The aim of this study is to develop a fuzzy inference model to
estimate the impact of change orders on the duration of
construction projects in Syria. This can help in obtaining the
optimal estimation of the increasing of the project duration caus
ed
by the changes. The capability of gradient estimation of the fuzzy
logic approach reduces the distrust of estimation using factor
assessment. Also it estimates the duration of the project after any
change.via the experts evaluation or according to the crisp logic.
Changes in construction projects are considered as prevalent phenomenon. Where,
most of projects face changes in drawings, specifications, work scope, or contractual
conditions.
The traditional construction followed in Syrian projects has a long t
ime span between
planning, design, and construction. As result the possibility of changes occurrence in any
project becomes considerable. There are many causes of change orders in construction
industry. These changes, mostly causes time and cost overrun and managerial
complications.
The objective of this study is determining the main causes of change orders;
arranging them according to their significance; and studying their effects on project’s cost
and time. The owner or the engineer supervising the project is the party who is responsible
for change orders in the project.
Many studies have tried to determine the impact of change orders on the cost and
time of the project, which in turn leads to differences and disputes between contractors and
owners. Where change orders dealt with in various engineering projects.
T
his search displays formal causes of change orders occurring during the life cycle of
the project in Syrian coastal zone. Particular building projects are studied, and the most
important impact on completion of the project indicators (cost_time) is discussed. Also
identifies the party responsible for the change, and shows the weak points during follow
the change order life cycle and provides recommendations for each of the responsible
parties, stressing the need to monitor performance in order to manage change order and
address the causes and impact alleviation. The prediction models were drafted at additional
cost that may result from change orders.
