Wastewater treatment plant (WWTP) is an essential process in the manufacturing industry. However, wastewater treatment process is not a profitable process as it requires a significant amount of investment. It is important to design a WWTP that meets wastewater discharge legalisation with low investment costs. To do this, area footprint (land area) occupied by technologies in a WWTP must be factored into the design decision. Unfortunately, the area footprint is yet to be studied. As wastewater treatment processes involve multiple treatment units, the different combinations of these treatment units will give a range of capital costs and costs associated with the area occupied. In addition, the carbon footprint of technology resulting from power consumption must be considered. Each technology possesses unique power consumption requirements and these requirements may influence the total carbon footprint for a given WWTP design. Investment costs, area footprint and carbon footprint must be considered simultaneously but are conflicting in nature. This work aims to present a multi-objective decision-making tool to screen wastewater treatment technologies and to synthesise a WWTP design with low investment cost, low area footprint, and low carbon footprint. Specifically, fuzzy multiobjective optimisation (FMOO) is used to determine a desirable trade-off between investment costs, area footprint, and carbon footprint. To demonstrate the developed approach, a sago-based WWTP case study is solved. Based on the results, a trade-off between these optimisation objectives had reduced 5.35 m2 of area footprint, 986 USD/d of total investment cost, and 108 kg CO2/d of carbon footprint of the synthesised WWTP.
ASJC Scopus subject areas
- Chemical Engineering(all)