Maintenance strategy decision making leveraging facility past performance data in military dormitories



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Operations and maintenance (O&M) is the longest and most expensive portion of the facility lifecycle and accounts for over 60% of all costs. In the O&M phase, facility maintenance accounts for 19% of costs, yet many organizations adopt an ad hoc approach to maintenance planning and decision-making which costs billions of dollars a year in lost maintnenace productivity. Improving maintenance efficiency is important for owners and operators of buildings because of the costs and the impact that maintenance has on occupant comfort. Within the United States government, dormitories account for 8% of managed building space and are important to quality of life of assigned personnel. Therefore, maintenance of dormitories is an area that deserves special attention in maintenance decisions. Decision makers should leverage information that is already recorded across the building lifecycle to enhance maintenance efficiency. Understanding the most common problems and how to prevent them during design and preparing to respond to them during O&M is key knowledge for facility managers (FM). Being able to make budget decisions about preventative (PM) and corrective (CM) maintenance strategies and then monitor the effectiveness of these decisions provides a way to improve the efficiency of limited maintenance resources. Finally, knowing what factors are most important when deciding to renovate or overhaul facility systems in dormitories focuses FM decision making. FMs should leverage their work order database to reveal trends in common problems and to track the ratios of PM to CM to help guide maintenance budget decisions. By monitoring the amount of CM over the age of the building and looking at key decision factors, FMs can make better decisions about when to conduct renovations or upgrade major systems in their dormitory portfolio. This dissertation provides analysis of maintenance work orders to reveal common problems in military dormitories and establishes benchmarks for PM to CM ratios and CM densities as buildings age to enable better decisions. This dissertation intellectually contributes methods for implementing data mining and analysis of maintenance data and a method for determining critical factors in strategy decision making to improve dormitory maintenance.


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