Prediction of Cutting Material Durability by T = f(vc) Dependence for Turning Processes

Zajac, Jozef; Duplák, Ján; Dupláková, Darina; Cizmar, Peter; Olexa, Igor; Bittner, Anton

doi:10.3390/pr8070789

Cited by 9 publications

(11 citation statements)

References 32 publications

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“…Attempts to anticipate the durability of cutting tools exist and are mentioned in the literature [32][33][34]. Thus, both Zajak et al [32] and Panda et al [33] determined, through multiple experiments and the statistical processing of experimental data, the The presence of iron cyanamide was also noted, and the proportion of iron sulfides (FeS + FeS 2 ) reached 10%. Because the chemical interaction between components has a short duration, the matrix hardness was not diminished (61 HRC-Figure 8b).…”

Section: The Performances Of Cutting Tools-removable Plates-made Of T1 Sulfonitrocarburized Hss In Powdered Solid Medium Containing Carbamentioning

confidence: 99%

“…Plates-Made of T1 Sulfonitrocarburized HSS in Powdered Solid Medium Containing Carbamide, as Compared to the Same Plates Subjected to Other Types of Thermochemical Treatments-Nitrocarburized, Gas Nitrided, Ion Nitrided Attempts to anticipate the durability of cutting tools exist and are mentioned in the literature [32][33][34]. Thus, both Zajak et al [32] and Panda et al [33] determined, through multiple experiments and the statistical processing of experimental data, the mathematical expressions of the correlations between tool durability (T) and cutting speed (Va), using obtained useful information related to the optimal processing speed.…”

Section: The Performances Of Cutting Tools-removablementioning

confidence: 99%

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Sulfonitrocarburizing of High-Speed Steel Cutting Tools: Kinetics and Performances

et al. 2021

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The scholarly literature records information related to the performance increase of the cutting tools covered by the superficial layers formed “in situ” when applying thermochemical processing. In this context, information is frequently reported on the carbamide role in processes aiming carbon and nitrogen surface saturation. Sulfur, together with these elements adsorbed and diffused in the cutting tools superficial layers, undoubtedly ensures an increase of their operating sustainability. The present paper discusses the process of sulfonitrocarburizing in pulverulent solid media of high-speed tools steel (AISI T1, HS18-0-1) and its consequences. The peculiarity of the considered process is that the source of nitrogen and carbon is mainly carbamide (CON2H4), which is found in solid powdery mixtures together with components that do not lead to cyan complex formation (non-toxic media), and the sulfur source is native sulfur. The kinetics of the sulfonitrocarburizing process, depending on the carbamide proportion in the powdered solid mixture and the processing temperature, was studied. The consequences of the achieved sulfonitrocarburized layers on the cutting tools’ performance are expressed by the maximum permissible cutting speed and the maximum cut length. An interesting aspect is highlighted, namely the possibility of using chemically active mixtures. Their components, by initiation of the metallothermic reduction reaction, become able to provide both elements of interest and the amount of heat needed for the ultrafast saturation of the targeted metal surfaces.

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Section: The Performances Of Cutting Tools-removable Plates-made Of T1 Sulfonitrocarburized Hss In Powdered Solid Medium Containing Carbamentioning

confidence: 99%

Section: The Performances Of Cutting Tools-removablementioning

confidence: 99%

Sulfonitrocarburizing of High-Speed Steel Cutting Tools: Kinetics and Performances

et al. 2021

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“…On the other hand, Aslantas et al [57] obtained empirical relations between cutting speed, feed rate, depth of cut and surface roughness parameters using the RSM for the micro-turning process in a Ti6Al4V alloy and Su et al [58] employed a multi-objective optimization method based on grey relational analysis and RSM along with Taguchi method for analyzing surface roughness and MRR in turning of an AISI 304 austenitic stainless steel. Regression analysis is also used by Zajac et al [59] to make predictions of cutting tool durability in turning processes. Furthermore, in the research study from Torres et al [60] the manufacturing of TiB 2 by using EDM was analyzed by using RSM.…”

Section: State Of the Artmentioning

confidence: 99%

A Proposal of an Adaptive Neuro-Fuzzy Inference System for Modeling Experimental Data in Manufacturing Engineering

Pérez

2020

Mathematics

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In Manufacturing Engineering there is a need to be able to model the behavior of technological variables versus input parameters in order to predict their behavior in advance, so that it is possible to determine the levels of variation that lead to optimal values of the response variables to be obtained. In recent years, it has been a common practice to rely on regression techniques to carry out the above-mentioned task. However, such models are sometimes not accurate enough to predict the behavior of these response variables, especially when they have significant non-linearities. In this present study a comparative analysis between the precision of different techniques based on conventional regression and soft computing is initially carried out. Specifically, regression techniques, based on the response surface model, as well as the use of artificial neural networks and fuzzy inference systems along with adaptive neuro-fuzzy inference systems will be employed to predict the behavior of the aforementioned technological variables. It will be shown that when there are difficulties in predicting the response parameters by using regression models, soft computing models are highly effective, being much more efficient than conventional regression models. In addition, a new method is proposed in this study that consists of using an iterative process to obtain a fuzzy inference system from a design of experiments and then using an adaptive neuro-fuzzy inference system for tuning the constants of the membership functions. As will be shown, with this method it is possible to obtain improved results in the validation metrics. The means of selecting the membership functions to develop this model from the design of experiments is discussed in this present study in order to obtain an initial solution, which will be then tuned by using an adaptive neuro-fuzzy inference system, to predict the behavior of the response variables. Moreover, the obtained results will also be compared.

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“…The machine tool control system has strict protective measures to ensure personal and equipment safety. It is also suitable for large cutting capacity, high efficiency, and large-scale processing of parts in mechanical industries such as automobiles, ships, bearings, and military sectors [7].…”

Section: Introductionmentioning

confidence: 99%

An Algorithm for Optimizing the Process Parameters of the Spindle Process of Universal CNC Machine Tools Based on the Most Probable Explanation of Bayesian Networks

Zhang,

Liu,

Wang

et al. 2023

Processes

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As an essential component of a universal CNC machine tool, the spindle plays a critical role in determining the accuracy of machining parts. The three cutting process parameters (cutting speed, feed speed, and cutting depth) are the most important optimization input parameters for studying process optimization. Better processing quality is often achieved through their optimization. Therefore, it is necessary to study the three cutting process parameters of the CNC machine tool spindle. In this paper, we proposed an improved algorithm incorporated with the beetle antennae search algorithm for the most probable explanation in Bayesian networks to achieve optimization calculation of process parameters. This work focuses on building adaptive dynamic step parameters to improve detection behavior. The chaotic strategy is discretized and used to establish the dominant initial population during the population initialization. This article uses four standard network data sets to compare the time and fitness values based on the improved algorithm. The experimental results show that the proposed algorithm is superior in time and accuracy compared to similar algorithms. At the same time, an optimization example for the actual machining of a universal CNC machine tool spindle was provided. Through the optimization of this algorithm, the true machining quality was improved.

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Prediction of Cutting Material Durability by T = f(vc) Dependence for Turning Processes

Cited by 9 publications

References 32 publications

Sulfonitrocarburizing of High-Speed Steel Cutting Tools: Kinetics and Performances

Sulfonitrocarburizing of High-Speed Steel Cutting Tools: Kinetics and Performances

A Proposal of an Adaptive Neuro-Fuzzy Inference System for Modeling Experimental Data in Manufacturing Engineering

An Algorithm for Optimizing the Process Parameters of the Spindle Process of Universal CNC Machine Tools Based on the Most Probable Explanation of Bayesian Networks

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