When a company that manufactures steel & steel products at more than 300 operating facilities primarily in North America and operating 26 circular-based steel mills—you’re expected to run like a well-oiled machine. Isn’t it? For this leading manufacturer, known for its annual production capacity of more than 27 million tons of steel and being North America’s largest recycler, processing approximately 20 million tons of ferrous scrap annually, even small inefficiencies had a big impact. Despite its scale, the company faced an operational bottleneck slowing down productivity.
The challenge wasn’t with the production lines, but what came before: quality inspection and cost estimation. Customers sent complex structural drawings—PDFs filled with joists, girders, and intricate specifications. Manually interpreting these visuals, plotting each component, and calculating estimates became a time-consuming and error-prone task. Skilled employees were spending hours redrawing designs and verifying dimensions instead of focusing on value-added engineering.
The result? Slower turnaround times, reduced employee productivity, and risk of costly inaccuracies in quoting. Despite being a forward-looking organization, their reliance on manual processes was holding them back in an increasingly digital world.
That’s when Acuvate stepped in—introducing AI-ML-driven automation to transform the inspection process. Let’s take a closer look at why the existing process was becoming unsustainable and how this automation, a digital transformation in steel industry, offered a clear path forward.
From Manual to Machine-Led: How Acuvate Automated Structural Analysis with AI-ML Driven Solution
What if structural estimation didn’t require hours of manual labour, dozens of engineering hours, and the risk of human oversight? What if joist and girder identification could be completed in seconds—accurately and at scale? That’s the opportunity Acuvate unlocked for this leading steel manufacturer.
Understanding the time drain and inefficiencies from manually reviewing structural PDFs, Acuvate introduced an intelligent automation layer using AI and machine learning. The solution was designed to interpret complex technical drawings with the precision & consistency only intelligent models could offer.
Here’s how the solution implemented by Acuvate worked:
- Smart Detection: A custom AI-ML model was trained to read and interpret PDF diagrams, instantly identifying the number, type, and length of the parts within the drawings, such as all key structural components—joists, girders, and their associated dimensions.
- Detail Extraction: The model accurately extracted specific details about these parts.
- Precise Counting: It calculated the total number of parts required from the design.
Contextual Mapping: The start and end points of each component were detected to support precise planning.
All this data was then transformed into a compatible format for the customer’s cost estimation software, enabling direct upload and instant quote generation. This automation removed the need for manual drawing and calculation, speeding up the process.
Powered by Roboflow and advanced ML model technologies, this shift didn’t just reduce processing time—it eliminated manual effort entirely, increased accuracy, and gave employees time to focus on higher-value tasks.
Acuvate AI solution for steel industry became more than just a tool—it redefined how the customer approached quality inspection, driving speed, precision, and operational impact setting an example for AI quality inspection in steel manufacturing with AI-driven cost estimation for steel projects.
Delivering Measurable Impact Through Intelligent Automation
For a company operating at the scale of being one of North America’s largest steel producer, even small improvements in process efficiency can drive massive gains. With Acuvate’s AI-powered quality inspection solution, the results were immediate and transformative—bringing clarity, speed, and accuracy to a once-manual and error-prone process.
Here’s how the business was impacted:
- 30% Reduction in Manual Effort: By eliminating the need to manually calculate part dimensions or draw components in software, teams reclaimed valuable time and minimized repetitive workload.
- Faster Estimations, Simplified Process: What previously required multiple steps and manual validation was now streamlined through intelligent data extraction—allowing faster quote generation and quicker project turnaround.
- Boosted Productivity: Automation of routine inspection tasks such as steel structure drawing automation and automated joist & girder identification meant employees could focus on more strategic responsibilities, resulting in higher output and reduced operational drag.
Significant Cost Savings: By reducing human error and optimizing workflows, the customer experienced notable cost reductions—cutting inefficiencies at every step of the estimation cycle.
This transformation wasn’t just about implementing a new technology of smart steel manufacturing with AI-ML. It was about equipping teams with a smarter way to work—where automation enhances capability, reduces friction, and amplifies business value at scale.
What began as a time-consuming, error-prone manual task was transformed into a streamlined, intelligent process—thanks to our AI-ML-powered solution. By understanding the customer’s unique needs and leveraging automation, Acuvate AI solution for steel industry not only improved operational efficiency but empowered teams to do more with less effort. This success story is a testament to what’s possible when innovation meets industry expertise.
If your business is facing similar challenges in quality inspection or other manual processes, Acuvate is ready to help you lead with intelligence.
Are you ready to transform your operations?
