Dairy industry wastewater, characterized by its high load of organic and inorganic pollutants, continues to pose significant challenges to conventional treatment technologies. Electrocoagulation (EC) has emerged as an effective alternative, but its success depends on the careful optimization of multiple interrelated parameters. This commentary builds upon the study “Comparative Evaluation Between Taguchi Method and Response Surface Method for Optimization of Electrocoagulation Process in the Context of Treatment of Dairy Industry Wastewater” by Praful et al., which benchmarked the Taguchi method against Response Surface Methodology (RSM) for EC process optimization. While RSM offers flexibility in modeling complex interactions, the Taguchi method stands out for its experimental simplicity, reduced resource demand, and practical applicability in real-world settings. This commentary critically evaluates the strengths and limitations of the Taguchi method and positions it not as an endpoint but as a foundational method that can be extended through hybridization. By advocating for the integration of Taguchi with modern computational and decision-support tools, this article proposes a roadmap for developing more adaptive, intelligent, and multi-objective optimization strategies in industrial wastewater treatment.

Dairy wastewater, Electrocoagulation, Taguchi method, Statistical optimization, Hybrid modeling