International Journal of Application or Innovation in Engineering & Management
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ISSN 2319 – 4847
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Title: |
A maintenance cost prediction model for
elementary schools by correcting FM budget
history and performance data
|
Author Name: |
Chun-Kyong Lee, Yong-Il Jeon |
Abstract: |
Abstract
Daejeon Office of Education which is located in one of the 5 largest city in Republic of Korea, has 292 elementary, middle, and
high schools (total floor space of 2.45 million ?). About 70% of them was built more than 15 years before and they have spent
a total of KRW 113.5 billion pre a year (2008 ~ 2012 average) for facility improvement. The budget shortage occurs every year
due to the increase in the aged school facilities and the increase of the school facilities due to the construction of the new city.
We want to predict the maintenance cost through the performance data, but it is difficult to secure it because the data retention
period is five years.
In this study, based on the 30 year facility management budget history, we derive estimated maintenance cost from
performance data and predict a model for proper maintenance cost of school facilities (elementary school) by regression
analysis. Considering that the period of keeping the facility management budget data is not limited, ‘Estimated maintenance
cost from performance data’ is derived based on the maintenance budget data for the past 30 years, and regression analysis is
performed to calculate the ‘prediction model of maintenance cost’ and the error rate test for this prediction model and the
adequacy of the case application are verified. The results of this study can be used as an objective criterion for long-term
planning in school facilities, and realistic budgeting is possible.
Keywords: maintenance cost prediction model, facility management, educational facility, maintenance and repair costs |
Cite this article: |
Chun-Kyong Lee, Yong-Il Jeon , "
A maintenance cost prediction model for
elementary schools by correcting FM budget
history and performance data " , International Journal of Application or Innovation in Engineering & Management (IJAIEM),
Volume 6, Issue 5, May 2017 , pp.
084-094 , ISSN 2319 - 4847.
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