1/11/2024 0 Comments Realtimes installer![]() A BIM model is used as reference to provide pipe system component information. This paper proposes a new AI framework with machine learning (ML) and heuristic optimization techniques for automating practical pipe system installation schedule generation and optimization. Artificial intelligence (AI) maximizes the value of data by learning from previous cases and facilitates decision-making by making the process smarter and automatic. To effectively improve the installation schedule, current knowledge of the installation site situation is important, with this knowledge being used to generate realistic schedules. Thus, the process is still fragmented and essentially manual, with inefficient information flow. Current approaches are time-consuming, not automated and do not provide real-time schedules. During the installation stage, there can be delays or interference that could lead to the failure of the initial schedule plan. This is of particular importance in the installation of pipe systems, for which it is time consuming to plan and coordinate between team members the detailed requirements and information for the generation of practical installation schedules. Real time scheduling is an important and necessary task in the planning and execution of construction projects. Piping systems, which are used in many infrastructure systems such as the distribution networks for utilities – water, sewage, gas, oil, etc., are very important in this regard. ASCE., Dean and ProfessorĬollege of Design, Construction and Planning, University of Florida, Gainesville, Florida, systems in the United States are aging and considerable investment is needed to renew and replace a significant proportion of the existing systems. ![]() Jyoti Singh, Ph.D., Post-Doctoral Associate,Ĭollege of Design, Construction and Planning, University of Florida, Gainesville, Florida, J. ![]() 173-190, Real-time pipe system installation schedule generation and optimization using artificial intelligence and heuristic techniques DOI:
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