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Abeid, J and Arditi, D (2003) Photo-net: an integrated system for controlling construction progress. Engineering, Construction and Architectural Management, 10(03), 162–71.

Duyshart, B, Walker, D, Mohamed, S and Hampson, K (2003) An example of developing a business model for information and communication technologies (ICT) adoption on construction projects - the National Museum of Australia project. Engineering, Construction and Architectural Management, 10(03), 179–92.

Luu, D T, Ng, S T and Chen, S E (2003) Parameters governing the selection of procurement system - an empirical survey. Engineering, Construction and Architectural Management, 10(03), 209–18.

Nassar, K (2003) Construction contracts in a competitive market: C3M, a simulation game. Engineering, Construction and Architectural Management, 10(03), 172–8.

Toakley, A R and Marosszeky, M (2003) Towards total project quality - a review of research needs. Engineering, Construction and Architectural Management, 10(03), 219–28.

Wirahadikusumah, R (2003) Application of dynamic programming and simulation for sewer management. Engineering, Construction and Architectural Management, 10(03), 193–208.

  • Type: Journal Article
  • Keywords: maintenance programmes; prediction; models; life cycle costing; dynamic modelling; simulation
  • ISBN/ISSN: 0969-9988
  • URL: http://titania.emeraldinsight.com/vl=1289930/cl=13/nw=1/rpsv/cw/mcb/09699988/v10n3/s4/p193
  • Abstract:
    This paper proposes a decision-making framework to assist asset managers in decision making regarding sewer maintenance/rehabilitation (M&R) plans under constraints of limited access to sewer condition data. It discusses the application of probabilistic dynamic programming in conjunction with a Markov chain model to analyze the life cycle cost of combined sewer systems. M&R issues have traditionally been addressed with a crisis-based approach, but this study contributes to sewer infrastructure management efforts in developing a management system based on life cycle cost analysis. The framework includes the optimal M&R techniques for sewer projects and the optimal times of application. The role of simulation is also explored to obtain the variability of the total cost. By knowing the expected costs and their variabilities, a deeper understanding of life cycle costs of sewer infrastructure can be obtained. The model's capability is enhanced further by testing its sensivitity to varying discount and inflation rates.