## 2 Materials and Methods
This ensured that the results were not influenced by changes in tool condition, allowing for a consistent evaluation of machining performance under varying process parameters. To evaluate the machinability of PLA-CF components manufactured by FFF, real-time measurements (on-line monitoring) were taken of three key process values: temperature in the cutting zone, cutting forces, and electrical energy consumption (Figure 1), to characterize the thermal, mechanical, and energetic responses of the material throughout the machining process. The measurement of cutting temperature was carried out using a FLIR A305 sc infrared thermal imaging camera, positioned to ensure a clear view of the tool-workpiece interface. The emissivity of the carbon fiber-reinforced PLA material was determined in accordance with the UNE-EN ISO 4288:1998 standard [44], which provides guidelines for assessing surface characteristics relevant to infrared thermography. This calibration step provided a value of 0.95 for the PLA-CF emissivity. The thermographic data were processed using FLIR ResearchIR software (Version 4.40.11.35), which enabled frame-by-frame analysis and extracted the cutting zone temperature. The cutting forces were measured with a Kistler 9257B piezoelectric dynamometer, obtaining the value of three orthogonal force components: _Fx_ (passive forces), _Fy_ (cutting  
Figure 1: On-line monitoring variables for the machining analysis. forces), and _Fz_ (feed forces). These forces were recorded continuously throughout the machining cycle to evaluate the mechanical load on both the tool and the workpiece. The DynoWare software (Version 2.6.5.16) was used to record and visualize the force data. From the collected data, average force values were considered for each cutting parameter combination for a cutting length of 150 mm. The electrical energy consumption during the turning process was evaluated to determine the influence of the cutting parameters on the machining. This parameter complements the machinability assessment by providing information on the energy efficiency and sustainability of the process. The measurement process was performed with a Fluke 1732 network analyzer, which was connected to the power supply of the machining system, obtaining the electrical power (_P_) and the energy consumption per second (_E_). Data acquisition was analyzed using the Fluke Energy Analyze Plus software (Version 3.11.2). Once the machining process had been carried out, an off-line evaluation was conducted to assess the geometrical quality of the machined parts and a chip morphology analysis (Figure 2). A representative sample of the chip was collected to carry out the morphological analysis. Care was taken during collection to avoid altering the shape or surface characteristics of the chip, ensuring that the sample reflected the cutting process conditions. The morphological analysis was performed using a ZEISS Stereo Optical Microscope (SOM) (Carl Zeiss AG, Oberkochen, Germany) equipped with an AxioCam digital camera. This image process enabled a qualitative assessment of chip formation and helped identify the effects of different cutting parameters on chip morphology. The visual information obtained supported the interpretation of the machinability of PLA-CF and complemented the analysis of cutting forces and surface finish. The geometry analysis was structured into three levels: Dimensional Accuracy Assessment, Macrogeometric Deviation Evaluation, and Microgeometric Deviation Characterization. These levels are used to evaluate the impact of the turning operation on the  
Figure 2: Off-line monitoring variables for the machining analysis. final geometry of FFF-manufactured parts. In addition, the chip observation allows for completing the machinability analysis carried out in the on-line monitoring results. To evaluate the dimensional accuracy of the machined PLA-CF specimens, a series of measurements were made with a digital micrometer (0-25 mm, resolution 0.001 mm).