features that typically affect the otherwise linear dynamic response of structural components with internal defects. One of them is the Scaling Subtraction Method (SSM), which evaluates nonlinear features of the response to a high-amplitude harmonic excitation by subtracting a scaled reference signal. Originally tested on granular materials, the SSM was shown to be effective for composite materials as well. However, the dependence of the technique efficiency on the testing frequency, usually selected among the natural frequencies of the system, may limit its application in practice. This paper investigates the feasibility of applying the SSM through a broadband impulsive excitation, which would avoid the need of a preliminary modal analysis and address the issue of the proper selection of the excitation frequency. A laminated composite beam was tested in intact and damaged conditions under both scaled harmonic excitations of different frequency and broadband impulsive signals of scaled amplitude. Two damage indicators working on the frequency domain were introduced. The results showed a good sensitivity of the SSM to the presence and level of impact damage in composite beams when applied through a broadband impulsive excitation.

Fused deposition modeling (FDM) is widely applied in various fields due to its affordability and ease of use. However, it faces challenges such as achieving high surface quality, precise dimensional tolerance and overcoming anisotropic mechanical properties. This paper analyzes and compare the machinability of 3D printed PLA, PETG and carbon fiber reinforced PETG focusing on surface roughness and burr formation. A design of experiments (DoE) with a full factorial design was used, considering three factors: rotation speed, feed rate and depth of cut. Each factor had different levels: rotational speed at 3000, 5500 and 8000 rpm; feed rate at 400, 600 and 800 mm/min; and depth of cut at 0.2, 0.4, 0.6, and 0.8 mm. Machinability was evaluated by roughness and burr height using a profilometer for all the materials under the same milling conditions. To evaluate the statistical significance of the influence of various processing parameters on surface roughness and burr formation in 3D printed components made of three different materials PLA, PETG and carbon fiber reinforced PETG, an analysis of variance (ANOVA) test was conducted. This analysis investigated whether variations in rotational speed, feed rate and depth of cut resulted in measurable and significant differences in machinability results. Results showed that milling parameters significantly affect roughness and burr formation, with optimal conditions for minimizing any misalignment highlighting the trade-offs in parameter selection. These results provide insights into the post-processing of FDM-printed materials with milling, indicating the need for a balanced approach to parameter selection based on application-specific requirements.