Fluor Corp. and IBM Watson have announced the use of artificial intelligence (AI)-based systems to predict, monitor and measure the status of engineering, procurement, fabrication and construction (EPC) megaprojects from inception to completion.
The collaboration aims at improving big data analytics and diagnostic systems that help predict critical project outcomes and provide early insights into the health of projects.
Fluor is introducing the EPC project health diagnostics (EPHDSM) and the market dynamics/spend analytics (MD/SASM) systems.
Developed with IBM Research and IBM Services, these tools identify dependencies by fusing thousands of data points across the entire lifecycle of capital projects.
Fluor selected IBM Research and IBM Services to assist in the development of these advanced systems as part of its global data-centric transformation strategy.
These tools assess the status of a project by predicting issues such as rising costs or schedule delays based on historical trends and patterns; gaining earlier insights from many sets of complex factors across project execution; and identifying the root causes of issues and the potential impacts of changes as input to the decision-making process, including estimate analysis, forecast evaluation, project risk assessment and critical path analysis.
Read the article online at: https://www.hydrocarbonengineering.com/refining/14092018/fluor-uses-ibm-watson-for-megaprojects-predictive-analytics-capability/