Sharif Digital Repository

The application of sensor system is becoming more commonplace in improving productivity and reliability. Although measuring force signal have been widely used for monitoring of metal machining process that their application to stone cutting has not been well investigated. In this paper, the effect of machining parameter on force signal and tool wear was investigated. The result indicate that increasing of the depth of cut and spindle speed will increase the force and tool wear while increasing feed rate will increase force and decrease tool wear  

A new predictive model for evaluating the vibration of a sawing machine was developed using a new rock classification system. The predictors are machine parameters and a rock sawability index. The new rock classification system includes four major parameters of the rock: uniaxial compressive strength, abrasivity index, mean Moh's hardness, and Young's modulus. The FAHP approach was used when determining the weights of these parameters by six decision makers. Two groups of carbonate rocks were sawn using a fully-instrumented laboratory sawing rig at different feed rates and depths of cut. During the sawing trials system vibration was monitored as a measure of saw performance. Then, a new... 

The desired milling process with high material removal rate (MRR) and low surface roughness of the product can be achieved only if machining chatter is absent. Incorporating chatter into the optimal selection of the machining parameters leads to a complex problem. Therefore, the approach of selecting conservative intervals for the machining parameters is usually employed instead. In this paper, a practical approach is proposed to specify the optimal machining parameters (depth of cut and spindle speed) in order to maximize MRR and minimize forced vibrations by considering machining chatter. Firstly, the worst-case scenario-based optimization problem in terms of the surface quality is solved... 

Metal matrix composites (MMCs) have received considerable attention due to their excellent engineering properties. However, poor machinability has been the main deterrent to their substitution for metal parts. The hardness and abrasive nature of reinforcement phase causes rapid tool wear during machining which results in high machining costs. In this study, the effect of SiC particles (5, 15 & 20 percent) on tool wear in turning process is experimentally investigated. Continuous dry turning of Al/SiC particulate metal matrix composite produced by powder metallurgy and utilizing titanium carbide inserts has been achieved as the test method. The influence of machining parameters, e.g. cutting... 

Metal matrix composites (MMCs) have received considerable attention due to their excellent engineering properties, but their poor machinability has been the main deterrent to their substitution for metal parts. Optimization of machining parameters such as cutting speed, feed rate and depth of cut will improve the machinability of this material. This paper represents application of artificial neural network (ANN) model and genetic algorithm to study the machinability aspects of Al/SiC-15% produced by powder metallurgy process and to obtain optimum machining conditions. A multilayer feed forward ANN has been employed to study the effect of machining parameters on three aspects of machinablity,...