A new way of identifying, predicting and regulating residual stress after chip-forming machining

Valíček, Ján; Czán, Andrej; Harničárová, Marta; Šajgalík, Michal; Kušnerová, Milena; Czánová, Tatiana; Kopal, Ivan; Vagaská, Alena; Kmec, Ján; Šafář, Marek

doi:10.1016/j.ijmecsci.2019.03.007

Cited by 23 publications

(13 citation statements)

References 24 publications

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“…These relate not only to the instantaneous state and changes in the physical-mechanical parameters of the material being machined but also to the condition and changes of the machine tool and the entire technology. The way of dealing with these items is described in detail and is available in granted patents and publications [21][22][23][24][25][26].…”

Section: The Results Achievedmentioning

confidence: 99%

“…The design model methodology allows them to be tracked along the length of the beam and throughout the load process in connection with the spatio-temporal development of the distribution of the parameters of all the others, in the process of reshaping the involved functions, as shown in more detail below. Complex derivation of Equations (2)-(37) for machining is done in our patented works [24,26] and publications [21][22][23]25].…”

Section: Derivation Of the Equations For Cutting Parameters Predictionmentioning

confidence: 99%

“…The present equation Ra mp = f (R mp , E xpNO ) is sufficient to satisfy this requirement. If we know the integral quantity of roughness, we can derive other main topographical functions according to the previously derived equations of equilibrium [21][22][23][24][25][26] and we can calculate with them further. Further, the Y ret value preferably serves to calculate the tangential forces and the stress for the adhesion control.…”

Section: The Ratio Of Machining Parameters Rmpmentioning

confidence: 99%

“…The structure and texture of the surface after machining is sufficiently discretely expressed by equations (Ra, Y ret , a p ) = f (R mp , E xpNO ). For sufficiently discreetly expressed grain size D gr of the coating material was derived [21][22][23][24][25][26] the equation of Equation (35) for different materials. Discrete distribution of particle size distribution by discrete cutting parameters can be determined by D gr = f (R mp , E xpNO ).…”

Section: The Ratio Of Machining Parameters Rmpmentioning

confidence: 99%

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Prediction of Cutting Parameters of HVOF-Sprayed Stellite 6

et al. 2020

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In this research, the authors set out to propose a new method of predicting and adjusting the main cutting parameters of chip machining, namely spraying on the substrate. In the experiments, a total of 28 turning cuts on a Stellite 6 coating layer were realized. The base materials of the Stellite 6 layers were EN S235JRG1 and carbide WC-Co. This work aimed to find out and optimize the influence of different combinations of cutting parameters. Due to the coating solution, the work is focused on the evaluation of the roughness Ra (μm) of the turned substrate, the grain size Dgr (μm) of the spraying, the normal stress σrz (MPa), the residual stress σrez (MPa), the specific cutting force Fc (N), the quality of adhesion to the substrate Adhmp (MPa) and other parameters. For the sake of a comprehensive solution to the problem, several new predictive equations and subsequent suggestions for solutions have been derived from this research topic based on the newly obtained experimental results. The proposed models and procedures make it possible to get new results and insights into coating technologies.

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Section: The Results Achievedmentioning

confidence: 99%

Section: Derivation Of the Equations For Cutting Parameters Predictionmentioning

confidence: 99%

Section: The Ratio Of Machining Parameters Rmpmentioning

confidence: 99%

Section: The Ratio Of Machining Parameters Rmpmentioning

confidence: 99%

See 2 more Smart Citations

Prediction of Cutting Parameters of HVOF-Sprayed Stellite 6

et al. 2020

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“…The research work of the authors [17][18][19][20][21] in the area of AWJ cutting is focused on three aspects: AWJ cutting tool geometry, mechanics of the cutting process, and material properties. The main result of their work was that they found a method for identification of a position of equilibrium/neutral plane in the cut produced by AWJ, and based on it, they determined the constant of material cuttability for abrasive water jet cutting technology [22,23].…”

Section: Introductionmentioning

confidence: 99%

The Predictive Model of Surface Texture Generated by Abrasive Water Jet for Austenitic Steels

et al. 2020

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Austenitic stainless steel belongs to the best oxidation-resistant alloys, which must function effectively and reliably when used in a corrosion environment. Their attractive combination of properties ensures their stable position in the steel industry. They belong to a group of difficult-to-cut materials, and the abrasive water jet cutting technology is often used for their processing. Samples made of stainless steel AISI 304 has been used as the experimental material. Data generated during experiments were used to study the effects of AWJ process parameters (high-pressure water volume flow rate, the diameter of the abrasive nozzle, the distance of the nozzle from the material surface, cutting head feed rate, abrasive mass flow, and material thickness) on surface roughness. Based on the analysis and interpretation of all data, a prediction model was created. The main goal of the long-term research was to create the simplest and most usable prediction model for the group of austenitic steels, based on the evaluation of the practical results obtained in the company Watting Ltd. (Budovateľská 3598/38, Prešov, Slovakia) during 20 years of operation and cooperation with customers from industrial practice. Based on specific customer requirements from practice, the publication also contains specific recommendations for practice and a proposal for the classification of the predicted cut quality.

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Reverse reconstruction of surface topography from residual stress after chip‐forming machining of the material

Valíček

Harničárová

Kušnerová

et al. 2020

Materialwissenschaft Werkst

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Residual stress is induced in the sample of a material stressed by external forces (tension, pressure, thermal stress, etc.) from the beginning of the stress. An instantaneous level is a function of the intensity of the external deformation work, the time and speed of the deformation, and the degree of immediate surface and volume deformation. It is proportional to the individual deformation limits, i. e., the elastic limit, yield point, flexural strength and breach limit; the maximum is reached at the level of the breach limit. Furthermore, it is dependent on the physical‐mechanical properties of the material and on the method, i. e., the technology of straining, or machining. The same applies to the roughness distribution and other topographical features on the machined surface. The tension that has not been exhausted is partly returned to the volume of the sample and partly acts in contact with space, within a certain distance and time. This paper aims to present a reverse reconstruction of the surface topography from residual stresses after chip‐forming machining of the material. Our original approach to the solution fully exploits the rules of roughness distribution and other topographic features of the surfaces of the given materials after machining, not only by chip‐forming machining.

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A new way of identifying, predicting and regulating residual stress after chip-forming machining

Cited by 23 publications

References 24 publications

Prediction of Cutting Parameters of HVOF-Sprayed Stellite 6

Prediction of Cutting Parameters of HVOF-Sprayed Stellite 6

The Predictive Model of Surface Texture Generated by Abrasive Water Jet for Austenitic Steels

Reverse reconstruction of surface topography from residual stress after chip‐forming machining of the material

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