A parametric-fuzzy logic system for paint cost estimation of products with uncertain geometric characteristics

Cost estimation is an upstream activity in manufacturing and service business. Accurate cost estimation promotes profitable decision making. In this study, a cost model was developed to estimate paint cost in a spraying process of wooden toys. The required amount of paint was formerly believed as a function of only product surface area. However, data collected earlier indicated that volume and projected area also had significant contribution. Altogether, these parameters triggered uncertain paint loss which complicated a cost model. In order to solve this problem, we propose a cost estimation method based on a fuzzy theory. While the traditional parametric cost function used a constant paint consumption rate, the proposed fuzzy model allowed the loss to be dependent on product parameters. Predictive results from both models were compared with actual data and their performances were measured. Overall performance of the fuzzy model is more superior especially for larger products in an upright placement on the spraying rack. With an accurate cost estimation system, enterprises can plan for more efficient material requirements, and pricing strategies.