Fluor taps into IBM Watson for digital transformation of EPC projects

With the help of IBM Watson technologies, Fluor is delivering an artificial intelligence solution to monitor the status of global megaprojects and drive project cost savings through predictive analytics
Fluor taps into IBM Watson for digital transformation of EPC projects Fluor taps into IBM Watson for digital transformation of EPC projects Fluor taps into IBM Watson for digital transformation of EPC projects Fluor taps into IBM Watson for digital transformation of EPC projects Fluor taps into IBM Watson for digital transformation of EPC projects

Large capital projects, especially in the energy and chemicals and mining and metals markets, are incredibly complex with enormous amounts of data, people and moving parts

Staff Reporter

Fluor Corporation is using artificial intelligence-based systems to predict, monitor and measure the status of engineering, procurement, fabrication and construction (EPC) megaprojects from inception to completion.

Fluor said its extensive 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.

Large capital projects, especially in the energy and chemicals and mining and metals markets, are incredibly complex with enormous amounts of data, people and moving parts that are constantly changing and need to be understood to keep a project on schedule and budget.

To gain insights from project data in nearly real-time and to understand the implications of changing factors, 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, working collaboratively with Fluor, these innovative tools help to identify dependencies and provide actionable insights by fusing thousands of data points across the entire life cycle 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. Fluor said it 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.

"Harnessing the power of data to make meaningful insights will alter how megaprojects around the world are designed, built and maintained," said Arvind Krishna, senior vice president and director of IBM Research. "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."

Ray Barnard, Fluor's senior executive vice president of systems and supply chain, said: "The ability to rapidly analyse and comprehend big data that drives decisions at any point throughout the engineering, procurement, fabrication and construction of today's megaprojects is an imperative for the success of our company and the protection of our clients' capital investments.

"And to be the best at predictive analytics and project execution in our industry, we teamed with IBM to create EPHD and MD/SA, an advanced and effective set of diagnostic tools and capabilities that rapidly predict best-in-class pricing globally, project status and outcomes, and improves the quality of services and decision-making as we serve our clients around the globe."

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 modelling.

A 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 visualisation 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; 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.

Fluor said that as it continues on its global data-centric transformation journey, it plans to further develop and expand EPHD and MD/SA using analytics and artificial intelligence capabilities from IBM Watson and integrate them into Fluor's processes.

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