Equipment logistics, maintenance, and repair are important aspects of construction equipment management. A well-managed equipment fleet helps reduce downtime, as well as total maintenance and repair costs. With quickly growing fleets of equipment, large contractors tend to divert the maintenance and repair of equipment from equipment managers to project managers. As a result, the equipment managers shift their attention from operational-level decision-making to corporate-level strategic decision-making regarding equipment management, which is often a challenging job with the current equipment management system. This paper presents an equipment data warehouse and a prototype decision support system (DSS). The proposed equipment data warehouse enables equipment managers to visually analyze the equipment fleet data from different perspectives and at various level of details. The data-warehouse-based DSS facilitates high-level, fact-based decision-making regarding equipment logistics, supplies, maintenance, repair, and replacement and has higher levels of performance and flexibility than the current equipment management system.
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Environmental Science(all)