Knowledge-assisted BIM-based visual analytics for failure root cause detection in facilities management

This paper investigates a knowledge-assisted BIM-based visual analytics approach for failure root-cause detection in FM and utilizes BIM visualization capabilities to provide FM technicians with visualizations that allow them to utilize their cognitive and perceptual reasoning for problem solving.

Abstract

Facilities managers need to identify failure cause–effect patterns in order to prepare corrective and preventive maintenance plans. This task is difficult because of the complex interaction and interdependencies between different building components. Standardization based on Building Information Modeling (BIM) provides new opportunities to improve the efficiency of facilities management (FM) operations by sharing and exchanging building information between different applications throughout the lifecycle of the facilities. This paper aims to utilize BIM visualization capabilities to provide FM technicians with visualizations that allow them to utilize their cognitive and perceptual reasoning for problem solving. It investigates a knowledge-assisted BIM-based visual analytics approach for failure root-cause detection in FM. For this purpose, the inspection and maintenance data of Computerized Maintenance Management System (CMMS) are integrated with a BIM. Moreover, various sources of building knowledge such as fault trees and relationships between components are formally represented. These resources are used to create custom visualizations through an interactive user interface which helps in exploiting the heuristic problem solving ability of field experts to find root causes of failures in a building.