Otimização no co-processamento de resíduos na indústria do cimento envolvendo custos, qualidade e impacto ambiental

Abstract

This PhD thesis presents an optimization model for the use of industrial waste as alternative fuels taking into account targets such as quality, specific heat consumption, and pollutant emissions constraints, among others. The model takes into account the raw material and fuel cost, and also the electric power consumption cost requested for grinding which is another important factor. In the modeling, two optimization techniques were used: (i) the deterministic approach, through the Quadratic Sequential Programming (SQP) method in a combination with Monte Carlo’s method and (ii) the heuristic approach, through the Genetic Algorithm (GA) and Differential Evolution (DE) techniques applying penalty functions in order to validate the obtained results. Among the employed algorithms, the GAs didn't show a satisfactory solution, presenting convergence problems due to the need of satisfying all the imposed restrictions. On the other hand, for the SQP and the DE algorithms, the results were satisfactory with a small difference between the obtained optimum values. The DE method demanded a larger computational time when compared with the SQP due to the great number of objective function evaluations, an inherent characteristic of the DE. The results obtained from the modelling were quite satisfactory, being possible to evaluate the levels of substitution of the primary fuel for the alternative fuel derived from the industrial wastes, taking into account the acceptable limits of pollutant emissions, the cement quality standards as well as others parameters specific which are for the cement industry.