عنوان مقاله [English]
In today's competitive world, improving processes to enhance product quality has always been a major concern for organizations. Design of experiments as one of statistical quality control methods leads to increasing the product quality and consequently productivity in manufacturing .In this research, we firstly tried to identify and prioritize the problems of industrial paints in one of the industrial paints manufacturers (Partofooladfam Co.) by using
failure mode and effects analysis (FMEA), and then using the array method Taguchi orthogonal to design experiments, determine optimal values for the levels of effective factors identified in the process. In this way, 6 factors in three levels and 1 factor in two levels were defined while the L18 array was selected for designing the required experiments. The obtained results showed that the best level of quality paints was obtained for the experiment with the following characteristics: granulation over 10micron, peak metal temperature (PMT) of 232°C, pigment of high quality, resin content of 55%, catalyst content of 4.1%, using plate with medium quality and maximum content of additives. In order to determine the effectiveness of the proposed method, the risk priority number (RPN) in FMEA was compared before and after Taguchi method implementation. The mean RPNs for all the identified problems droped by 19 points. This shows the impact of Taguchi’s method on reducing the risks of product failure and enhancing product quality.
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