AI-based big-data decision-making support systems for Korean contractor’s lifecycle project management of overseas Engineering-Procurement-Construction (EPC)

Abstract

Due to the failure of data management by engineering & construction companies, project managers do not receive reliable data analysis to make timely decisions. To solve these problems, we are developing AI-based engineering big data integration analysis support system. The system is based on a big data-based knowledge base that collects and builds various EPC engineering commercial and public data through Enterprise Resource Planning (ERP) or Project Management Information System (PMIS), and an engineering machine learning platform with various algorithms. We are developing intelligent decision-making applications such as Predicting design costs, analyzing design errors, analyzing change order, analyzing bidding documents, and Plant equipment prediction maintenance. This has the advantage of leading to project managers' preemptive response through project risk management and dashboards. The research team used ERP, PMIS, commercial data (RS Means, Richardson, CESK) and public data from the engineering & construction companies as the data source. The expertise (Lessons Learned) gained through this platform can open up to the public or sell to other companies.