An Integrated Framework for Life Cycle Costing in Buildings

This paper summarises the difficulties in the application of life cycle costing (LCC) as a decision making tool in the construction industry on the parts of the client, the analyst and the industry practices. Life cycle costing encompasses a great deal of uncertainty, functions of which are data imperfection, randomness and ambiguity. The traditional use of the probability theory and statistics in LCC analyses could only deal with random uncertainty. This falls short from dealing with situations including incomplete information, human judgement and uncertainty. An integrated LCC framework is proposed. This framework is based on the simple idea that a complex problem may be deconstructed into simpler tasks. Then, the appropriate tools are assigned a subset of tasks that match their capabilities. The framework utilises statistics, fuzzy set theory and artificial neural networks to improve the quality of LCC as a decision making tool.