In the project, Fluor’s engineering, fabrication, construction and supply chain expertise is coupled with artificial intelligence and analytic technologies from IBM Watson. The result is big data analytics and diagnostic systems to help predict critical project outcomes and provide early insights into the health of projects.
For Fluor, large capital projects, especially in the energy and chemicals, and mining and metals markets, are very complex with enormous amounts of data, people and moving parts that are constantly changing yet 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 (EPHD) and the Market Dynamics/Spend Analytics (MD/SA) systems. Developed with IBM Research and IBM Services, working collaboratively with Fluor, these tools help to identify dependencies and provide actionable insights by fusing thousands of data points across the entire life cycle of capital projects.
Arvind Krishna, senior vice president and director of IBM Research, says: “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.”
Ray Barnard, Fluor’s senior executive vice president of systems and supply chain, says: “The ability to rapidly analyze 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.”
According to Fluor, 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 create learning models.
A user interface provides access to the data, reports and results of the analysis, using a natural language conversational interface that is sensitive to EPC domain. The system also provides 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.
Leslie Lindgren, Fluor’s vice president of information management, adds: “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.”
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 is also consulting experience from across its entire historical data store and global workforce to understand markets and monitor project factors impacting cost and schedule.
Fluor says it will continue to develop and expand EPHD and MD/SA using analytics and artificial intelligence capabilities from IBM Watson.