Framework for Modeling On-Site Productivity of Preventive Maintenance Activities for Wastewater Collection Systems

Preventive maintenance of drainage networks is an essential component of urban infrastructure management. Large cities require significant budgetary and other resources to perform the necessary prescheduled cleaning and flushing activities at various locations around the city at regular intervals. However, planning and scheduling of these activities can be challenging because of the wide variation of actual on-site flushing duration, which depends on a number of factors such as location, properties of the pipes, frequency of flushing, time of day, and season. This study develops a model for estimating the on-site duration of high pressure flushing (HPF), based on such predictor variables. The model is developed and validated using historical data from the City of Edmonton, where 5,500 km of network is maintained through more than 1,400 prescheduled preventive maintenance locations for HPF. The panel data set utilized in this study is obtained by integrating several databases, one of which is the historical data collected by the global positioning system (GPS) device installed in the flushing trucks. The framework presented here first uses ordered probit analysis to estimate the probability of a number of stops to flush a given set of pipes and then forecasts the flushing duration by means of a multiple regression model. This approach is applicable for similar municipalities and can be effectively used for resource optimization, maintenance scheduling, sensitivity analysis, and performance evaluation. (C) 2015 American Society of Civil Engineers.