Determining the Optimal Composition of Industrial Paint Formulation and Productivity Enhancement in Related Production Processes Using FMEA Technique and Taguchi Orthogonal Arrays

In today's competitive world, various organizations have been constantly concerned with improving production processes as a way to enhance product quality.  Experiment design is a statistical quality control method leading to increased product quality, and thereby, enhanced manufacturing productivity. The present study set out to identify and prioritize the defects in industrial paints produced by Partofooldam industrial paint manufacturing company through failure mode and effects analysis (FMEA) and to determine optimal value levels for the identified effective factors using Taguchi Orthogonal Array Method. To serve the purpose, six trihedral factors and one dihedral factor were defined and the L18 array was selected for designing the required experiments. The findings indicated that the best paint quality was obtained in the experimental condition with over 10 micron granulation, peak metal temperature (PMT) of 232°C, high quality pigment, resin content of 55%, catalyst content of 4.1%, using medium quality plate and maximum content of additives. The effectiveness of the proposed method was determined by comparing the risk priority number (RPN) in FMEA before and after implementing Taguchi Method which showed a 19 point drop in the mean RPNs for all the identified problems. The results verified the impact of Taguchi’s method on reducing product failure risk and enhancing product quality.