Burj Khalifa pioneers Intelligent Asset Management Systems

Described as both a ‘Vertical City’ and ‘A Living Wonder,’ Burj Khalifa, developed by Dubaibased Emaar Properties PJSC, is a global icon. The tower is home to the world’s first Armani Hotel, 900 residential apartments, and 37 corporate suites. To meet the demands of this mega high rise, it is essential to achieve the greatest efficiency across all systems, making them reliable and fit to meet the requirements of all its occupants.

Burj Khalifa pushes the frontiers of engineering, mechanical and design expertise. To increase the reliability of the assets, the first step was to measure their criticality, operating profile and failure history. The previously used Computerized Maintenance Management System (CMMS) provided the required historical data to study failures, downtime and asset maintainability. In light of their criticality level, the associated maintenance tasks were reviewed and assessed using Reliability Centered Maintenance (RCM) techniques. The study revealed the causes of failure and what can be done to mitigate the root cause associated with each scenario. RCM studies were completed for all critical assets in Burj Khalifa and the maintenance tasks and their frequency were updated and optimised accordingly.

Adopting predictive maintenance regimes helped in increasing assets’ reliability. Knowing when the asset is about to fail, provides the maintenance staff with adequate time for planning any required downtime and fixing a potential challenge before the asset breaks down. As most of the tower’s assets are connected to the Building Automation System (BAS), we studied the possible alarms that can be generated from the systems and assigned a priority level to each alarm. This allowed the operators to prioritise alarms and escalate the same to Service Providers to formulate an action before the failure occurs.

While ensuring the assets remained reliable and robust, a great deal of attention was focused on optimising the use of energy. Burj Khalifa’s energy consumption is monitored on a daily basis to ensure the most efficient use of resources. The definition of the Internet of Things (IoT) may be very similar to the BAS with the exception of the analytical module. Burj Khalifa devised a mechanism to introduce an analytical ability to BAS and increase its intelligence level. The initial scenario was:

  • BAS generates an alarm and the same is displayed on the operator's screen
  • The operator calls the help desk and registers a Service Request (SR)
  • Helpdesk assigns the same to the relevant supervisor
  • The supervisor assigns to the available technician
  • The technician goes to site to diagnose the problem
  • He approaches the store to acquire the required tools and spares
  • Rectification is completed
  • Technician checks with BMS if alarm is at rest
  • Once complete, he provides feedback to helpdesk to help close the Work order (WO)

Note: The above procedure excludes a planned downtime for rectification.

The intelligent introduction of self-analysis that allowed an asset to diagnose itself reduced the maintenance cycle as follows:

  • The asset senses a fault analyzes the root cause and issues a WO directly to the technicians. The WO contains the required tools and spares required to rectify the fault. It will advise the technician and the relevant personnel on the planned downtime based on the operational requirements and the urgency of the fault.
  • Technician proceeds to rectify the fault on the preplanned slot.

The introduction of smart analytics has increased the productivity of the technicians and reduced downtimes. Overall, it has enhanced asset reliability, optimised maintenance tasks and frequencies while ensuring efficient use of energy and economic savings.

(The Author, Bashar Mohammad Kassab is the Director, HFM, Burj Khalifa & The Dubai Mall)

 

 

 
 
RELATED ARTICLES
 
 
 

BLOGGING POINT

Busting 5 Misleading Myths in FM Software

Adrian Jarvis, Director, FSI Middle East

 

FACILITY FOCUS

 

EXPERT TALK

Connected Buildings and Predictive Asset Optimisation

Sangeetha B, Deputy CEO, Al Fajer Facilities Management

 

DIRECTORY