Multiresponse optimization based on statistical response surface methodology and desirability function for the production of particleboard

It is very difficult to determine the actual level of process parameters responsible for the quality production of particleboard due to the high degree of process variable interactions and lack of robust methodology for optimization. In this study, an attempt was made to optimize the process parameters of particleboard production by using multi-response optimization process. Plackett–Burman factorial design was first employed to eliminate some factors from selected seven important parameters: flake thickness, flake length, dried chips moisture content (MC%), amount of adhesive, pressing time, pressure, and press temperature. By using this screening procedure, three important factors: flake thickness, dried chips moisture content and press temperature were found to have significant effect on particleboard properties. Afterwards, Box–Behnken design was performed as response surface methodology (RSM) with desirability functions to attain the optimal flake thickness, MC% and press temperature that affect modulus of rapture (MOR) and modulus of elasticity (MOE) of particleboard production. The optimized parameters for maximum MOR and MOE determined were found to be: flake thickness, 0.15 mm; press temperature, 182 °C; and dried chip MC% 3.5. Finally, a confirmation study was executed by using optimized levels of parameters which showed well response to the predicted model.