Life-Cycle Cost Analysis and Deterioration Model for Sewer Network in Baghdad

Abstract

Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. Because of that sewage systems suffer from neglect and deterioration.The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability and a life cycle cost analysis for the sewer networks in Baghdad city as well as give the top management appropriate decision making. The practical part includes the questionnaire, build four models and then design software . Different modeling techniques were used based on statistical methods such as discriminant, regression, and survival analysis also artificial neural network (ANN) was used to build the deterioration model. Three regions in Baghdad city were selected as case studies. The results of the discriminant model gave correct classification for the condition class of the sewer network 90.6, 91.8 and 68.9% for regions 1(part of AL Karkh), 2(part of AL-Rusafa) and 3(Zublin main line) respectively. The main significant variables influencing were sewer age, length, traffic, planning, performance and maintenance(Management function ). For the regression model, levels of planning, maintenance and function (combine or separate network) had significant influences. The model can explain 74.4, 91.6 and 83.1% of the sewer condition in regions 1, 2 and 3 respectively. The survival model estimated that at a probability of 0.4 the network will serve for 28 year in region 1. For region 2 with the probability of 0.2 the network will serve for 31 years and a probability of 0.3 in region 3, the network will serve for 40 years. From ANN the confusion matrix gave 74.1% in region 1 with a mean square error (MSE) of 0.07. In region 2 the confusion matrix gave 94.1% and MSE 0.08 where for region 3 the confusion matrix gave 76.7% and MSE 0.128. It was built as a life –cycle cost model by adding various costs which include installation cost, maintenance cost and demolition and add the impact of annual inflation to benefit top management to make decision .using these models a computer program was designed as the deterioration model which also included the total life cost for the network considered in the study. Models achieved high accuracy results and the program was useful to beneficiaries. The study found important recommendations in this area, including Continuous inspection of the sewer network and providing a good source of information for future planning.