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In machining systems, the quality of the manufactured part is directly related to the condition of the tool used. Sharp tools are mostly used on the final machining pass to obtain enhanced dimensional accuracy and surface smoothness. Worn tools on the other hand are typically used for coarse machining. The operator usually makes tool assignments based on his experience, the wear levels of the tools and the type of machining task. However, this kind of operator judgment is bound to errors and may not be reliable in processes requiring high precision. Therefore, a tool condition monitoring system is highly desirable to achieve the best results in machining quality. In this study, three-axis cutting forces, torque, three-axis accelerometer and acoustic emission signals were analyzed and used for the development of an online tool condition monitoring system. Various time domain and statistical features extracted from these signals were used to train support vector machine models in a binary decision tree, which was used to predict the condition of the cutting tool. The genetic algorithm was employed for reducing the dimensionality of the feature set by selecting the features that correlates best with the tool condition. Nine experiments were carried out at different cutting conditions. Experimental results demonstrated the efficacy of the proposed scheme. The classification rates for the tool condition monitoring system before and after inclusion of the genetic algorithm step were determined as 89% and 100%, respectively.

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Purpose -This paper describes a robotic system developed for tiling mosaics based on image processing according to customer expectations. Design/methodology/approach -Many varieties of mosaics art in different forms has been applied manually over centuries for art decorating. Although the mosaics material is cheap with immense decorative potential, the mosaics tiling process is difficult and costly skill to perform. Therefore, an image processing based robotic tiling system has been presented and applied in this study. An algorithm has been developed for converting the computer image to mosaic picture by using Borland Cþþ Builder 6.0 and successfully utilized on six degrees of freedom Ultimate Puma 500 type industrial robot for tiling glass mosaics to any plane. Findings -According to result of this study, it can be realized that the robots could be successfully utilized on decorating processes, e.g. tiling mosaics, for faster and flexible production. Originality/value -Presented robotic system allows the craftsmen to produce large and extra ordinary mosaic figures by using computer image and glass mosaic tiles. The goal of using a robot in this application is to increase the speed without man-faults and flexibility.