An Integrated Decision Support Framework for Life-cycle Building Asset Management

Download or read book An Integrated Decision Support Framework for Life-cycle Building Asset Management written by Maha Reda Alkasisbeh and published by . This book was released on 2018 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building assets are essential to the economic, cultural, and historical growth of any nation. Examples of buildings include shelters, entertainment facilities, living spaces, teaching facilities, civil offices, parking structures, police buildings, libraries, and service areas used to accommodate human activity. Deterioration of building assets, inadequate renewal budgets, climbing deficits, and increasing demand levels are difficulties that face owners when managing building assets. The role of asset management has recently become significant in municipal governments for strategic, operational, and financial reasons. The main functions of an asset management system include assessment of the current condition, prediction of future deterioration, asset prioritization, selection of maintenance and repair strategies, and fund allocation. Many research efforts have been mostly focused on managing a few infrastructure asset types such as bridges, pavements, and underground utilities while neglecting building assets. However, properly managing building assets cannot be ignored as they suffer over time serious problems including deterioration, premature failures, and possibly the need for replacement. Additionally, the scarcity of and increasing demand for building materials, shortages of land and energy, and limited resources add to the need for effective building asset management. There are numerous types of assets that must be analyzed and categorized, presenting difficulties in the development of a universal management system for the different types of buildings. Each building type is complex with unique characteristics and numerous components that have different maintenance needs and requirements. Additionally, existing standard building classification systems lack specific requirements for effective building asset management such as asset location and asset attributes including condition and deterioration rates. These standard systems have priorities that are mostly focused on estimating costs during the design and construction phases, and do not necessarily align well with the needs of asset management. Consequently, an effective data-driven decision-making process is critical for proactively maintaining and ensuring the long-term sustainability of building assets. Defining asset management requirements in the early project stages and facilitating the integration of asset data collected during design and construction with building asset information are critical issues that must be addressed. Early efforts in data integration have focused on the design and construction phases without considering asset management requirements and processes. Therefore, the goal of the research effort in this dissertation is to develop a comprehensive framework for building asset management that will facilitate the integration of all life cycle phases. An automated decision support system for building asset management using building information modeling (BIM) and relational database management systems (DBMS) was developed. The system consists of a new building asset inventory model that is based on the work breakdown structure (WBS) principles, a multi-phase condition rating method, and a building asset DBMS that is integrated with the BIM model. The main contributions of this research include 1) developing a framework for asset management that integrates all life cycle phases of buildings; 2) eliminating duplicate data collection efforts and data redundancy, 3) improving the quality, integrity and timeliness of asset information; and 4) enhancing building asset performance through proactive maintenance or replacement decision making processes. The results and findings of this study could be the starting point for extensive work related to 1) as-built data that is needed for building asset management; 2) integrating the BIM-DBMS asset management with geographic information systems (GIS) to improve certain asset tracking such as underground utilities; and 3) examining the applicability of the proposed framework on other types of municipal assets such as roads, and bridges.