Identification of Business Intelligence in Managing Maintenance Management

IDENTIFICATION OF BUSINESS INTELLIGENCE IN MANAGING MAINTENANCE MANAGEMENT JOB FUNCTIONS FOR FEDERAL GOVERNMENT OFFICE BUILDINGS IN PUTRAJAYA

Project Leader

Dr. Siti Hajar Othman

Team Members

Dr. Muhammad Najib Mohamed Razali

Assoc. Prof. Dr. Yasmin Mohd. Adnan

Dr. Nurul Hana Adi Maimun

Sr. Ts. Siti Hafsah Zulkarnain

Research Assistant

Ain Farhana Jamaludin

ABSTRACT

This research attempts to assess the significance of big data applications in the maintenance management for government buildings in Putrajaya. By using theoretical aspects of big data analytics, especially implementation in other areas such as medical and engineering, valuable information and knowledge is able to be discovered from the asset maintenance. By integrating the concept of big data and business analytics with maintenance data and knowledge management to produce data analytics, there is a comprehensive closed-loop mechanism of maintenance management for the maintenance management job function. The big data analytics’ output also utilises empirical analyses by using VECM Granger causality and PCA. This research aims to utilise data management in maintenance management by employing big data analytics as a background of the study. This is a relatively new concept, especially in the maintenance management area. Although the government through JKR has developed mySPATA to coordinate all maintenance data in Putrajaya, nevertheless through the examination of the system, it was revealed that the system is a stand-alone system, which is not dynamic. It is merely a repository system to collect all data from all vendors. With the current data management situation, it is essential for the researchers to collect all maintenance data and transform it into more systematic, data which are able to meet the big data concept, comprising of value, velocity, veracity and volume (4Vs). The main challenge in maintenance management in Putrajaya is that data are handled manually and are not well- managed. Therefore it is crucial for data management of maintenance to be stored in a systematic way. In other words, it needs a more efficient process right from the beginning of the data management process.

The significance of this research is demonstrated through the utilisation of big data analytics with the main domain being maintenance management. This research utilises the method of a data capturing technique by employing econometrics’ analyses. The outputs have provided potential reasons to enhance the data management of maintenance management in Putrajaya where the government offices are located. The analytical tools which provide data architecture and data transformation will transform the maintenance management job function into sophisticated functionalities. This will help facilitate maintenance management information integration. Maintenance is essential for a building in order to ensure the building is able to meet its requirements, namely safety, security, reliability, availability and quality. Therefore, the future of maintenance data management should be embodied within the concept of big data analytics with data organisation and functionalities. This research provides insight into the advantage of big data analytics’ concept in maintenance management and its feasibility to accelerate the implementation of fourth industrial revolution (Industry 4.0).

Keywords: Big Data, Maintenance, Management, Data, Putrajaya, Malaysia