Analyzing the Long-Term Service Life of MEP Using the Probabilistic Approach in Residential Buildings

Sanghyo Lee,Yonghan Ahn

doi:10.3390/su10103803

Abstract

Establishing an effective long-term maintenance plan is essential to ensure the sustainability of a building. Among the various components of a building, the mechanical, electrical, and plumbing (MEP) components are complexly affected by various parameters, such as quality and user pattern, with respect to the service life. Besides, these components are replaced at different points in time, which becomes one of the main risks when establishing a maintenance plan for the building. Therefore, it is very important to consider the uncertainty in calculating the service lives of MEP components in a systematic and reasonable way. This study aims to systemize the MEP components of residential buildings and analyze their service life patterns using a probabilistic approach for long-term maintenance planning. The analysis was performed on 54,318 maintenance cases from 1998 to 2017 at 65 twenty-five-year-old rental apartment buildings in South Korea. Before performing the analysis, a service life matrix was established by classifying the MEP components into 12 types and setting the service life time at 6–25 years. Then, the service life distribution was derived for each MEP component. The probabilistic approach can provide information for rational maintenance decision-making regarding each MEP component as well as basic service life settings. Since the performance of the MEP components deteriorates due to various reasons, de facto uncertainty exists in the service life of each component; thus, the probabilistic approach can serve as an important decision-making method. If probabilistic methods are developed by acquiring the cost data in addition to the frequency of maintenance activity used in this study, a more effective long-term maintenance plan can be established.

Highlights

The importance of building maintenance is emphasized around the world [1,2] because of the growing complexity of buildings, the increasing proportion of systems in the buildings, higher levels of service, and the higher portion of maintenance costs in the life cycle costs of buildings [3].In particular, about 30–40% of the total natural resources that are used in industrialized countries are exploited by the building industry
This study aims to derive the implications of long-term maintenance planning that reflects uncertainties using the periodic maintenance frequency data for the MEP components of residential buildings
54,318 maintenance activity data were acquired for 65 twenty-five-year-old residential buildings in South Korea and the frequency distributions were derived based on a probabilistic approach to overcome the limitations of the conventional deterministic methods and reflect the uncertainties in the service life times of MEP components

Summary

Introduction

The importance of building maintenance is emphasized around the world [1,2] because of the growing complexity of buildings, the increasing proportion of systems in the buildings, higher levels of service, and the higher portion of maintenance costs in the life cycle costs of buildings [3].In particular, about 30–40% of the total natural resources that are used in industrialized countries are exploited by the building industry. Energy wastage, emissions, and environmental impacts due to buildings are expected to increase in the few years, an effective strategy for monitoring and managing the building industry is urgently required [6]. Effective maintenance of the building performance can minimize the adverse effects of buildings on the environment in terms of energy consumption, carbon dioxide emissions, and waste generation [7,8,9]. From this perspective, establishment of a proper maintenance plan is important for maintenance managers [10]

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