TITLE:
Investigation of Pile Construction and Productivity Loss: An Analysis of Macro Impact Factor
AUTHORS:
Minhaz Ahmed, Wang Xu
KEYWORDS:
Productivity Loss, Macro-Effect Factor, Pile Construction, Regression Model, SVR Model
JOURNAL NAME:
World Journal of Engineering and Technology,
Vol.11 No.4,
November
29,
2023
ABSTRACT: Pile foundations are challenging to build due to
subsurface obstacles, contractor ignorance, and difficulties with site
planning. Given the unpredictable environment of the construction site,
productivity losses during pile work are to be thought possible. Prior to
finishing a site pre-investigation, a foundation’s area is usually sampled for
statistical reasons. There are studies on pile construction outside of
Bangladesh that are supported by relevant empirical data in the literature.
Since Bangladesh, which is regarded as a third-world country, is ignored in
this regard, the literature currently available about pile building and the
associated productivity loss is unable to provide adequate information or
appropriate empirical data. Due to this pile-building sector in Bangladesh has
been experiencing a decline in production for quite some time now. Before
attempting to increase productivity in pile construction, it is essential to
investigate the potential losses and the variables that might have an
influence. This study aims to accomplish the following objectives: 1) identify
the primary factors that have an impact on pile construction; 2) develop an SVR
model that accurately predicts productivity loss; and 3) figure out the
projected loss by basing it on the historical scenario that is the most comparable
to the current one. A Support Vector Regression (SVR) model was developed after
a study of the relevant literature. This model enabled the collection of 110
pile building projects from five significant locations in Bangladesh. The model
was constructed using a list of eight inputs in addition to a list of five
macro elements (labor, management, environment, material, and equipment) (soil
condition, pile type, pile material, project size, project location, pile
depth, pile quantity, and equipment quantity). Using 10-way cross validation,
the SVR achieves an accuracy of 87.2% in its predictions. On the basis of what
has occurred in the past, we are able to estimate that there will be a loss of
around 18.55 percent of the total output. A new perspective for engineers
studying the delay factors with productivity loss is provided by the outcome of
important tasks as it relates to loss in productivity and overall factors
faced. In the building construction industry, effective management should place
more emphasis on the correlation between productivity loss and the factors that
cause it. Therefore, to represent the effect on productivity loss, real factors can be summed up as a decline
in productivity loss. The findings of the study would urge specialists to
concentrate on waste as a means of increasing overall production.