Razvoj sistema za projektovanje i optimizaciju konstrukcije pribora

U disertaciji se prikazuje razvoj sistema za projektovanje i optimizaciju konstrukcije pribora za mašinsku obradu. Analizirani su različiti prilazi u projektovanu pribora. Prikazana je koncepcija i funkcionisanje razvijenog sistema. Validacija sistema je izvršena na konkternim radnim predmetima za operacije obrade bušenja i glodanja. Na kraju su dati odgovarajući zaključci i mogući pravci budućih istraživanjaThe dissertation shows the development of system for fixture design and layout optimization for machining processi. Different approaches were analyzed in fixture design. The concept and functioning of the developed system is presented. Validation of the system is made with specific workpieces for drilling and milling process operations. At the end the appropriate conclusions and possible directions for future research are given

Estimation of CNC Grinding Process Parameters Using Different Neural Networks

Continuation of research on solving the problem of estimation of CNC grinding process parameters of multi-layer ceramics is presented in the paper. Heuristic analysis of the process was used to define the attributes of influence on the grinding process and the research model was set. For the problem of prediction - estimation of the grinding process parameters the following networks were used in experimental work: Modular Neural Network (MNN), Radial Basis Function Neural Network (RBFNN), General Regression Neural Network (GRNN) and Self-Organizing Map Neural Network (SOMNN). The experimental work, based on real data from the technological process was performed for the purpose of training and testing various architectures and algorithms of neural networks. In the architectures design process different rules of learning and transfer functions and other attributes were used. RMS error was used as a criterion for value evaluation and comparison of the realised neural networks and was compared with previous results obtained by Back-Propagation Neural Network (BPNN). In the validation phase the best results were obtained by Back-Propagation Neural Network (RMSE 12,43 %), Radial Basis Function Neural Network (RMSE 13,24 %,), Self-Organizing Map Neural Network (RMSE 13,38 %) and Modular Neural Network (RMSE 14,45 %). General Regression Neural Network (RMSE 21,78 %) gave the worst results

Primena CAD/CAM tehnologije u projektovanju i izradi mostova pune anatomske forme na bazi cirkonijum-dioksida

Daily progress of dentistry, especially in the field of prosthodontics is introducing new materials and technologies. With the increasing need for aesthetically acceptable and non-metal materials, it came to development and improvement of ceramic materials and computer based systems (CA). The patient came in order to compensate the missing left lateral incisor. Since the adjacent teeth are brushed and the print was taken, casted model has been scanned using 3Shape D800 laboratory scanner. Dental restoration has been designed using 3Shape DentalSystem Premium software and the available tools. After completing the virtual design, the data are sent to the program responsible for CAM Zenotec® mini CAD/CAM device. As a result, the compensation with the full morphology was obtained without the need for finishing works.Stomatologija, posebno stomatološka protetika svakodnevno napreduje uvođenjem novih materijala i tehnologija. Kako se javlja sve veća potreba za estetski prihvatljivim i bezmetalnim materijalima, došlo je do razvoja i unapređenja keramičkih materijala i računarima podržanih sistema (CA). Pacijent se javio radi nadoknade nedostajućeg levog bočnog sekutića. Pošto su susedni zubi zbrušeni i uzet otisak, izliven je model koji je skeniran pomoću 3Shape D 800 laboratorijskog skenera. Zubna nadoknada je dizajnirana pomo ću 3Shape DentalSystem Premium softvera korišćenjem raspoloživih alata. Nakon završenog dizajna virtuelni podaci su poslati u program odgovoran za CAM Zenotec® mini CAD/CAM uređaja. Kao rezultat, dobijena je nadoknada pune morfologije bez potrebe za dorađivanjem

Fuzzy Hybrid Method for the Reconstruction of 3D Models Based on CT/MRI Data

This research proposes a hybrid method for improving the segmentation accuracy of reconstructed 3D models from computed tomography/magnetic resonance imaging (CT/MRI) data. A semi-automatic hybrid method based on combination of Fuzzy C-Means clustering (FCM) and region growing (RG) is proposed. In this approach, FCM is used in the first stage as a preprocessing step in order to classify and improve images by assigning pixels to the clusters for which they have the maximum membership, and manual selection of the membership intensity map with the best contrast separation. Afterwards, automatic seed selection is performed for RG, for which a new parameter standard deviation (STD) of pixel intensities, is included. It is based on the selection of an initial seed inside a region with maximum value of STD. To evaluate the performance of the proposed method, it was compared to several other segmentation methods. Experimental results show that the proposed method overall provides better results compared to other methods in terms of accuracy. The average sensitivity and accuracy rates for cone-beam computed tomography CBCT 1 and CBCT 2 datasets are 99 %, 98.4 %, 47.2 % and 89.9 %, respectively. For MRI 1 and MRI 2 datasets, the average sensitivity and accuracy values are 99.1 %, 100 %, 75.6 % and 99.6 %, respectively. The average values for the Dice coefficient and Jaccard index for the CBCT 1 and CBCT 2 datasets are 95.88, 0.88, 0.6, and 0.51, respectively, while for MRI 1 and MRI 2 datasets, average values are 0.96, 0.93, 0.81 and 0.7, respectively, which confirms the high accuracy of the proposed method

Fuzzy Hybrid Method for the Reconstruction of 3D Models Based on CT/MRI Data

This research proposes a hybrid method for improving the segmentation accuracy of reconstructed 3D models from computed tomography/magnetic resonance imaging (CT/MRI) data. A semi-automatic hybrid method based on combination of Fuzzy C-Means clustering (FCM) and region growing (RG) is proposed. In this approach, FCM is used in the first stage as a preprocessing step in order to classify and improve images by assigning pixels to the clusters for which they have the maximum membership, and manual selection of the membership intensity map with the best contrast separation. Afterwards, automatic seed selection is performed for RG, for which a new parameter standard deviation (STD) of pixel intensities, is included. It is based on the selection of an initial seed inside a region with maximum value of STD. To evaluate the performance of the proposed method, it was compared to several other segmentation methods. Experimental results show that the proposed method overall provides better results compared to other methods in terms of accuracy. The average sensitivity and accuracy rates for cone-beam computed tomography CBCT 1 and CBCT 2 datasets are 99 %, 98.4 %, 47.2 % and 89.9 %, respectively. For MRI 1 and MRI 2 datasets, the average sensitivity and accuracy values are 99.1 %, 100 %, 75.6 % and 99.6 %, respectively. The average values for the Dice coefficient and Jaccard index for the CBCT 1 and CBCT 2 datasets are 95.88, 0.88, 0.6, and 0.51, respectively, while for MRI 1 and MRI 2 datasets, average values are 0.96, 0.93, 0.81 and 0.7, respectively, which confirms the high accuracy of the proposed method

Advanced procedure for fabrication of substructure in dentistry

The paper presents some aspects of the novel integrated system, procedure for fabrication of metal substructure of metal-ceramic crowns. The results been shown that the CAD/CAE/RP technology integration presented in this paper can be fully applied to casting metal substructures. The substructure fabricated in this way, confirm the reduction of the total manufacturing time, with an increase in the percentage of high quality castings that use integrated system

Modelling and Prediction of Surface Roughness in CNC Turning Process using Neural Networks

The paper presents an approach to solving the problem of modelling and prediction of surface roughness in CNC turning process. In order to solve this problem an experiment was designed. Samples for experimental part of investigation were of dimensions 30 × 350 mm, and the sample material was GJS 500 - 7. Six cutting inserts were used for the designed experiment as well as variations of cutting speed, feed and depth of cut on CNC lathe DMG Moriseiki-CTX 310 Ecoline. After the conducted experiment, surface roughness of each sample was measured and a data set of 750 instances was formed. For data analysis, the Back-Propagation Neural Network (BPNN) algorithm was used. In modelling different BPNN architectures with characteristic features the results of RMS (Root Mean Square) error were controlled. Specially analysed were the RMS errors realised by different number of neurons in hidden layers. For the BPNN architecture with one hidden layer the architecture (4 – 8 - 1) was adopted with RMS error of 3,37%. In modelling the BPNN architecture with two hidden layers, a considerable amount of architectures was investigated. The adopted architecture with two hidden layers (4 - 2 - 10 - 1) generated the RMS error of 2,26%. The investigation was also directed at the size of the data set and controlling the level of RMS error

Application of Replica Technique and SEM in Accuracy Measurement of Ceramic Crowns

The paper presents a comparative study of the measuring values of the marginal gap related to the ceramic crowns made by dental CAD/CAM system using the replica technique and SEM. The study was conducted using three experimental groups, which consisted of ceramic crowns manufactured by the Cerec CAD/CAM system. The scanning procedure was carried out using three specialized dental 3D digitization systems from the Cerec family - two types of extraoral optical scanning systems and an intraoral optical scanner. Measurements of the marginal gap were carried out using the replica technique and SEM. The comparison of aggregate values of the marginal gap using the replica technique showed a statistically significant difference between the systems. The measured values of marginal gaps of ceramic crowns using the replica technique were significantly lower compared to those measured by SEM. The results indicate that the choice of technique for measuring the accuracy of ceramic crowns influences the final results of investigation

Comparative analysis of 3d digitization systems in the field of dental prosthetics

Amongst the modern engineering technologies which have found broad application in the field of dentistry, one of the most widely used is the 3D digitization. This paper deals with the application of 3D digitization systems in the field of dental prosthetics, and attempt to contribute in this field through comparative analysis of this kind of systems. Special attention is focused on extra oral 3D digitization systems and among them on non specialized dental 3D digitization systems. Beside the general overview and analysis of nine different systems, this paper presents experimental results of comparative accuracy analysis of two high-end 3D digitization systems - Atos II Triple Scan and Zeiss Metrotom 1500. Investigation was based on CAD inspection technique and included 3D and 2D cross sectional analysis. Results related to 3D analysis show that the majority of deviations are in positive direction, concentrated around 0,025 mm. Results of 2D analysis implicate the conclusion that the accuracy of the analysed systems is dependent on surface shape as well as on the model position during the process of 3D digitization

Utvrđivanje korozionih karakteristika stomatološke legure sa induktivno spregnutim plazma masenim spektrometrom

Corrosion resistance is one of the characteristics that dental alloy should possess as it should be placed in the oral cavity. Adverse tissue reactions of the gingiva and the periodontium close to dental cast alloys may be caused by the effects of released metal elements. Corrosion effect of dental Co-Cr-Mo alloy was investigated by ICP MS according to the EN ISO 10271 and EN ISO 22674. Co- Cr dental alloy Remanium GM 800+ (Dentaurum Ispringen, Germany was tested in artificial saliva for 7 days at 37ºC. The released metals were detected by Nexion 300X ICP MS (Perkin Elmer, USA). The results showed that the metal release was very low for Co, Cr and Mo, far below the permitted levels. ICP-MS can be considered as very reliable method for such a research.Otpornost na koroziju je jedna od karakteristika koju poseduju stomatološke legure koje trebaju biti postavljene u usnoj duplji. Neželjene reakcije tkiva gingive i parodoncijuma sa stomatološkim legurama može biti uzrokovano efektima oslobođenih metalnih elemenata. Efekat korozije stomatološke Co- Cr -Mo legure ispitana je ICP MS prema EN ISO 10271 i EN ISO 22674 . Co- Cr stomatološke legure Remanium GM 800 + ( Dentaurum Ispringen , testirano u Nemačkoj u veštačkoj pljuvački tokom 7 dana na 37º C. Otkriveni su oslobođeni metali Nekion 300Ks ICP MS ( Perkin Elmer , SAD ). Rezultati su pokazali veoma slabo oslobađanje metala, Cr i Mo , daleko ispod dozvoljenih nivoa. ICP -MS može smatrati veoma pouzdan metod za ovakvo istraživanje