Document Type
Article
Publication Date
11-29-2022
Publication Source
Buildings
Abstract
Planned Preventive Maintenance (PPM) and Unplanned Maintenance (UPM) are the most common types of facility maintenance. This paper analyzes current trends and status of Facility Management (FM) practice at higher education institutions by proposing a systematic data-driven methodology using Natural Language Process (NLP) approaches, statistical analysis, risk-profile analysis, and outlier analysis. This study utilizes a descriptive database entitled "Facility Management Unified Classification Database (FMUCD)" to conduct the systematic data-driven analyses. The 5-year data from 2015 to 2019 was collected from eight universities in North America. A preprocessing step included but was not limited to identifying common data attributes, cleaning noisy data, and removing unnecessary data. The outcomes of this study can facilitate the decision-making process by providing an understanding of various aspects of educational facility management trends and risks. The methodology developed gives decision makers of higher education institutions, including facility managers and institution administrators, effective strategies to establish long-term budgetary goals, which will lead to the enhancement of the asset value of the institutions.
ISBN/ISSN
2075-5309
Document Version
Published Version
Publisher
MDPI
Volume
12
Peer Reviewed
yes
Issue
12
eCommons Citation
Pampana, Ashish Kumar; Jeon, JungHo; Yoon, Soojin; Weidner, Theodore J.; and Hastak, Makarand, "Data-Driven Analysis for Facility Management in Higher Education Institution" (2022). Civil and Environmental Engineering and Engineering Mechanics Faculty Publications. 74.
https://ecommons.udayton.edu/cee_fac_pub/74
Included in
Civil Engineering Commons, Construction Engineering and Management Commons, Environmental Engineering Commons, Other Civil and Environmental Engineering Commons, Transportation Engineering Commons
Comments
This open-access article is provided for download in compliance with the publisher’s policy on self-archiving. To view the version of record, use the DOI:https://doi.org/10.3390/buildings12122094