AI‑Driven Sensing for the Modern Shop Floor: A Practical Guide
1:00 pm – 1:30 pm
1:00 pm – 1:30 pm
1:30 pm – 2:00 pm
Metal fabrication plants operate in demanding environments where safety, traceability, and quality directly impact profitability and customer satisfaction. This presentation explores how AI-based solutions are transforming fabrication operations through real-time personnel and equipment detection, intelligent material tracking, and automated quality monitoring.
Using computer vision, edge processing, and integrated industrial IT architectures, AI systems can detect unsafe conditions, prevent equipment conflicts, track work-in-process from receiving through shipping, and identify quality deviations at early stages. These technologies enable proactive decision-making, reduce incidents, minimize rework, and improve throughput.
The session will also outline practical deployment strategies, including integration with PLCs, MES, ERP, and existing camera infrastructure, demonstrating how fabrication plants can implement scalable AI solutions that deliver measurable improvements in safety performance, operational visibility, and product quality.
2:00 pm – 2:30 pm
This presentation explains how manufacturers are scaling AI visual inspection from traditional end-of-line quality gates into selective in-process control to reduce scrap, rework, and process variation. We will discuss how software-defined lighting, sample-efficient AI, 2.5D inspection, Generative AI and large field-of-view imaging, enable reliable defect detection on large, reflective parts both at final inspection and during production. Real manufacturing case examples in automotive, battery, electronics industries will show how end-of-line inspection data is used as a quality benchmark while inline inspection is introduced without disrupting cycle time. Attendees will gain practical guidance on when to apply in-process inspection, how to integrate it with existing end-of-line systems, and what operational benefits this phased approach delivers.