The optimum machining conditions recommended in the literature for one of the most commonly used materials for responsible heavy-duty workpieces in mechanical engineering, 42CrMo4+QT steel, are valid only for certain cutting tools and machine tools. This paper presents the results of an investigation of the machinability of this type of steel on the criteria of cutting tool lifetime and roughness of machined surfaces in turning on CNC machines with robotic power supply. A planned experiment has been carried out as a result of which theoretical and experimental models have been obtained and graphical dependencies, reflecting the influence of cutting speed and feed when working with replaceable carbide inserts from different manufacturers have been constructed. The dependencies allow to predict with sufficient accuracy the tool lifetime of the studied inserts and the roughness of the machined surfaces using cutting conditions in a certain range. The analysis carried out shows that the machinability of 42CrMo4+QT steel depends on the elements of the cutting conditions, with the widest variation in the values of the cutting tool lifetime criterion. The cutting speed has a stronger influence on this criterion. The optimum cutting conditions that guarantee maximum tool lifetimes of the studied inserts and minimum roughness of the machined surfaces ware determined.

The wear resistance of diamond dressing rolls depends on the manufacturing technology used and the characteristics of the working diamond layer, such as the type and grain size of the diamond grains, the type of bond, and the concentration and distribution of the diamonds. To optimise the lifetime of diamond rolls made of synthetic diamonds using the electroplating method, this paper proposes an innovative approach to compacting the intergranular spaces by treating them with diamond grains finer than the main fraction. To implement this approach, analytical dependencies were derived for the distance between the diamond grains. Intensive wear of the diamond roller bond was observed when the distance was exceeded as a result of contact with the abrasive grains of the grinding wheel. A ratio between the grain sizes of the main and additional diamond fractions is also recommended. Diamond roller dressers made of synthetic diamonds with a medium or high strength and a mixed grit size were created and their wear resistance was studied during the uni-directional and counter-directional dressing of electrocorundum grinding wheels using the plunge-grinding method. Theoretical and experimental models were constructed to predict the lifetime and the wear of diamond rolls in relation to the radial feed rate, the dressing speed ratio, the dress-out time, and the grit size ratio. Multi-objective optimisation based on a genetic algorithm was used to determine the optimal dressing conditions, ensuring the best combination of the maximum lifetime and minimum wear of the diamond rolls. The results obtained confirm the validity and correctness of the proposed approach for increasing the wear resistance of diamond roller dressers.

The quality of ground surfaces depends largely on the topography of the active surface of the grinding wheel, which, in turn, is determined both by the structure of the grinding wheel and by the conditions of the dressing process. This article proposes a new approach to improving the quality of ground surfaces by optimizing the dressing conditions with diamond rollers, based on the correlation between the roughness of the ground surfaces, the roughness of the cutting surface of the grinding wheel, and the parameters of the dressing process. A comprehensive theoretical–experimental study and modeling of the microgeometry of electrocorundum grinding wheels and the roughness of ground surfaces, depending on the dressing conditions with diamond dressing rolls made of medium- and high-strength synthetic diamonds with a mixed grit size, has been carried out. A complex quality indicator has been defined, determined as the ratio between the roughness of the ground surfaces and the roughness of the cutting surface of the grinding wheels, and models have been constructed for its determination, depending on the dressing conditions. By applying a genetic algorithm, optimal conditions for uni-directional and counter-directional dressing (dressing speed ratio, radial feed rate, the dress-out time and the ratio between the grit sizes of the diamond roller dresser and grinding wheel) have been determined, which ensure a minimum value of the complex quality indicator in combination with minimum roughness of the ground surfaces.

The objective of the grinding process is to obtain a better surface finish (roughness, accuracy, etc.) or a high material removal rate of the workpiece. These grinding process response variables depend largely on both the grinding conditions and the topography of the grinding wheels formed during dressing. In this regard, the paper focuses on determining the optimal dressing conditions for grinding wheels dressed with diamond roller dressers during rough and finish grinding. A new multi-objective optimization approach for determining dressing conditions has been proposed, which leads to Pareto-optimal solutions for increasing the grinding process production rate, reducing roughness, and increasing the accuracy of ground surfaces. To demonstrate the performance of this approach, one process of dressing electrocorundum grinding wheels with novel diamond rollers made of medium- and high-strength synthetic diamonds with mixed grain sizes has been selected. Empirical models have been developed to examine the production rate of the grinding process, the roughness of the ground surfaces, and the accuracy of the machined parts. Multi-objective optimization based on a genetic algorithm has been performed by applying two methods: determining an optimal compromise area for the dressing process conditions, and the weighted utility function method. The novelty of the implementation is due to the process of identifying the precise optimal dressing parameters specifically for the investigated mixed-grit diamond rollers. The optimization results show that rough grinding requires uni-directional dressing with a diamond roller AC32 at a feed rate of 1.4 mm/min, a dressing speed ratio of 0.8, a dress-out time of 1.0 s, and a grit size ratio of 2.56, ensuring a production rate of 875 mm³/min, a surface roughness Ra up to 1.25 µm, and a cylindricity deviation up to 12.5 µm. For fine grinding, optimal counter-directional dressing parameters include a feed rate of 0.26 mm/min, a speed ratio of 0.23, a dress-out time of 5.0 s, and a grit size ratio of 2.2, which guarantee a minimum surface roughness Ra of 0.38 µm, a cylindricity deviation of 8.1 µm, and a production rate of at least 600 mm³/min.

This article presents the results of a comprehensive study of the performance of zirconia-toughened and mixed-alumina ceramic tools in CNC turning of 42CrMo4 steel with hardnesses of 35, 40, and 45 HRC. Empirical models have been developed for the cutting tool lifetime and the surface roughness of the machined surfaces as a function of cutting speed and hardness of the machined material. Through multi-objective compromise optimization via two approaches (the optimal compromise region and the generalized arithmetic mean utility function with weighting coefficients) and the application of a genetic algorithm, the optimal conditions for performing the CNC turning process were determined when using tools made of different mineral ceramics for steel with varying hardness. These conditions provide a tool lifetime exceeding 8 min and a high machined surface quality with a roughness below 1.7 µm.

The optimum turning conditions for 42CrMo4 hardened steel, defined and recommended in the literature, are valid only for certain cutting tools and machine tools. In this paper, an attempt has been made to optimize the cutting parameters for CNC turning with robotic power supply of the machine tool by using a new type of CVD coated replaceable carbide insert as cutting tool. To determine the optimal cutting conditions such as cutting speed, feed and depth of cut, a multi-objective optimization, based on a genetic algorithm, was conducted. The generalized arithmetic mean utility function with weighting coefficients has been chosen as the optimization parameter, which is a complex index characterizing the cutting tool lifetime and production rate in turning. The optimization problem has been solved in the following sequence: 1) a model of the generalized utility function was created, reflecting the complex influence of the turning process parameters; 2) the optimal cutting conditions were determined, under which the generalized utility function has a maximum; 3) Pareto optimal solutions were found, which guarantee the best combination between tool lifetime and production rate in turning.