1. Determination of shear bond strength between PEEK composites and veneering composites for the production of dental restorationsAnamarija Kuchler, Klementina Pušnik Črešnar, Iztok Švab, Tomaž Vuherer, Majda Žigon, Mihael Brunčko, 2023, izvirni znanstveni članek Opis: We studied the shear bond strength (SBS) of two PEEK composites (BioHPP, BioHPP plus) with three veneering composites: Visio.lign, SR Nexco and VITA VM LC, depending on the surface treatment: untreated, sandblasted with 110 μm Al2O3, sandblasted and cleaned ultrasonically in 80% ethanol, with or without adhesive Visio.link, with applied Visio.link and MKZ primer. For the BioHPP plus, differential scanning calorimetry (DSC) revealed a slightly lower glass transition temperature (Tg 150.4 ± 0.4 °C) and higher melting temperature (Tm 339.4 ± 0.6 °C) than those of BioHPP (Tg 151.3 ± 1.3 °C, Tm 338.7 ± 0.2 °C). The dynamical mechanical analysis (DMA) revealed a slightly higher storage modulus of BioHPP (E’ 4.258 ± 0.093 GPa) than of BioHPP plus (E′ 4.193 ± 0.09 GPa). The roughness was the highest for the untreated BioHPP plus, and the lowest for the polished BioHPP. The highest hydrophobicity was achieved on the sandblasted BioHPP plus, whereas the highest hydrophilicity was found on the untreated BioHPP. The highest SBSs were determined for BioHPP and Visio.lign, adhesive Visio.link (26.31 ± 4.17 MPa) or MKZ primer (25.59 ± 3.17 MPa), with VITA VM LC, MKZ primer and Visio.link (25.51 ± 1.94 MPa), and ultrasonically cleaned, with Visio.link (26.28 ± 2.94 MPa). For BioHPP plus, the highest SBS was determined for a sandblasted surface, cleaned ultrasonically, with the SR Nexco and Visio.link (23.39 ± 2.80 MPa).
Ključne besede: BioHPP, CAD/CAM milling, BioHPP plus, pressing, veneering composites, roughness, wettability, shear bond strength
Objavljeno v DKUM: 05.04.2024; Ogledov: 213; Prenosov: 14
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2. Comparison of different optimization and process control proceduresMarko Reibenschuh, Franc Čuš, Uroš Župerl, 2010, pregledni znanstveni članek Opis: This paper includes a comparison of different optimization methods, used for optimizing the cutting conditions during milling. It includes also a part of using soft computer techniques in process control procedures. Milling is a cutting procedure dependent of a number of variables. These variables are dependent from each other in consequence, if we change one variable, the others change too. PSO and GA algorithm are applied to the CNC milling program to improve cutting conditions, improve end finishing, reduce tool wear and reduce the stress on the tool, the machine and the machined part. At the end a summary will be given of pasted and future researches.
Ključne besede: optimization, milling, cutting parameters, LENS
Objavljeno v DKUM: 04.08.2017; Ogledov: 1144; Prenosov: 361
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3. Intelligent adaptive cutting force control in end-millingUroš Župerl, Franc Čuš, Edvard Kiker, 2006, izvirni znanstveni članek Opis: In this article, an adaptive neural controller for the ball end-milling process is described. Architecture with two different kinds of neural networks is proposed, and is used for the on-line optimal control of the milling process. A BP neural network is used to identify the milling state and to determin the optimal cutting inputs. The feedrate is selected as the optimised variable, and the milling state is estimated by the measured cutting force. The adaptive controller is operated by a PC and the adjusted feedrates are sent to the CNC. The purpose of this article is to present a reliable, robust neural controller aimed at adaptively adjusting feed-rate to prevent excessive tool wear, tool breakage and maintain a high chip removal rate. The goal is also to obtain an improvement of the milling process productivity by the use of an automatic regulation of the cutting force. Numerous simulations are conducted to confirm the efficiency of this architecture. The proposed architecture for on-line determining of optimal cutting conditions is applied to ball end-milling in this paper, but it is obvious that the system can be extended to other machines to improve cutting efficiency.
Ključne besede: end milling, adaptive force control, neuron controller, cutting conditions, adaptive control systems
Objavljeno v DKUM: 12.07.2017; Ogledov: 1289; Prenosov: 134
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4. Design and construction of the technological process of product productionMarko Drempetić, 2016, magistrsko delo Opis: Master’s thesis contains technological procedure for developing product which includes design,
making of technological documentation, choosing parameters for CNC machining, and
measuring of the final product. The product from this master thesis is “Oil control block”. This is
one of the parts of the high voltage switchgear GIS „Gas Insulated Switchgear“ which is used for
regulation of pressure during switching. The product is made from material C45 (1.0503)
according to European norm EN 10277-2-2008. The technological process is shown in
spreadsheet view. Also it’s explained the workholding device and the way of using it, then it’s
shown the technological documentation which follows the machining process, then the NC
program and 3D model. It will be shown the CNC milling machine "Matsuura H.Plus-630
Horizontal Machining Center" and the parameters for machining process. After machining
process is done the workpiece is sent to the Quality Control Department where it is checked
GD&T. Dimension are controlled on 3D coordinate measurement system “FARO” then the
control list is generated with the appropriate software.
Ključne besede: technological process, workpiece, milling process, G and M code, 3D Laser
scanner
Objavljeno v DKUM: 04.04.2016; Ogledov: 1566; Prenosov: 197
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5. Optimiranje značilnih parametrov frezanja z uporabo razvojne tehnike optimizacije jate delcevUroš Župerl, Franc Čuš, Valentina Gečevska, 2007, izvirni znanstveni članek Opis: Izbira rezalnih parametrov je najpomembnejši korak pri postopku načrtovanja proizvodnje, zato izdelamo novo tehniko razvojnega računanja za optimiranje procesa odrezovanja. V prispevku je uporabljena tehnika, ki oponaša dinamiko delcev v velikih skupinah (optimizacija PSO), za učinkovito in simultano optimiranje postopkov frezanja. V omenjenih postopkih smo soočeni s problemom več ciljnih dejavnikov. Najprej uporabimo umetno nevronsko mrežo (UNM) za napovedovanje rezalnih sil, nato z algoritmom PSO pridobimo optimalno rezalno hitrost in podajanja. Cilj optimizacije je, ob upoštevanju omejitev, določiti ekstrem ciljne funkcije (napovedna površina največjih sil). Med optimizacijo delci, s svojo inteligenco, letijo po prostoru rešitev in iščejo optimalne rezalne pogoje po strategiji algoritma PSO. Rezultati pokažejo, da je integriran sistem nevronskih mrež in kolektivne inteligence učinkovita metoda pri reševanju večciljnih optimizacijskih problemov. Njena velika učinkovitost na širokem območju rezalnih parametrov potrjuje, da sistem lahko praktično uporabimo v proizvodnji. Rezultati simulacij nakazujejo, da predlagan algoritem v primerjavi z rodovnimi algoritmi (GA) in simulacijskim (SA) ohlajanjem lahko poveča natančnost rešitve in konvergenco postopka. Nova tehnika razvojnega računanja ima nekoliko prednosti ter koristi in je primerna za uporabo v kombinaciji z modeli na osnovi umetnih nevronskih vezij, pri katerih niso na voljo izrecne relacije med vhodi in izhodi. Raziskava odpre vrata na področju obdelave z odrezovanjem za nov razred optimizacijskih tehnik, ki slonijo na razvojnem računanju.
Ključne besede: odrezovanje, končno frezanje, rezalni parametri, nevronske mreže, razvojne tehnike, optimizacija jate delcev, cutting, end-milling, cutting parameters, neural networks, evolution techniques, particle swarm optimization
Objavljeno v DKUM: 10.07.2015; Ogledov: 1625; Prenosov: 40
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6. Real-time cutting tool condition monitoring in millingFranc Čuš, Uroš Župerl, 2011, izvirni znanstveni članek Opis: Reliable tool wear monitoring system is one of the important aspects for achieving a self-adjusting manufacturing system. The original contribution of the research is the developed monitoring system that can detect tool breakage in real time by using a combination of neural decision system and ANFIS tool wear estimator. The principal presumption was that force signals contain the most useful information for determining the tool condition. Therefore, the ANFIS method is used to extract the features of tool states from cutting force signals. ANFIS method seeks to provide a linguistic model for the estimation of tool wear from the knowledge embedded in the artificial neural network. The ANFIS method uses the relationship between flank wear and the resultant cutting force to estimate tool wear. A series of experiments were conducted to determine the relationship between flank wear and cutting force as well as cutting parameters. Speed, feed, depth of cutting, time and cuttingforces were used as input parameters and flank wear width and tool state were output parameters. The forces were measured using a piezoelectric dynamometer and data acquisition system. Simultaneously flank wear at the cutting edge was monitored by using a tool maker's microscope. The experimental force and wear data were utilized to train the developed simulation environment based on ANFIS modelling. The artificial neural network, was also used to discriminate different malfunction states from measured signals. By developed tool monitoring system (TCM) the machining process can be on-line monitored and stopped for tool change based on a pre-set tool-wear limit. The fundamental limitation of research was to develop a single sensor monitoring system, reliable as commercially available system, but 80% cheaper than multisensor approach.
Ključne besede: end-milling, tool condition monitoring, wear estimation, ANFIS
Objavljeno v DKUM: 10.07.2015; Ogledov: 1945; Prenosov: 124
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7. Influence of the milling strategy on the durability of forging toolsIvo Pahole, Dejan Studenčnik, Karl Gotlih, Mirko Ficko, Jože Balič, 2011, izvirni znanstveni članek Opis: The quality of a tool's surface has a direct influence on the number of well-produced parts. For the machining of an active tool surface, two technological processes are used: electrical discharge machining and high-speed milling. These two processes are used when machining new tools and for the repairing of used forging tools. In both cases, the material has already been thermally treated, so it has to be used for hard milling. Practical experience shows that the milling strategy has a big influence on the durability of a forging tool. This paper shows the influence of the CNC machining direction during high-speed milling on the durability of the engraving within the forging tool. In some cases the correct milling strategy can increase the durability of the forging tool by about one third.
Ključne besede: orodja za kovanje, kakovost površine, visokohitrostno rezkanje, CNC-rezkanje, forging tools, surface quality, high speed cutting, CNC milling
Objavljeno v DKUM: 10.07.2015; Ogledov: 1530; Prenosov: 120
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8. Using LabVIEW software for development of new data acquisition softwareMarko Reibenschuh, Franc Čuš, Uroš Župerl, 2012, izvirni znanstveni članek Opis: LabVIEW enables programing and development of different interfaces for monitoring. Because of worldwide increasing demands for condition monitoring and demands to increase productivity, a new user interface for data acquisition is developed and applied to gather data and information during cutting. Other possibilities for implementing the method into production process are also researched. To monitor a high speed process, the use of high speed camera is inevitable.. This paper presents preliminary development, tests and result.
Ključne besede: monitoring, milling, data acquisition, LabVIEW
Objavljeno v DKUM: 10.07.2015; Ogledov: 1316; Prenosov: 62
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9. Intelligent tool path generation for milling of free surfaces using neural networksJože Balič, Marjan Korošec, 2002, izvirni znanstveni članek Opis: The presented paper has an intention to show how with the help of Artificial Neural Network (ANN), the prediction of milling tool-path strategy could be made in order to establish which milling path strategy or their sequence will show the best results (will be the most appropriate) at free surface machining, according to set technological aim. In our case the best possible surface quality of machined surface was taken as the primary technological aim. Configuration of used Neural Network (NN) is presented, and the whole procedure is shown on an example of mould, for producing light switches. The verification of machined surface quality, according to average mean roughness, Ra, is also being done, and compared with the NN predicted results
Ključne besede: neural network, CAD/CAM, CAPP, ICAM, milling strategy
Objavljeno v DKUM: 01.06.2012; Ogledov: 1900; Prenosov: 116
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10. Prediction of surface roughness with genetic programmingMiran 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 v DKUM: 01.06.2012; Ogledov: 2154; Prenosov: 133
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