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The image processing and analysis applied in manufacturing industry is increasing. The applications are mostly in quality control, such as visual inspection. If the processing and analysis are used in production lines for ceramic tiles, it could be very demanding and it has to be very fast. So the use of powerful computer architectures such as computer clusters is applied.In this paper we present the image processing method of ceramic tiles that determine image object dimension and orientation. Processing was done on Beowulf cluster using different number of nodes and processors and starting MPICH and LAM/MPI jobs.

The ceramic tiles industry has a significant environmental impact due to consumption of raw materials, energy and environmental emissions. There are numerous activities on global level in accordance to the principles of sustainable development. This paper presents the development and application of mathematical models of manufacturing processes based on static neural networks for prediction and control of environmental impact of ceramic tiles production process. The neural network learning is made based on known input and output values from the production process. The control of the environmental impact is made on the basis of the output values from the process amounts of correct and faulty ceramic tiles. The model for prediction of correct amount of tiles and percentage of waste with an average error of 1.7% is presented in this paper. It could be successfully used to estimate and control the environmental influence. A simple model of production process has been applied in the manufacturing process of ceramic tile factory KIO Keramika d.o.o. Orahovica. It produced ceramic tiles using monofiring process according to EN 14 411 B III group Part L. The company has introduced and certified management systems according to ISO-9001. and ISO 14001