Predicting the Performance of Highway Project Using Gray Numbers

Earned Value Analysis is a methodology used to monitor project performance in terms of time, scope and cost and also to deal with uncertain situations that come within. Uncertainty is a part of construction project and sometimes these situations can cause a great loss in the project's success. Recently, to deal with uncertain situations a different approach has been developed to predict the project performance in a non-deterministic way, i.e., using gray interval numbers. A framework using gray interval numbers has been developed to predict the project performance and hence this study aims at using the framework to predict the performance of a real-life highway project of total duration of approximately 2 years. The analysis involves the verbal directed data from the site by the experts which were denoted as gray interval numbers. The results indicate that the project is under budget as the CPI is 1.06 and ahead of schedule as the SPI is 1.2. The results also show the worst case scenario that the project may exceed the budget as CPI is 0.83 and may run behind the schedule as SPI is 0.69. The outcomes of the study are in the form of range which provides the overall profile of the project and also helps the project team members to not always be accurate or deterministic with the outcomes. Since the construction sector was majorly hit by an uncertain event, i.e., COVID-19, this study can be very helpful in determining the performance after facing such a huge gap. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Predicting the Performance of Highway Project Using Gray Numbers

Earned Value Analysis is a methodology used to monitor project performance in terms of time, scope and cost and also to deal with uncertain situations that come within. Uncertainty is a part of construction project and sometimes these situations can cause a great loss in the project’s success. Recently, to deal with uncertain situations a different approach has been developed to predict the project performance in a non-deterministic way, i.e., using gray interval numbers. A framework using gray interval numbers has been developed to predict the project performance and hence this study aims at using the framework to predict the performance of a real-life highway project of total duration of approximately 2 years. The analysis involves the verbal directed data from the site by the experts which were denoted as gray interval numbers. The results indicate that the project is under budget as the CPI is 1.06 and ahead of schedule as the SPI is 1.2. The results also show the worst case scenario that the project may exceed the budget as CPI is 0.83 and may run behind the schedule as SPI is 0.69. The outcomes of the study are in the form of range which provides the overall profile of the project and also helps the project team members to not always be accurate or deterministic with the outcomes. Since the construction sector was majorly hit by an uncertain event, i.e., COVID-19, this study can be very helpful in determining the performance after facing such a huge gap. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A Risk Management Tool for Construction Sector India During Covid-19 Crisis

In construction industry, with the management of time and cost of the project, risk management is also especially important. Recently, COVID-19 pandemic has brought a huge crisis on construction sector. During this crisis, risk management becomes even more crucial to avoid further losses in the project. This study aims at identifying the risks involved in construction project during COVID-19 crisis, analyse them and develop a plan to bring the project back on schedule. Possible risks involved in construction sector due to COVID-19 are identified and defined. The risks are classified based on the categories like commercial risk, health and safety risk, completion risk etc. The project was analysed for all categories of risks using Expected Value Method (EVM) for statistical analysis. EVM evaluates the average outcome when the future events may or may not happen. Based on the analysis, Composite Likelihood factor, Composite Impact factor and risk severity has been computed. The EVM results shown that the commercial risk would be at a high level with a risk severity equals to 0.034 and completion risk would be at a low level with a risk severity equals to 0.003. Using this approach, the occurrence of risks at various stages of the project can also be predicted. EVM is found to be a convenient and accurate method to identify risks that might occur and prepare a contingency plan to avoid further losses. © 2023, Canadian Society for Civil Engineering.