Performance Optimization of Buried Water Infrastructure under the Impact of Urban Densification: Taguchi’s DoE Approach

Abstract Densification is a common strategy to cope with the growing demands of urban residential needs around the world. The process involves densifying the existing neighborhoods to restrict urban expansion in the outskirts. The functional capability of a modern city is largely dependent on buried water infrastructure (BWI). Densification implies an increase in drinking water demand, wastewater generation, and water-impervious areas, which increases the vulnerability of existing BWI. Eventually, the increase in densification weakens BWI performance, which can be maintained by adjusting the level of densification and other controlling factors. This study optimizes the control factors to maximize the performance-to-densification ratio ( P / D ) using the Taguchi design of experiment (DoE) approach. An orthogonal array ( L 25 ) with five levels of six control factors is considered for analysis. Signal-to-noise ( S / N ) ratios are estimated for all experiments to find the optimal combination. A confirmation test is performed to validate the optimal combination by evaluating their S / N ratios. The S / N ratio of the optimum combinations of control factors for the response variable P / D is improved by 7.59 dB. Analysis of variance is also performed to find the percentage contribution of the control factors to the response variable. The percentage of multifamily housing (MFH), average daily water demand (ADD), average age of water mains ( AA ), and total cost ( TC )control factors are identified as statistically significant on the response variable with a P -value >97%. A comparison between the results of optimization for the response variable performance and P / D indicates that (1) a decrease in the consumption of ADD and a better condition of AA can improve BWI performance, reducing the overall densification impacts; indicates (2) a reduction in financial burden (i.e., TC ) at the same level of MFH. The application of the adopted approach is demonstrated for a municipality located in British Columbia, Canada.