Optimization plays a key role in a process control industry to optimize and prediction of the system’s performance. Most of the process control are multi-variable and to control the parameters to optimized the system performance through the classical method is inflexible, unreliable and time-consuming. Thus, an alternative method will be more effective for parameter optimization & prediction. In this research investigates parameters affecting the liquid flow for the various studied. Design of Experiments based on metaheuristic algorithm is conducted for the analysis of influencing factors. Response surface methodology (RSM) & ANOVA are widely used as a mathematical and statistical tool for system performance optimization. RSM can be employed to optimize and analyze the effects of several independent factors on a treatment process to obtain the maximum output. This paper is to present a comprehensive review on the usability & effectiveness of RSM & ANOVA based on flower pollination algorithm for process parameters modelling and optimization of liquid flow processes. From the appraisal it indicates that the FPA based RSM is gives the more predicted output than the FPA based ANOVA is approximately 9.0389e-6.
liquid flow process,experimental design & analysis, optimization,process parameter, RSM
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