Any artificial intelligence (AI) researcher will tell you that AI does not replace human intelligence. For one thing, AI systems rely on the data and objectives they’re given to mimic human actions while humans draw on a wide range of experience, motivation, emotion, metaphor, and generalization to bring novel ideas to a problem.

Still, a trained AI system can complete some of the more repetitive and tedious EPC work just as a human would, leaving engineers free for in-depth design, analysis, and assessment of project outcomes. AI also helps engineers improve performance, plan for fewer mishaps, and drive smoother and faster EPC projects.

AI Improves Data Access

As EPC teams grow to include more partners and contractors, they need faster and easier data access. AI-driven search engines help engineers find the files they need quickly. It also powers expert locators, so people can connect to the right specialist when needed. Improved data access saves the time people normally spend hunting around share drives and company directories. Plus, it lowers the likelihood of mistakes from accidentally using outdated documents.

AI Reads and Processes Project Documents

AI excels at collecting and analyzing huge amounts of information. For example, AI systems use engineering language processing (ELP) trained to “understand” EPC engineering terms. ELP software reads project documents such as requirements, material specifications, supplier bids, budgets, and schedules. It collects specific information and populates templates, creates reports, and updates statuses.

AI can also scan design files and highlight any deviations from the requirements. When there are stacks of complicated forms to review, such as in the technical bid evaluation (TBE) process, these systems save weeks of labor and present engineers with the details they need for high-quality decisions.

AI Facilitates Optimal Designs

AI systems help EPC engineers collect and manage the vast information required for planning and design. For example, autonomous machinery surveys construction sites and collects the data to create 3D maps and construction layouts. The information speeds initial planning and ensures accurate measurements.

AI also helps engineers explore design options. Most construction projects capture specifications in the building information model (BIM) framework. AI systems use the model to iterate through design variations, assessing them based on given success criteria and learning from each version until it reaches the optimal configuration. Engineers can use the process to explore possibilities for specific priorities, such as using newly developed materials, lowering carbon footprint, or minimizing environmental impact.

Smart Schedulers Manage Labor and Resource Logistics

Smart schedulers look at the required resources for each project phase and optimize the work plan. If supplies are delayed or workers call in sick, the scheduler revises the plan to keep the project running. These systems also carry out simulations for contingencies. If a permit is delayed or seasonal weather causes a backup, they can determine the best response ahead of time.

For on-site resources, AI coordinates with equipment sensors and inventory monitors. They scan the health and maintenance cycles of machinery to keep everything operating as needed. And they track supply levels, automatically replenishing when needed, to ensure each phase has the required materials.

Autonomous Vehicles Handle Repetitive or Dangerous Construction Tasks

At the construction site, self-driving equipment completes repetitive work such as pouring concrete, laying bricks, building walls, welding, and demolition. These machines handle tasks at dangerous heights or locations, allowing engineers to operate them from a safe distance. Engineers are less exposed to dust, vibrations, and projectiles, as well.

One person can manage several machines, so the team saves labor costs and work proceeds faster. Autonomous equipment also operates more efficiently than machines driven by humans do. For example, AI-based vehicles steer and break more smoothly, so parts and tires last longer, needing less maintenance and lowering costs.

AI Scans Site Data for Problems

Engineers don’t have the time to watch every build site all the time. But they may get surprised by problems they didn’t see coming. AI monitoring systems help avoid surprises by continually scanning for likely trouble.

Sensors, cameras, and data tags on equipment capture information, which AI software is trained to analyze. It can find impending issues, such as safety violations or conflicts between initial design and as-built specifications. Sensors also relay the location of equipment and its usage, which AI audits for anomalies. When problems do arise, engineers have time to address them before they spiral into cost and schedule overruns.

AI Identifies Performance Patterns and Trends

AI systems eat data. They collect the millions of minute details that make up each project and find patterns and trends that help EPC engineers predict how the next project will go and improve processes as needed. As noted in Construction Executive magazine, “Today, machine learning and predictive data analytics are being applied to aid and inform project stakeholders in making smart, actionable decisions throughout the entire construction project lifecycle.”

For example, AI software identifies situations which, in past projects, have resulted in unexpected expenses. It looks through data collected from ongoing projects to predict where those problem situations are likely to arise again. Then EPC engineers take steps to avoid them in the planning or build phases.

With AI-powered data analytics, engineers also get early warning of supply chain snarls or labor bottlenecks. And importantly, they know which site conditions are likely to cause safety hazards or accidents. Engineers have evidence-based guidance about where and how they can most effectively focus their attention.

How Rudy for Engineers is a TBE Engineer’s Best Friend

Rudy for Engineers applies the power of AI to the TBE process, deftly managing and processing requirements, bid packages, supplier bids, templates, and reports. Rudy’s customized engineering language processing reads internal and external documents, spreadsheets, and templates, extracting the important information and transferring the details to the TBE template for review.

Rudy also manages the workflow, coordinates communications between the TBE team, vendors, and contractors, and keeps all TBE documents in one place. With the Insight Hub’s data analytics, engineers can learn from past TBE phases to improve future ones.

Rudy’s AI transforms TBE from an arduous journey to an efficient, optimized process. It allows you to:

  • Save weeks of time and labor
  • Enjoy a single system of record with smart search
  • Free up your time by having Rudy take care of TBE knowledge management
  • Facilitate collaboration among partners and vendors
  • Analyze a progress dashboard for stakeholders and executives
  • Calculate predictive insights from past data

Take Rudy for a test run and experience the benefits with your team. Schedule a free demo here.