The enzyme washing process is extensively applied in the industrial production of denim garments. The process parameters of enzyme washing have significant effects on washing performances and costs. Since the relationships between the process parameters and washing performances cannot be expressed explicitly, it is impractical to determine the process parameters to obtain the optimal production cost while satisfying requirements of customers intuitively. This paper proposes an optimization methodology by combining Kriging surrogate and differential evolution (DE) algorithm to address the production cost optimization of enzyme washing for indigo dyed cotton denim. First, an experiment using Taguchi L16 orthogonal array is conducted where temperature and concentration of cellulase enzyme are taken into consideration with processing time as the input parameters, while the washing performances (including color strength value, stiffness, and tensile strength in warp and weft directions of the washed denim fabrics) are the output responses. Second, the relationships between the inputs and outputs are established using the Kriging model. Third, the effects of the input parameters on the washing performances are analyzed, and the production cost optimization model is illustrated. Finally, a case study is given to depict the optimization process and a verification experiment is conducted to verify the effectiveness of the optimal values. On the whole, the proposed hybrid method, Kriging-DE, shows great capability of optimizing the production costs of the enzyme washing process for indigo dyed cotton denim.
Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The San Joaquin Valley
