Statistical Process Control for Heavy-Metal Adsorption: Challenges and Opportunities
Abstract
The inherent complexity of heavy-metal adsorption calls for robust analytical and experimental tools suited to industrial automation. Experimental data collected from several industrial automation were analysed with the help of statistical process control. The measured efficiency reached up to 33% under the optimal operating conditions. The results support the adoption of the proposed method in routine engineering practice.
Keywords:
heavy-metal adsorptionstatistical process controlgenetic algorithmoptimizationenergy efficiency
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