Offshore staff
IRVING, Texas and ARMONK, New York – Fluor Corp. and IBM have developed artificial intelligence-based systems to predict, monitor, and measure the status of engineering, procurement, fabrication, and construction (EPC) of megaprojects from inception to completion.
Fluor’s engineering, fabrication, construction and deep supply chain expertise, coupled with artificial intelligence and analytic technologies from IBM Watson, forms the foundation for big data analytics and diagnostic systems that help predict critical project outcomes and provide early insights into the health of projects.
Fluor has introduced the EPC Project Health Diagnostics (EPHDsm) and the Market Dynamics/Spend Analytics (MD/SAsm) systems. Developed with IBM Research and IBM Services, these tools help to identify dependencies and provide actionable insights by fusing thousands of data points across the entire life cycle of capital projects.
The company selected IBM Research and IBM Services to assist in the development of these advanced systems as part of its global data-centric transformation strategy. Fluor can now leverage a wealth of experience from across its entire historical data store and global workforce to quickly understand markets and monitor project factors impacting cost and schedule to drive improved certainty and cost efficiency across the entire project scope.
Arvind Krishna, senior vice president and director of IBM Research, said: “Harnessing the power of data to make meaningful insights will alter how megaprojects around the world are designed, built, and maintained.
“Together with IBM, Fluor is embracing artificial intelligence as an engine for transformation in data-driven industries that are ripe for innovation including energy and chemicals, and mining and metals construction projects.”
The EPHD and MD/SA systems are designed to transform complex data into actionable business insights using domain-driven semantic models to guide artificial intelligence-based predictive and diagnostics modeling. A unique feature of the systems is the blending of data with domain expertise to learn models that are operationally insightful. An advanced cognitive user interface provides seamless access to the data, reports and results of the analysis, using EPC domain-sensitive natural language conversational interface. The underlying domain understanding is used to guide project diagnostics and provide natural language summaries based on the reports, with data visualization techniques to ease its quick consumption and understanding.
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
• 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.
The company plans to further develop and expand EPHD and MD/SA using analytics and artificial intelligence capabilities from IBM Watson and integrate them into its processes.
Leslie Lindgren, Fluor’s vice president of Information Management, said: “Besides the work Fluor was already doing on predictive maintenance and construction sequencing, five years ago we began investing in predictive analytics and artificial intelligence capabilities to further evaluate performance and determine critical project outcomes as a part of our data-centric journey.
“We will be using these innovations on select large and megaprojects to quickly discover trends, patterns and meaning in our structured and unstructured data that deliver competitive advantage through the digital transformation of data into critical information with significant benefits to our clients, other stakeholders and our company.”
09/14/2018
