Introduction. Modern technologies of tool and mold production increasingly use metal-composite systems (MCS), which combine additively manufactured metal shells and metal-polymer fillers. This corresponds to priority areas of scientific and technological progress, such as digitalization and additive manufacturing (in accordance with the Federal Project “Development of Materials and Production Technologies” within the framework of the national program “Scientific and Technological Development”). The scope of application of MCS in industry is growing: according to industry reviews, their share in the production of high-precision components for the aerospace and automotive industries has increased by 25–30% over the past five years, providing economic benefits due to a 15–20% reduction in the weight of structures and improvement of the energy efficiency of processes. Such systems combine the strength and thermal conductivity of metal with the damping properties of polymers, yet exhibit high sensitivity to overheating during machining. Consequently, the temperature at the metal–MCPM (metal-polymer composite material) interface during turning may exceed the thermal stability threshold (170 °C), resulting in thermal degradation, loss of adhesion, and shell deformation. In the literature, the problem of MCS thermal stability in turning is addressed only fragmentarily: existing studies focus on monolithic composites or general heat‑transfer models, lacking detailed analysis of interfacial heating in additively manufactured systems featuring low‑conductivity fillers. Therefore, research is needed to quantify the thermal response during the machining of such systems and to determine the cutting parameters that provide their thermal stability. The objective of this work is to experimentally study the temperature response during turning of MCS with a shell thickness of δ = 3.5 mm and to construct a second-order regression model linking the temperature at the metal – MPCM interface with the cutting parameters.

Materials and Methods. A hardware-software measurement unit simulating the MCS structure was developed for the study. It included a replaceable bushing made of 12Kh18N10T steel, an internal insert made of Ferro-Chromium metal-polymer, three built-in type K thermocouples, and a data acquisition module based on an ESP32-WROOM microcontroller with MAX6675 converters, providing temperature recording at 5 Hz and data transmission via Wi-Fi. The accuracy of the measurements was confirmed by thermal imaging verification using FLUKE Ti400. The experiment was conducted according to the full factorial design (FFD) 2³ + n0, in which cutting speed V, feed S and cutting depth t were varied. Data processing was performed by the least-squares method with adequacy validation using Fisher's F-test and coefficient significance by Student's t-test. Based on the results of processing in real physical units, a second-order regression model was constructed — model 3.5TP, designed for engineering prediction.

Results. The analysis of the experimental data showed that the thermal response of the metal–composite system was nonlinear. The depth of cut t was the dominant factor increasing the temperature, whereas within the investigated range, an increase in the feed rate S and cutting speed V led to a decrease in the interface temperature due to a shorter thermal exposure time and more intensive heat removal with the chip flow. The resulting 3.5TP model was characterized by the coefficient of determination R² = 0.9513, Fisher criterion value F = 364.31 and the significance level p < 10⁻⁵, which validated its adequacy. Interpretation of the regression coefficients indicated that the depth of cut (t) had the strongest impact on the temperature rise, the feed rate (S) showed a moderate effect, and the cutting speed (V) had the least sensitivity within the investigated range. The constructed response surfaces and contour maps identified the “safe zones” of cutting conditions that satisfied the constraint T ≤ 170°C, corresponding to the thermal stability limit of the metal–polymer filler. The average deviation between the experimental and calculated data did not exceed 7 °C, that confirmed the high accuracy and predictive capability of the proposed model.

Discussion. The constructed 3.5TP model revealed the relationship between geometric and technology factors that determine the thermal load of the MCS during turning. The dominant impact of the depth of processing was due to the increase in the volume of the cut layer and heat generation in the contact zone, while the increase in feed and cutting speed was accompanied by compensating effects due to a decrease in the time of thermal contact and more intense heat removal with the chips. The results obtained indicated the need to optimize processing modes taking into account the shell thickness δ. Directions for further research were identified.

Conclusion. The conducted study demonstrates that the developed experimental setup reproduces accurately the thermal behavior of a metal–composite system composed of an additively manufactured metal shell and a metal–polymer filler. The constructed 3.5TP regression model adequately describes the temperature response during turning and can be used for engineering prediction of mechanical processing modes.