The Multi-Objective Robust Optimization of Molding Process Parameters for Particles from Tobacco Stems and Wood Chips

Abstract

Considering the stochastic uncertainty of three parameters (molding temperature, moisture content of raw materials and molding pressure) in the process of particles from tobacco stems and wood chips, the analytical robust optimal design of two quality properties (particle density and radial resistance pressure) is carried out. Based on the quadratic regression equation between performance and parameters, and the improved analytic hierarchy process (AHP) is used to deal with multi-objective. Taking the minimum variance of performance fluctuation as the objective, the optimal combination of process parameters is obtained by interior-point algorithm. Comparing with deterministic optimization, the variance of particle density is reduced by 8.45%, and the variance of radial resistance pressure is reduced by 29.76%, which has a good reference value to the actual production of biomass fuel.