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This study aims to reveal the influences of three-dimensional (3D) printing parameters such as layer heights (0.1 mm, 0.2 mm and 0.4 mm), infill rates (40, 70 and 100%) and geometrical property as tapered angle (0, 0.25 and 0.50) on vibrational behavior of 3D-printed polyethylene terephthalate glycol (PET-G) tapered beams with fused filament fabrication (FFF) method.

In this performance, all test specimens were modeled in AutoCAD 2020 software and then 3D-printed by FFF. The effects of printing parameters on the natural frequencies of 3D-printed PET-G beams with different tapered angles were also analyzed experimentally, and numerically (finite element analysis) via Ansys APDL 16 program. In addition to vibrational properties, tensile strength, elasticity modulus, hardness, and surface roughness of the 3D-printed PET-G parts were examined.

It can be stated that average surface roughness values ranged between 1.63 and 6.91 µm. In addition, the highest and lowest hardness values were found as 68.6 and 58.4 Shore D. Tensile strength and elasticity modulus increased with the increase of infill rate and decrease of the layer height. In conclusion, natural frequency of the 3D-printed PET-G beams went up with higher infill rate values though no critical change was observed for layer height and a change in tapered angle fluctuated the natural frequency values significantly.

The influence of printing parameters on the vibrational properties of 3D-printed PET-G beams with different tapered angles was carried out and the determination of these effects is quite important. On the other hand, with the addition of glass or carbon fiber reinforcements to the PET-G filaments, the material and vibrational properties of the parts can be examined in future works.

As a result of this study, it was shown that natural frequencies of the 3D-printed tapered beams from PET-G material can be predicted via finite element analysis after obtaining material data with the help of mechanical/physical tests. In addition, the outcome of this study can be used as a reference during the design of parts that are subjected to vibration such as turbine blades, drone arms, propellers, orthopedic implants, scaffolds and gears.

It is believed that determination of the effect of the most used 3D printing parameters (layer height and infill rate) and geometrical property of tapered angle on natural frequencies of the 3D-printed parts will be very useful for researchers and engineers; especially when the importance of resonance is known well.

When the literature efforts are scanned in depth, it can be seen that there are many studies about mechanical or wear properties of the 3D-printed parts. However, this is the first study which focuses on the influences of the both 3D printing parameters and tapered angles on the vibrational behaviors of the tapered PET-G beams produced with material extrusion based FFF method. In addition, obtained experimental results were also supported with the performed finite element analysis.

This study aims to elucidate the machining properties of low-cost expanded clay-reinforced syntactic foams by using different neural network models for the first time in the literature. The main goal of this endeavor is to create a casting machining-neural network modeling flow-line for real-time foam manufacturing in the industry.

Samples were manufactured via an industry-based die-casting technology. For the slot milling tests performed with different cutting speeds, depth of cut and lubrication conditions, a 3-axis computer numerical control (CNC) machine was used and the force data were collected through a digital dynamometer. These signals were used as input parameters in neural network modelings.

Among the algorithms, the scaled-conjugated-gradient (SCG) methodology was the weakest average results, whereas the Levenberg–Marquard (LM) approach was highly successful in foreseeing the cutting forces. As for the input variables, an increase in the depth of cut entailed the cutting forces, and this circumstance was more obvious at the higher cutting speeds.

The effect of milling parameters on the cutting forces of low-cost clay-filled metallic syntactics was examined, and the correct detection of these impacts is considerably prominent in this paper. On the other side, tool life and wear analyses can be studied in future investigations.

It was indicated that the milling forces of the clay-added AA7075 syntactic foams, depending on the cutting parameters, can be anticipated through artificial neural network modeling.

It is hoped that analyzing the influence of the cutting parameters using neural network models on the slot milling forces of metallic syntactic foams (MSFs) will be notably useful for research and development (R&D) researchers and design engineers.

This work is the first investigation that focuses on the estimation of slot milling forces of the expanded clay-added AA7075 syntactic foams by using different artificial neural network modeling approaches.