Chapter Project Management Information System (PMIS) Dashboard as a Digital Twin to Enhance Infrastructure Project Delivery: A Case Study of Ameroro Dam Project
Author(s)
Saputra, Rizky Agung
Fajarwanto, Agung
Widyastuti, Amy Rachmadhani
Munandar, Danang Aris
Setiawan, Herdy
Wardani, Sari Gita
Kadir, Abdul Rahman
Amar, Muhammad Yunus
Language
EnglishAbstract
In supporting the economic growth, Indonesian government has instructed to develop 201 National Strategic Infrastructure Projects, including Ameroro Dam Project. Located in Southeast Sulawesi, the construction process faced many engineering challenges with conventional monitoring methods, such as potentially delayed action plan and hindered decision making due to insufficient progress visualization data, inadequate real-time monitoring data, and unintegrated engineering data. Therefore, Project Management Information System (PMIS) dashboard is utilized as a Digital Twin innovation to overcome these challenges and optimize the project delivery. This study presents a case study approach on how PMIS could optimize the progress monitoring in Ameroro Dam Project. This PMIS Dashboard is integrated with Building Information Modelling, Digital Survey, Geospatial Data, and Project Management Data that supports the decision making as it provides more reliable data. This study illustrates the comparative study between conventional method and PMIS efficiency for a better project management. The effectiveness of PMIS can be seen as the integrated data is utilized to plan a construction working methods, along with monitoring the project schedule. Moreover, the visualization helps the engineers for a risk mitigation with the project performance display. Eventually, the paper concludes by the PMIS dashboard optimization for real-time progress monitoring in dam project, leading to more efficient infrastructure construction project management
Keywords
BIM; Digital Twin; Construction Working Methods; Geospatial Data; Progress Monitoring; Project ManagementDOI
10.36253/979-12-215-0289-3.120ISBN
9791221502893, 9791221502893Publisher
Firenze University PressPublisher website
https://www.fupress.com/Publication date and place
Florence, 2023Series
Proceedings e report, 137Classification
Virtualization