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http://dx.doi.org/10.6106/KJCEM.2018.19.5.003

An Uncertainty Analysis of Calculating Life Cycle Maintenance and Energy Costs for Technical Proposals  

Chung, Sung Young (The Graduate School of Housing and Urban Planning, Seoul National University of Science and Technology)
Kim, Sean Hay (School of Architecture, Seoul National University of Science and Technology)
Publication Information
Korean Journal of Construction Engineering and Management / v.19, no.5, 2018 , pp. 3-9 More about this Journal
Abstract
Although Life Cycle Cost (LCC) must be evaluated by experts, sometimes it may not allow a sufficient time for even the experienced LCC expert to make rational decisions. Therefore, it often ends with relatively comparing the final numbers. We have broken down 110 technical proposals that are actually bade and accepted for large construction projects, and then have analyzed the uncertainty of Maintenance and Energy (M&E) cost during building life cycle, which turns out be the most volatile factor in uncertainty of LCC. Also we suggest "Value Engineering Index (VEI)" - the reduced M&E cost that is normalized by the reduced first cost. It is analyzed that the most uncertain factors of the M&E cost include repair and replacement term differing from each project, duplicated repair and replacement, non-standard repair items, and site-specific energy cost. Eventually we propose a VEI population with a mean of 1.38 and a standard deviation of 1.19, which is obtained by individually and exclusively applying the uncertain factors of the M&E cost to the 35 standard sample of technical proposals. The LCC evaluators may be able to use the VEI population as the benchmark to select the technical proposal with the most reasonable LCC among many others in two suggested manners; the one is to deterministically calculate the probability of single VEIs, and the other is to stochastically calculate the probability of the VEIs where uncertainty is quantified.
Keywords
Life Cycle Cost; Value Engineering(VE); Technical Proposal; Uncertainty Analysis; Maintenance and Energy Cost;
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