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.

This paper presents an investigation into the MQL turning process of X5CrNi18-10 stainless steel with the objective of screening and selecting the most important MQL parameters on machinability of austenitic stainless steel. Effects of selected MQL parameters such as flow rate of vegetable-based oil (10 and 50 ml/h) and tap water (300 and 1700 ml/h), nozzle direction relative to cutting tool (rake and flank face), spray distance (30 and 50 mm), number of applied nozzles (1 and 2) and cutting oil type in means of its physical properties (39 and 95 mm 2 /s) were studied. In order to analyze the effect of MQL parameters on the quality characteristics of surface roughness and cutting forces, the cutting parameters including cutting speed, feed rate and depth of cut were kept constant for all experiments. A standard two level Taguchi orthogonal array L16 (2 6 ) was employed to select the most influential parameters. Results indicated that the most important parameters for simultaneous reducing of surface roughness and cutting forces were oil and water flow rate followed by the spray distance.

In this paper recent state of art and application of minimum quantity lubrication (MQL) in machining processes is presented. Machining with the MQL system presents huge potential for sustainability of global manufacturing industry. Companies are constrained by different legal frameworks and regulations and they are forced to use new techniques for cooling, flushing and lubrication to be economically, socially and environmentally friendly. Because of this, it is interesting for scientists and manufacturers to adopt new technologies to improve the quality of the finished product and to increase the tool life with the least impact on all sustainability segments of machining process. This can be achieved by employing alternative techniques of cooling like MQL system as a substitute for traditional emulsion flood cooling.

For investigation of a process parameter effect for a given set of factor values in this paper grey relational analysis is used. In order to find multi-parametric optimization of arithmetical mean deviation of the assessed profile as the surface roughness characteristic and for the material removal rate, the grey relational analysis is implemented. The analysis combined with Taguchi methods and based on the L9 orthogonal array experimental design was used. Obtaining the insight into the characteristics of the process, even with a smaller number of experimental runs by utilization of these methods is allowed. In terms of the machining process and material, the face milling for pure aluminium is performed. The machining of the workpiece through the different combination of settings for the spindle speed, feed and depth of cutting, as the main parameters, was performed

This paper aims to present and compare the damage identification results of two methods proposed by the authors for beam-like structures. Both methods use the same numerical and regression models as well as the experimentally obtained values of the beam bending frequencies. The difference between these methods lies in the final stage of their usage. The first method relies on finding three closest intersection points of frequency curves and the second method is based on finding a minimum value of the proposed frequency related functional. The results of damage identification for 28 damage scenarios using the proposed methods are presented and compared in this paper. The comparison showed that the accuracy of both methods is almost the same and depends mostly on the input data quality.