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1.
A model of surface roughness constitution in the metal cutting process applying tools with defined stereometry
Stanisĺaw Adamczak, Edward Miko, Franc Čuš, 2009, izvirni znanstveni članek

Opis: The process of surface roughness formation is complex and dependent on numerous factors. The analysis of the latest reports on the subject shows that mathematical relationships used for determining surface irregularities after turning and milling are not complete or accurate enough and, therefore, need to be corrected. A new generalized mathematical model of roughness formation was developed for surfaces shaped with round-nose tools. The model provides us with a quantitative analysis of the effects of the tool representation, undeformed chip thickness, tool vibrations in relation to the workpiece, tool runout (for multicutter tools) and, indirectly, also tool wear. This model can be used to prepare separate models for most of the typical machining operations. Surface roughness is represented here by two parameters Ra and Rt. Simulations carried out for this model helped to develop nomograms which can be used for predicting and controlling the roughness Ra of surfaces sculptured by face milling.
Ključne besede: metal cutting, surface roughness, finishing, face milling
Objavljeno: 31.05.2012; Ogledov: 1138; Prenosov: 11
URL Povezava na celotno besedilo

2.
Prediction of surface roughness using a feed-forward neural network
Jernej Šenveter, Simon Klančnik, Jože Balič, Franc Čuš, 2010, izvirni znanstveni članek

Opis: This article presents the development of a system for predicting surface roughness, using a feed-forward neural network. The primary goal was to develop a system in order to predict with complex reliability and defined accuracy. However, this system is designed in such a way that it is also possible to use it for various other workpieces. The described system uses a neural network which receives signals at the input level. The signals then travel through all hidden levels to the output level, where the responses to input signals are received. Data are used which affects the selection of surface roughness regarding the input to the neural network. Three different inputs in total are used for the neural network. Data which represents the inputs to the neural network are encoded, so that they occupy values between 0 and 1. Adequate cutting speed, feed, and depth of cut, are selected in order to achieve an adequate surface roughness of the workpiece, using the trained neural network. This contributes to the optimisation and economy of machining, which is very important during the production of an individual product and also for an individual company or organisation when transferring the final product to the contracting authority or final customer.
Ključne besede: machining, turning, surface roughness, neural network
Objavljeno: 31.05.2012; Ogledov: 1074; Prenosov: 41
URL Povezava na celotno besedilo

3.
Biodiesel influence on tribology characteristics of a diesel engine
Stanislav Pehan, Marta Svoljšak, Marko Kegl, Breda Kegl, 2009, izvirni znanstveni članek

Opis: This paper deals with the influence of biodiesel on some tribology characteristics of a bus diesel engine with a mechanically controlled fuel injection system. The tests have been performed on a fully equipped engine test bed, on a fuel injection test bed and on a discharge coefficient testing device. The tested fuel was neat biodiesel produced from rapeseed. Attention was focused on the biodiesel influence on the pump plunger surface roughness, on the carbon deposits in the combustion chamber, on the injector and in the injector nozzle hole. The pump plunger surface was analyzed by experimentally determined roughness parameters and by a microscope. The carbon deposits at fuel injector and in the combustion chamber were examined using endoscopic inspection. The deposits in the injector nozzle were investigated indirectly by measuring the nozzle discharge coefficient. Numerical simulation has been performed in order to estimate the influence of the discharge coefficient variation on the computed injection characteristics. The obtained results indicate that biodiesel usage may even improve the pump plunger lubrication conditions. Furthermore, the carbon deposits in the combustion chambers did not vary significantly in quantity but they were noticeably redistributed. Finally, it was found out that the variation of the nozzle discharge coefficient has to be taken into account only if high accuracy of numerical simulation is desired.
Ključne besede: biodiesel, surface roughness, carbon deposits
Objavljeno: 01.06.2012; Ogledov: 1092; Prenosov: 61
URL Povezava na celotno besedilo

4.
Prediction of surface roughness with genetic programming
Miran Brezočnik, Miha Kovačič, Mirko Ficko, 2004, izvirni znanstveni članek

Opis: In this paper we propose genetic programming to predict surface roughness in end-milling. Two independent data sets were obtained on the basis of measurement: training data set and testing data set. Spindle speed, feed rate,depth of cut, and vibrations are used as independent input variables (parameters), while surface roughness as dependent output variable. On the basis of training data set, different models for surface roughness were developed by genetic programming. Accuracy of the best model was proved with the testing data. It was established that the surface roughness is most influenced by the feed rate, whereas the vibrations increase the prediction accuracy.
Ključne besede: end milling, surface roughness, prediction of surface roughness, genetic programming
Objavljeno: 01.06.2012; Ogledov: 1009; Prenosov: 72
URL Povezava na celotno besedilo

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