EPC companies are struggling with costs and schedule overruns, resulting in their margins dwindling away. More and more are looking toward technical tools with artificial intelligence (AI) to help them better manage mega-projects. As an industry, construction has lagged in digital adoption, so most companies have yet to harness the power of AI. But those that do can, capture a competitive advantage in the market and quickly grow market share before others catch up.

According to Global Banking and Finance Review’s segment analysis for the industry, “The global Artificial Intelligence (AI) in Construction market is forecast to reach USD 4.51 Billion by 2026.” The capacity for AI to enhance performance across most areas of construction mega-projects is driving this growth.

The term ‘AI’ encompasses a vast software ecosystem which includes machine learning, data analytics, image recognition, autonomous equipment operators, and natural language processing. EPC firms will draw on any or all of these systems as a coordinated suite of AI capabilities. And when deployed, these systems will confer competitive advantages, including:

  • More reliable project planning
  • Faster project completion
  • Lower risk of schedule and cost overruns
  • Reduced human error
  • Lower labor costs
  • Improved safety records

1. Develop robust consistent designs more quickly.

Getting started with the right specifications greatly reduces the risk of cost and schedule overruns down the line. But with the complexity of EPC projects, it’s easy to accidentally bake flaws into the design that cause problems later.

AI systems are good at running endless simulations and combinations of solutions to find the optimal one. Engineers input constraints and requirements, and the AI iterates through alternatives, learning from each until it reaches the ideal option.

For EPC project design, AI can be used to create digital twins that let engineers experiment on different designs and determine the best fit to requirements. AI systems can also evaluate design specifications from different teams, identifying conflicts and generating alternate solutions.

2. Lower costs and save time in technical bid evaluation.

The technical bid evaluation (TBE) phase of a mega-project is time and labor-intensive. But much of the work is repetitive, which AI with natural language processing (NLP) can handle. NLP can be trained to read technical specifications and materials requisitions and draft digital packages for suppliers. AI can also create the TBE spreadsheet from requirements.

Once the bids are in, the NLP software digests the information and quickly pulls relevant details for each bid. It populates the TBE template with the information from each vendor, so engineers have an organized data set for comparison and selection.

With the AI handling much of the monotonous work, the team shaves weeks off the schedule and cuts hundreds of labor hours. Plus, the AI helps reduce human error and ensure nothing from requirements, submissions, or follow-up falls through the cracks.

3. Increase the reliability of planning and scheduling.

When AI is used to optimize design, it’s much easier to plan the project and schedule each phase because a good design helps avoid unexpected delays or unintended conflicts which require re-work. 
AI truly shines when it comes to scheduling. Project schedule optimizers evaluate millions of possible timetables quickly, selecting the best ones based on requirements and priorities.  
As a build progresses, machine learning applications take inputs from project progress, equipment downtime, supply chain factors, weather patterns, and past experience to determine whether a schedule is at risk of delay. These systems also take real-time input from worksites about worker and equipment availability, alerting managers to shortages. This fine-grained, on-going analysis of work activities and equipment usage helps EPC firms run a leaner team with less risk of blowing past deadlines.

4. Save labor costs in the building phase.

Because AI excels at handling laborious tasks that are usually relegated to humans, autonomous machines are starting to step in on the job site. They save time, reduce errors, and handle hazardous work during the building phase.

Autonomous equipment efficiently executes basic tasks such as excavation, demolition, pouring concrete, bricklaying, welding, and lifting. The vehicles are pre-programmed with engineering specifications, and engineers supervise the work to ensure quality.

3D printers also handle repetitive tasks. For example, they can construct walls onsite to save weeks of labor and speed up the schedule. Or offsite 3D manufacturers create custom parts that would otherwise have to be assembled and welded at the job site.

Natural language processing also pitches in during the project build phase. It assists in data entry for basic record keeping such as submittal logs and document closeouts. NLP can read timesheets and employee records as well to help ensure people with the right skills are available when needed.

5. Monitor projects in real-time to increase productivity.

Project monitoring is becoming more and more important for successful EPC projects. According to Deloitte’s 2021 Engineering and Construction Industry Outlook, 24% of E&C firms they surveyed are investing in monitoring by drones and other autonomous technology to increase worker productivity and efficiency.

Drones, cameras, and equipment trackers collect information that will feed back to AI systems which in turn scan for safety issues, schedule risks, or mismatches between design requirements and build. Managing engineers have early warnings about looming issues and can adjust as needed to avoid problems. The information can also be used to improve procedures, update site conditions, and enhance training.

Take the first steps to outpacing the competition.

With so many new technologies and AI-driven applications, it’s hard to take your first steps. Many AI-based initiatives involve dozens of moving pieces to collect data, train the AI, run the analysis, and decipher the results. But EPC companies can easily realize the benefits of AI with an application designed to fit neatly into a mega-project workflow, such as Mintmesh’s Rudy for Engineers.

Rudy for Engineers brings the power of AI to your TBE process without requiring major changes to your infrastructure. It uses a version of NLP customized for construction materials and requirements to manage the tedium of TBE – creating the templates, reviewing supplier submissions, populating the decision matrix, and drafting reports. In addition, it includes smart workflow management and data analytics.

With Rudy, companies looking for the advantages of AI can deploy it quickly and easily. From the first project, Rudy will save significant labor and time required for the TBE process and lay the groundwork for continued improvement and increased competitive strength.

Get ahead of the competition with AI you can deploy quickly. Learn more about Rudy today