Fuzzy- versus Simulation-Based Life-Cycle Cost for Sewer Rehabilitation Alternatives
Publication: Journal of Performance of Constructed Facilities
Volume 27, Issue 5
Abstract
The ample framework to maintain infrastructure remains the continuous challenge in efficiently carrying out municipal duties. In North America, aging municipal infrastructure has reached the breaking point. This results in a large excess of infrastructure rehabilitation activities and cost escalation. Life-cycle cost (LCC) analysis, which can effectively deal with data vagueness and judgmental appraisal, is essential to evaluate various alternatives of infrastructure rehabilitation, particularly for sewers. Therefore, the objective of the present research is to develop LCC models using fuzzy and simulation approaches that deal with vague, imprecise, qualitative, linguistic, or incomplete data. Deterioration and cost data are collected for two sewer materials—PVC and concrete—with diameter ranges from 150 to 600 mm. The developed LCC models, with the help of an automated Microsoft Excel–based program, are utilized to select the best rehabilitation alternatives/scenarios. Results show that open-trench/sleeve, slip-lining, and pipe-bursting scenarios have the lowest LCC in spot-repair, renovation, and replacement categories, respectively. The developed models help academics and practitioners (for example, municipal engineers) plan suitable new installation/rehabilitation programs and their associated costs to avoid any unpleasant surprises.
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References
Abraham, D. (2003). “Life cycle cost integration for the rehabilitation of wastewater infrastructure.” Proc., Const. Research Congress, ASCE, Reston, VA.
American Water Works Association (AWWA). (2001). Manual of water supply practices: Rehabilitation of water mains, M28, 2nd Ed., American Water Works Association, Denver.
American Water Works Service (AWWS). (2002). “Deteriorating buried infrastructure management challenges and strategies.” Rep., U.S. Environmental Protection Agency, Washington, DC.
Ammar, M., Zayed, T., and Moselhi, O. (2013). “Fuzzy-based life-cycle cost model for decision making under subjectivity.” J. Constr. Eng. Manage., 139(5), 556–563.
Arditi, D., and Messiha, H. (1996). “Life-cycle costing in municipal construction projects.” J. Infrastruct. Syst., 2(1), 5–14.
ASCE. (2009). “Report card for America’s infrastructure.” 〈https://apps.asce.org/reportcard/2009/grades.cfm〉 (Apr. 20, 2010).
Ashworth, A. (1996). “Estimating the life expectancies of building components in life-cycle costing calculations.” Struct. Surv., 14(2), 4–8.
Byrne, P. (1995). “Fuzzy analysis: A vague way of dealing with uncertainty in real estate analysis?” J. Property Valuation Investment, 13(3), 22–41.
Chughtai, F., and Zayed, T. (2008). “Infrastructure condition prediction models for sustainable sewer pipelines.” J. Perform. Constr. Facil., 22(5), 333–341.
C. N. Watson and Associates (CNWA). (2010). “Municipality of Port Hope water and wastewater rate study.” Rep. CP-3, CNWA, Mississauga, ON.
Dillon Consulting and Harfan Technologies. (2003). “City of Moncton water main transmission and distribution system needs assessment study.” Rep. 02-0904-0700, Moncton, Canada.
Dong, W., and Shah, H. (1987). “Vertex method for computing functions of fuzzy variables.” Fuzzy Sets Syst., 24(1), 65–78.
Dong, W., Shah, H., and Wong, F. (1985). “Fuzzy computations in risk and decision analysis.” Civ. Eng. Syst., 2(4), 201–208.
Edwards, P., and Bowen, P. (1998). “Practices, barriers and benefits of risk management process in building services cost estimation: Comment.” Construct. Manag. Econ., 16(1), 105–108.
El-Assay, A., Ng, H., Chua, K., Yong, C., Ariarathnam, S., and Ruwanpura, J. (2006). “Cost forecast model for sewer infrastructure network in Edmonton.” 1st Int. Construction Specialty Conf., Canadian Society of Civil Engineers (CSCE), Calgary, AB, Canada.
Federation of Canadian Municipalities (FCM). (2007). “The coming collapse of Canada’s municipal infrastructure.” 〈www.fcm.ca〉 (Apr. 22, 2009).
Ferrari, P., and Savoia, M. (1998). “Fuzzy number theory to obtain conservative results with respect to probability.” Comput. Methods Appl. Mech. Eng., 160(3–4), 205–222.
Heavens, John W. (1999). “Rehabilitation of water mains by trenchless renovation.” 1999 Int. Public Works Congress and Exposition, ASCE, Reston, VA, 160–170.
Jones, M. P. (1992). “Review of current UK techniques for rehabilitating water mains: Water resources planning and management saving a threatened resource—In search of solutions.” Proc., Water Resources Sessions at Water Forum, ASCE, New York, 764.
Kishk, M., and Al-Hajj, A. (2002). “A fuzzy model and algorithm to handle subjectivity in life cycle costing based decision-making.” J. Financial Man. Property Construction, 5(1–2), 93–104.
Kleiner, Y., Adams, B., and Rogers, J. (2001). “Water distribution network renewal planning.” J. Comput. Civ. Eng., 15(1), 15–26.
Lorterapong, P., and Moselhi, O. (1996). “Project-network scheduling using fuzzy set theory.” J. Constr. Eng. Manage., 122(4), 308–318.
Najafi, M., and Kim, K. O. (2004). “Life-cycle-cost comparison of trenchless and conventional open-cut pipeline construction projects.” Proc., ASCE Pipeline Division Specialty Congress—Pipeline Engineering and Construction, ASCE, Reston, VA, 635–640.
National Guide to Sustainable Municipal Infrastructure (NGSMI). (2003). “Selection of technologies for sewer rehabilitation and replacement.” Rep. for InfraGuide Best Practice Document No. 1.0.
O’Day, D. K. (1992). “Water main rehabilitation needs for the 1990's: Water resources planning and management: Saving a threatened resource—In search of solutions.” Proc., Water Resources Sessions at Water Forum, ASCE, New York, 760.
Rajani, B., and Kleiner, Y. (2004). “Alternative strategies for pipeline maintenance/renewal.” AWWA 2004 Annual Conf., American Water Works Association, Denver, 1–16.
Ross, T. (1995). Fuzzy logic with engineering applications, McGraw Hill, New York.
Shahata, K., and Zayed, T. (2013). “Simulation-based life cycle cost modeling and maintenance plan for water mains.” J. Structure Infrastruct. Eng., 9(5), 403–415.
Shaheen, A., Fayek, R., and AbouRizk, S. (2007). “Fuzzy numbers in cost range estimating.” J. Constr. Eng. Manage., 133(4), 325–334.
Sobanjo, J. (1999). “Facility life-cycle cost analysis based on fuzzy set theory.” 8th Int Conf. on Durability of Building Materials and Components, Vancouver, Canada, Vol. 3, National Research Council Canada, Vancouver, Canada, 1798–1809.
Vinpulanandan, C., and Pansari, G. (2005). “Life cycle cost model (LCC-CIGMAT) for wastewater system.” Proc., Pipeline Division Specialty Conf., Houston, 740–751.
Water Environment Federation and American Society of Civil Engineers (WEF and ASCE). (1994). “Existing sewer evaluation and rehabilitation.” WEF manual of practice FD-6 and ASCE manuals and reports on engineering practice no. 62, 2nd Ed.
Woodward, D. (1997). “Life cycle costing—Theory, information acquisition and application.” Int. J. Proj. Manag., 15(6), 335–344.
Zadeh, L. (1965). “Fuzzy sets.” Inf. Control, 8(3), 338–353.
Information & Authors
Information
Published In
Journal of Performance of Constructed Facilities
Volume 27 • Issue 5 • October 2013
Pages: 656 - 665
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Oct 14, 2011
Accepted: Apr 3, 2012
Published online: Sep 16, 2013
Published in print: Oct 1, 2013
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