THE STUDY OF ENERGY CONSUMPTION IN THE DIMENSION STONE CUTTING PROCESS

U industriji arhitektonsko-građevnoga kamena važno je predvidjeti utrošak energije kod njegova rezanja. Utvrđivanje odnosa strojnih varijabli s tim utroškom važan je postupak. Konstruirani su ispitni, laboratorijski rezaći strojevi s mogućnošću promjene radnih varijabli. Prikupljeni rezultati statistički su analizirani usporedbom s potrošnjom energije. Testiranje je načinjeno na sedam uzoraka karbonatnih stijena, uz različite vrijednosti dubine zarezivanja, jakosti i brzine. Tako je dobiven model utroška energije, postavljen u odnosu na svaku promatranu, nezavisnu varijablu. Statistička analiza načinjena je paketom SPSS. U njoj su primijenjeni t-test i F-test. Vrijednosti predviđene takvim modelom prikazane su dijagramom raspršenja. Rezultati su vrlo bliski linearnomu modelu predstavljenomu pravcem pod kutom od 45 stupnjeva. Takav model odlikuje se visokim stupnjem točnosti te korelacije između predviđenih i opaženih vrijednosti. Stoga on može biti korišten za izračun utroška energije uz različite ulazne varijable.In the dimension stone industry, predicting the energy consumption in rock cutting process and examining its relationship with machining parameters are among the most important steps to achieve the optimum conditions in terms of energy consumption. A laboratory scale cutting machine with changing machining parameters was made and its energy consumption was evaluated through the statistical analysis. Tests were carried on seven carbonate rock samples under different operating conditions at different depths of cut, feed rates and peripheral speeds. Finally, an energy consumption model was obtained through statistical studies using SPSS software. The t and F tests were used to validate the model and to control each of the independent variables. To see the prediction capability of the derived model, the scatter diagram of the observed and estimated values was plotted. The results showed that the points are very close to the 1:1 diagonal straight line. It concluded that the developed model has a high degree of accuracy with a high correlation between the predicted and the observed values. Due to its high accuracy, the proposed model can be used in the calculation of energy consumption under various operating parameters