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The construction industry’s use of simulation has greatly evolved since its introduction in the mid-70s. Aside from its use in day-to-day activities, it has been shown to be a vital tool for the transfer of specialized construction management knowledge and skills to students, which would otherwise have been acquired through a lengthy, risky, and expensive learning process on the jobsite. The construction industry has experienced considerable changes and development with respect to public ; client expectations, project size, and complexity, necessitating the delivery of graduates who are already proficient in managing construction projects. The paper shows Simphony.NET along with the functionality of its various modeling elements and discusses the various aspects of simulation taught in the course. As a simulation methodology, Cyclone has been widely used in the design and analysis of construction operation for over the last 20 years. Simphony simulation in General purpose templet as the implementation computer program of Cyclone, had a great contribution in the promotion of Cyclone. Traditional construction planning, which depends on historical data and heuristic modification, prevents the integration of managerial details such as productivity dynamics. Specifically, the distance between planning and execution brings cost overruns and duration extensions. To minimize variations, this research presents Simphony simulation framework for predicting productivity dynamics at the construction planning phase. To develop this framework, we examined critical factors affecting productivity at the operational level, and then forecast the productivity dynamics. The resulting plan includes specific commands for retrieving the required information from Simphony and executing operation simulations. It consists of the following steps: (1) preparing a symphony model to produce input data; (2) composing a construction simulation at the operational level; and (3) obtaining productivity dynamics from the symphony integrated simulation. To validate our framework, we applied it to a construction of swear line beneath the route model. By using GPM with construction operation simulations, we were able to create reliable construction plans that adapted to project changes. Our results show that the developed framework facilitates the reliable prediction of productivity dynamics, and can contribute to improved schedule reliability, optimized resource allocation, cost savings associated with buffers, and reduced material waste.

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