Факултет за производњу и менаџмент [Научни радови] / Faculty of Production and Management Trebinje [Scientific papers]

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    CAD/CAM system implementation criteria in the process generating of optimal and efficient models for clothing industry
    (National Research-Development Institution for Leather Textiles, Romania, 2020) DIMITRIJEVIĆ, DRAGAN; SPAIĆ, OBRAD; ĐURIĆ, ŽELJKO; UROŠEVIĆ, SNEŽANA; NIKOLIĆ, MAJA
    The first part of the paper is a systematic explanation of the process of defining the most important parameters for generating optimal and efficient models of small and medium sized enterprises (SMEs) of the clothing industry, with the presentation of specific and adequate methods of research, i.e. with the evaluation of data for designing new models, and including previous research data. The following is an explanation of the final phase, i.e. a systematic and objective design assessment, through the implementation of preliminary results of exploitation studies of the modal experiment and computer simulation of the new model, based on which the criteria for efficient and optimal implementation of the CAD/CAM systems are defined.
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    (Center for Quality, Faculty of Engineering, University of Kragujevac, Serbia,, 2020) Spaić, Obrad; Krivokapić, Zdravko; Marinović, Budimirka; Jovanović, Janko
    One of the most commonly used and at the same time the most complicated cutting tools in terms of body geometry is the spiral drill bit. In the process of their production, the key operation is the production of spiral grooves. Until now, the grooves on the drill bits have been mainly produced by milling, grinding, rolling and extrusion processes. All these procedures have their advantages and disadvantages as well. Based on the experimental measurements of the dimensions of the grooves of the drill bits produced by the rolling and grinding technology, the paper defines the basic parameters and a new technological procedure for the production of grooves of the drill bits has been designed. For the suggested technological procedure of making of grooves of the drill bits, the advantages and disadvantages of the conventional production of the grooves of the drill bits by rolling or grinding technology have been analysed.
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    Modelling Surface Roughness in the Function of Torque When Drilling
    (MDPI, 2020) Krivokapić, Zdravko; Vučurević, Radoslav; Kramar, Davorin; Šaković Jovanović, Jelena
    Given the application of a multiple regression and artificial neural networks (ANNs), this paper describes development of models for predicting surface roughness, linking an arithmetic mean deviation of a surface roughness to a torque as an input variable, in the process of drilling enhancement steel EN 42CrMo4, thermally treated to the hardness level of 28 HRC, using cruciform blade twist drills made of high speed steel with hardness level of 64–68 HRC. The model was developed using process parameters (nominal diameters of twist drills, speed, feed, and angle of installation of work pieces) as input variables varied at three levels by Taguchi design of experiment and measured experimental data for a torque and arithmetic mean deviation of a surface roughness for different values of flank wear of twist drills. The comparative analysis of the models results and the experimental data, acquired for the inputs at the moment when a wear span reaches a limit value corresponding to a moment of the drills blunting, demonstrates that the neural network model gives better results than the results obtained in the application of multiple linear and nonlinear regression models.
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    Development of family of artificial neural networks for the prediction of cutting tool condition
    (Faculty of Mechanical Engineering, University of Maribor,Slovenia Faculty of Mechanical Engineering, 2020) Spaić, O.; Krivokapić, Z.; Kramar, D.
    Recently, besides regression analysis, artificial neural networks (ANNs) are increasingly used to predict the state of tools. Nevertheless, simulations trained by cutting modes, material type and the method of sharpening twist drills (TD) and the drilling length from sharp to blunt as input parameters and axial drilling force and torque as output ANN parameters did not achieve the expected results. Therefore, in this paper a family of artificial neural networks (FANN) was developed to predict the axial force and drilling torque as a func-tion of a number of influencing factors. The formation of the FANN took place in three phases, in each phase the neural networks formed were trained by drilling lengths until the drill bit was worn out and by a variable parameter, while the combinations of the other influencing parameters were taken as constant values. The results of the prediction obtained by applying the FANN were compared with the results obtained by regression analysis at the points of experimental results. The comparison confirmed that the FANN can be used as a very reliable method for predicting tool condition.
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    (Institute for metallic materials and technology, 2021) Spaić, Obrad; Vukčević, Milan; Marinović, Budimirka; Koprivica, Aleksandra; Jovanović, Janko
    The current world trends and the global market require production organizations to increase the quality while reducing the costs of their products. In most cases, traditional production technologies of spiral drill bits (SD) cannot meet these expectations, as they most often fulfil only one of the set requirements. Thus, the cost of a SD produced with the rolling technology is low, but its quality is also much lower than that of the drills produced with the grinding technology whose cost is also much higher. The grooves of the SDs produced with our new technological method have advantages over the grooves produced with the rolling technology or grinding technology, and the savings in the material and grinding wheel are higher compared to the SDs produced with the grinding technology. This paper presents an analysis of the application of this new technological process for producing SD grooves