<p style="text-align: justify;">This paper analyzes the influence of basic turning parameters on&nbsp; vibrations and surface quality of titanium alloy Ti-6Al-4V. Due to specific mechanical properties, titanium processing often causes resonance, instability and increased roughness. The experiment was performed on a universal lathe, with varying cutting speed, feed and depth of cut, in order to&nbsp;<br />test different machining regimes. Vibration and roughness measurements confirmed that the best results are achieved by avoiding operating modes that cause resonance, thus reducing vibrations and improving surface quality. The obtained findings show that for a stable and precise machining process it is important to carefully select parameters and monitor vibrations in real time. In this way, the service life of the tool can be extended and a better quality of the finished product&nbsp;<br />can be achieved.</p>

<p>This paper focuses on the optimization of process parameters in band&nbsp; sawing of thick-walled cylindrical components made of G-X55CrNiSiS19-13-2 steel. The applied methodology is based on the integrated MOORATaguchi approach, utilizing the Taguchi L16 orthogonal array with three controlled factors: cutting speed, feed rate, and tool engagement length.&nbsp;<br />Measurable process parameters, particularly torque and power on the saw drive motor, were continuously monitored, while other indicators were indirectly determined using analytical methods. The results of the analysis of variance (ANOVA) indicate that all examined parameters have a significant influence on the overall process performance, as determined by&nbsp;<br />the application of the MOORA method.&nbsp;</p>

<p style="text-align: justify;">In the given example of Taguchi's experiment, an investigation was&nbsp; conducted into the influence of factors on the assembly speed of the tool for precise bolt tightening. Unnecessary loss of time can be detrimental to production processes; therefore, it is crucial to promptly identify all negative factors that affect time. Taguchi's experiment was carried out according to the orthogonal array L16(215). Recommendations for optimal assembly conditions were provided.</p>

<p style="text-align: justify;">In order to optimize the process parameters of face milling, an experiment&nbsp; was carried out in which three machining parameters were selected as&nbsp; input variables &ndash; spindle speed, axial depth of cut, and feed rate. Each&nbsp; parameter was varied at four levels, considering both rough and finish&nbsp; machining. The milling process was performed on a HURCO CNC&nbsp;<br />machine, using a solid carbide end mill with four cutting edges. The&nbsp; experiment was conducted using the Taguchi orthogonal array L16 (4^3).&nbsp; The output responses of the process are the surface roughness (Ra) and the material removal rate (MRR). Process parameter optimization was carried out using the multi-criteria optimization method - Grey Relational&nbsp;<br />Analysis (GRA), while the statistical significance of the parameters was&nbsp; examined by using ANOVA. The research established that the optimal values of MRR and Ra are obtained through the combination of the physical values of the input parameters: n = 6000 rpm, a = 2 mm, and f = 800 mm/min.&nbsp;</p>

<p style="text-align: justify;">An overview of previous research provides a fundamental understanding of the current state of the process of cutting styrofoam on a CNC cutter, identifying gaps and the need for further research. Identification of important parameters, such as wire cutting speed, density of the styrofoam and current intensity, provide the basis for planning the experiment. The research methodology is described in detail, including the selection of<br />factors, levels, and design of experiment (Box-Behnken design). The analysis of the data obtained by the experiment is focused on the output sizes 𝑦𝑦1 (external measure) and 𝑦𝑦2 (internal measure), with an emphasis on statistical analysis using Minitab and Microsoft Excel software. Through a comprehensive review, the paper aims to contribute to the understanding and optimization of the process of cutting styrofoam on a CNC cutter,<br />providing insights into the influence of parameters on the quality of cutting.</p>

<p style="text-align: justify;">There are many ways to accomplish optimization of machining process. In the experimental part of this paper, the optimization of machining process is accomplished from the aspect of cutting conditions, which are independent variables (speed, feed, and cutting depth), whereas the dependent variables refer to the surface roughness, more precisely, arithmetic average of surface heights and resultant cutting force, including<br />main cutting force, feed force and thrust force. Once the matrix of the experimental plan has been created, on the basis of a complete multifactor plan with eight points, with previously determined upper, middle and lower levels of cutting parameters for turning, the experiment followed. Once the results of surface roughness were measured by perthometer, as well as results of cutting forces by dynamometer, the optimization of<br />machining process was treated by means of predetermined methodologies,<br />described in this paper.</p>

In this paper, the influence of four factors on the forces during cutting, especially on the friction force was investigated. These factors are water quantity in MQL, speed, depth, and feed rate. In this study, the optimization of those factors to find their optimal combination for obtaining minimal intensity friction force has been looked into. The null hypothesis is that by using the MQL technique, the friction force can be significantly reduced. The experiment was planned using Taguchis L9 design of experiments. The study included performing the machining of the workpiece through different combinations of levels for the spindle speed, feed rate, amount of water, and depth of cut as the main parameters.

The paper presents one aspect of the analysis of energy consumption and productivity of the manufacturing operation. As an example of the operation, the operation of turning with a single-blade tool was taken. Sustainable development in its general concept implies sustainable materials, sustainable design, and sustainable manufacturing. This paper presents an analysis of one important part of sustainable manufacturing, and that is energy saving. The experimental study was conducted as follows. In laboratory conditions, an experimental-mathematical regression model of the relationship between cutting force and processing conditions was defined. Machining experiments were performed under ECO-friendly conditions with technology known as MQCL (Minimum Quantity Cooling Lubrication) machining. The obtained mathematical model was used to calculate the energy consumption and the workpiece material removal rate (MRR, productivity). The results of the analysis showed that there is a lot of space for optimization of machining conditions from the aspect of power consumption, with mandatory calculation and other machining costs, above all, the cost of tools and machine tools. In this regard, recommendations for analysis with the aim of power saving are given.

In the recent years, 3D printing has become a topic of great interest from both academic and the industrial sector through the increasing importance of Industry 4.0. This technology is based on layer-by-layer melting of materials to create a three-dimensional object. It is also known as additive production, and it is feasible through several different methods such as stereolithography, selective laser melting and sintering (SLM, SLS), these are just some of the examples, but fused decomposition modeling (FDM) has become the most interesting technique.This paper seeks to analyze the fracture strength (torque) of coupled gears made out of PLA plastic produced by the 3D printing process. To reduce the number of experimental measurements, the Taguchi L8(27) orthogonal array was used to analyze the influence of factors on two level. Investigated factors were: wall thickness, infill and number of infill lines, layer height, temperature, cooling and speed. Finally, optimization of most influential factors according to maximum torque was preformed, using Taguchi method too.