A comprehensive review of Design of experiment (DOE) for water and wastewater treatment application - Key concepts, methodology and contextualized application

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Abstract

Design of experiment (DOE) is a robust design methodology that can be used to solve various water engineering problems. It aims to obtain the maximal results from data, while minimizing inputs, in terms of experiments required. DOE consists of various steps and experimental designs. However, the steps, experimental design and selection of designs are not well discussed in literature. Prior reviews are also not as comprehensive in the provision of all forms of DOEs available in the context of water chemistry. This study hence aims to fill that gap and provide a unique and novel perspective of DOE application in this sector. Specific and contextualized examples of DOE were reviewed with recent innovation within these 5 years. Steps detailing the process for DOE were also discussed with emphasis on experiment design type, model analysis and up-to-date applications of DOE. It was found that the selection of DOE protocol depends on the contextualized application of the DOE, where certain DOE was more suitable for some context. The application of DOE can be generally split into 3 distinct categories: screening, optimization or the study of variable interactions. Whereas the selection of experimental design and modeling approach was also found to be a trade-off between the accuracy of the modeling results and the number of experiments required. When considering different DOE approaches to water chemistry, it is important to evaluate the different advantages and disadvantages of each DOE in its contextualized use. Through this review, practitioners would hence have more informed decisions in the selection of DOE for its appropriate application.

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Lee, B. C. Y., Mahtab, M. S., Neo, T. H., Farooqi, I. H., & Khursheed, A. (2022, June 1). A comprehensive review of Design of experiment (DOE) for water and wastewater treatment application - Key concepts, methodology and contextualized application. Journal of Water Process Engineering. Elsevier Ltd. https://doi.org/10.1016/j.jwpe.2022.102673

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