An effective approach for assessing risk of failure in urban sewer pipelines using a combination of GIS and AHP-DEA

Abstract The urban sewer pipeline network is a vital urban infrastructure that is highly at risk of failure and its deterioration can be harmful to the environment and public health and safety. Therefore, for performing an effective rehabilitation program, it is needed to prioritize the sewer pipelines. In this paper, a novel risk assessment approach is proposed for prioritizing sewer pipelines based on a combination of Geospatial Information System (GIS) and Analytic Hierarchy Process (AHP)- Data Envelopment Analysis (DEA). To do so, it calculates the Probability of Failure (PoF), along with the Consequence of Failure (CoF) for the sewer pipelines. Bayesian Network (BN) as the probabilistic method is used to calculate PoF. The main contribution of the study lies in using a combination of GIS, AHP, and DEA for quantitatively assessing the CoF, firstly, the criteria weights are determined by the AHP method through experts’ judgments. Then, GIS functionalities along with DEA, are used to calculate scores for the alternatives. Finally, the outputs of the AHP method are integrated with the outputs of the DEA method in order to calculate CoF. The proposed method is applied to a local sewer pipeline network as a real-world case study to assess its risk of failure. The results indicated that the sewer pipelines are in good condition in the study area and among 1605 sewer pipelines, only 48 of them (about 3 %) are in a critical situation that it is needed to perform rehabilitation program.

[1]  Ossama Salem,et al.  Risk Assessment of Wastewater Collection Lines Using Failure Models and Criticality Ratings , 2012 .

[2]  Tarek Zayed,et al.  Condition assessment model for sewer pipelines using fuzzy-based evidential reasoning , 2018 .

[3]  R. B. Kulkarni,et al.  Analytical techniques for selection of repair-or-replace options for cast-iron gas piping systems--Phase I. Topical report, March 1985-June 1986 , 1986 .

[4]  Tarek Zayed,et al.  Infrastructure Condition Prediction Models for Sustainable Sewer Pipelines , 2008 .

[5]  Solomon Tesfamariam,et al.  Earthquake disaster risk index for Canadian cities using Bayesian belief networks , 2012 .

[6]  Danilo Nicola Dongiovanni,et al.  Failure rate modeling using fault tree analysis and Bayesian network: DEMO pulsed operation turbine study case , 2016 .

[7]  Hongwei Zhu,et al.  Quantitative risk analysis on leakage failure of submarine oil and gas pipelines using Bayesian network , 2016 .

[8]  R. A Fenner,et al.  Approaches to sewer maintenance: a review , 2000 .

[9]  Teemu Kokkonen,et al.  Estimating water and wastewater pipe failure consequences and the most detrimental failure modes , 2018 .

[10]  Anthony Kenneth Charles Beresford,et al.  Evaluating the efficiency performance of airports using an integrated AHP/DEA-AR technique , 2015 .

[11]  Mauricio Sánchez-Silva,et al.  Integrity assessment of corroded pipelines using dynamic segmentation and clustering , 2019, Process Safety and Environmental Protection.

[12]  Massoud Tabesh,et al.  Integrated risk assessment of urban water supply systems from source to tap , 2013, Stochastic Environmental Research and Risk Assessment.

[13]  S Syachrani,et al.  Advanced criticality assessment method for sewer pipeline assets. , 2013, Water science and technology : a journal of the International Association on Water Pollution Research.

[14]  Varun Kumar Ojha,et al.  Identifying hazardousness of sewer pipeline gas mixture using classification methods: a comparative study , 2016, Neural Computing and Applications.

[15]  Prakash P. Shenoy,et al.  Using Bayesian networks for bankruptcy prediction: Some methodological issues , 2007, Eur. J. Oper. Res..

[16]  W. Cook,et al.  A data envelopment model for aggregating preference rankings , 1990 .

[17]  Mohammad Taleai,et al.  Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process , 2017, J. Geogr. Syst..

[18]  Zilla Sinuany-Stern,et al.  Combining ranking scales and selecting variables in the DEA context: the case of industrial branches , 1998, Comput. Oper. Res..

[19]  Yihai He,et al.  Big Data-Oriented Product Infant Failure Intelligent Root Cause Identification Using Associated Tree and Fuzzy DEA , 2019, IEEE Access.

[20]  Tarek Zayed,et al.  Defect-Based ArcGIS Tool for Prioritizing Inspection of Sewer Pipelines , 2018, Journal of Pipeline Systems Engineering and Practice.

[21]  Richard N. Palmer,et al.  Expert System for Prioritizing the Inspection of Sewers: Knowledge Base Formulation and Evaluation , 2002 .

[22]  Faisal Khan,et al.  Failure probability analysis of the urban buried gas pipelines using Bayesian networks , 2017 .

[23]  HarveyRobert Richard,et al.  Predicting the structural condition of individual sanitary sewer pipes with random forests , 2014 .

[24]  K. Bi,et al.  An AHP/DEA method for measurement of the efficiency of R&D management activities in universities , 2004 .

[25]  Dulcy M. Abraham,et al.  Estimating Transition Probabilities in Markov Chain-Based Deterioration Models for Management of Wastewater Systems , 2006 .

[26]  Jun Liu,et al.  An integrated AHP-DEA methodology for bridge risk assessment , 2008, Comput. Ind. Eng..

[27]  William M. Bowen,et al.  Subjective judgements and data envelopment analysis in site selection , 1990 .

[28]  Enrico Zio,et al.  Risk-based optimization of pipe inspections in large underground networks with imprecise information , 2016, Reliab. Eng. Syst. Saf..

[29]  Solomon Tesfamariam,et al.  Evaluating risk of water mains failure using a Bayesian belief network model , 2015, Eur. J. Oper. Res..

[30]  Jukka Korpela,et al.  Warehouse operator selection by combining AHP and DEA methodologies , 2007 .

[31]  Tarek Zayed,et al.  Structural Condition Assessment of Sewer Pipelines , 2010 .

[32]  Da Ruan,et al.  Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems , 2006, Inf. Sci..

[33]  Abdollah Hadi-Vencheh,et al.  A fuzzy AHP-DEA approach for multiple criteria ABC inventory classification , 2011, Expert Syst. Appl..

[34]  Zilla Sinuany-Stern,et al.  An AHP/DEA methodology for ranking decision making units , 2000 .

[35]  Massoud Tabesh,et al.  Risk assessment model to prioritize sewer pipes inspection in wastewater collection networks. , 2017, Journal of environmental management.

[36]  Mahmoud R. Halfawy,et al.  Integrated Decision Support System for Optimal Renewal Planning of Sewer Networks , 2008 .

[37]  Pierre-Alexandre Château,et al.  Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project , 2015, Reliab. Eng. Syst. Saf..

[38]  Yihai He,et al.  Risk-oriented assembly quality analysing approach considering product reliability degradation , 2018, Int. J. Prod. Res..

[39]  William Ho,et al.  Integrated analytic hierarchy process and its applications - A literature review , 2008, Eur. J. Oper. Res..

[40]  Tariq Shehab-Eldeen.  An automated system for detection, classification and rehabilitation of defects in sewer pipes , 2001 .

[41]  Taha Ashoori,et al.  Sewer Pipes Condition Prediction Models: A State-of-the-Art Review , 2019, Infrastructures.

[42]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[43]  Brajesh Dubey,et al.  A risk-based approach to sanitary sewer pipe asset management. , 2015, The Science of the total environment.

[44]  Solomon Tesfamariam,et al.  Statistical Inference of Sewer Pipe Deterioration Using Bayesian Geoadditive Regression Model , 2019, Journal of Infrastructure Systems.

[45]  Mohamed A. Ismail,et al.  Developing a road performance index using a Bayesian belief network model , 2011, J. Frankl. Inst..

[46]  John C. Matthews,et al.  Wastewater Pipe Condition Rating Model Using Multicriteria Decision Analysis , 2019 .

[47]  John C. Matthews,et al.  Consequence-of-Failure Model for Risk-Based Asset Management of Wastewater Pipes Using AHP , 2019, Journal of Pipeline Systems Engineering and Practice.

[48]  Barry J. Adams,et al.  Methodology for Bayesian Belief Network Development to Facilitate Compliance with Water Quality Regulations , 2010 .