Case Study: The Use of Concrete Prefabricated Prefinished Volumetric Construction (PPVC) For the World Tallest Two Blocks of 56-Storey Residential Towers in Singapore

Authors

  • Wong, Seng TW-Asia Consultants Pte Ltd
  • Heng, Kim Huat TW-Asia Consultants Pte Ltd
  • Maey, Leow Geok Mui TW-Asia Consultants Pte Ltd
  • Tan, Teng Hooi Singapore University of Social Sciences

DOI:

https://doi.org/10.14738/tecs.122.16501

Keywords:

prefabricated prefinished volumetric construction, reinforced concrete composite structural wall system

Abstract

In an effort to minimize dependence on foreign labor and enhance productivity in the construction sector, Singapore's building industry is urged to adopt the Design for Manufacturing and Assembly (DfMA) approach, which shifts a significant portion of construction activities to an off-site, controlled manufacturing setting. The Prefabricated Prefinished Volumetric Construction (PPVC) method, a notable example of such technology, markedly reduces the need for on-site labor and accelerates construction processes. This paper discusses the pioneering use of a patented reinforced concrete composite structural wall system in erecting two 56-story residential towers, featuring an innovative approach where adjacent PPVC modules are connected by self-levelling concrete, resulting in a robust combined wall system. Through prototype testing, including compression and shear tests, the effectiveness of this system under various stresses was confirmed, making this development a landmark in the use of reinforced concrete modular construction for high-rise residential buildings. The project saw the final PPVC module installed in January 2022, leading to a Temporary Occupation Permit by March 2023.

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Published

2024-04-27

How to Cite

Wong, S., Heng, K. H., Maey, L. G. M., & Tan, T. H. (2024). Case Study: The Use of Concrete Prefabricated Prefinished Volumetric Construction (PPVC) For the World Tallest Two Blocks of 56-Storey Residential Towers in Singapore . Transactions on Engineering and Computing Sciences, 12(2), 174–194. https://doi.org/10.14738/tecs.122.16501