Companies are utilizing the multidimensional analysis capabilities of AI for combined analysis for quality and safety for the first time. Anil Uzengi of Stroma is working with automotive companies to deploy edge-based cameras and AI systems to perform visual inspections for both safety and quality. “In Japan, ergonomic analysis is really important because they have an aging workforce. They want AI to detect musculoskeletal risks before injuries occur. The system looks for high-risk postures, repetitive motion, unsafe lifting, and similar patterns, then alerts employees and supervisors early,” Uzengi said. “The same system also verifies correct actions and component usage. If an operator uses the wrong part in an assembly, it can lead to critical faults. That’s why manufacturers are combining ergonomic safety with visual quality compliance in a single system,” he added.
AI is uniquely suited for analyzing unstructured data about safety risks. At The Heico Companies, employees are encouraged to flag anything that seems like a hazard. The emphasis is on making it very easy for employees to put concerns into the system. As David Roberts, Vice President of EHS, explained, “We empower employees to give us feedback about safety in real time. All they need to do is scan a QR code and provide a description of what they saw. They can do this in any format and don’t need to log in, fill out a form, or use drop-down menus. Talk about raw data!” Input can even be anonymous if the employee prefers. The AI system is able to sort through the unstructured data, identify patterns, and recommend actions. For example, the system may indicate that mobile equipment represents an increased hazard in a certain part of the factory. “It gave us more meaningful data, and it has driven very valuable conversations. We saw the value in it right away, and if it prevented one significant injury, it paid for itself.”
The connection between safety and maintenance is also of interest at The Heico Companies. “Thinking beyond EHS, we are starting to look at how we can use AI to analyze both safety records and maintenance logs. We’re asking how equipment problems and maintenance issues can contribute to safety risk,” Roberts said. “AI is teaching us to think about things a little differently in terms of how we approach some of these problems. We can do a lot more with the data than ever before.”
From Forklifts to AMRs
Addressing the specific hazards of mobile equipment was a top priority for NSK. Kyle Stiens said that the company wanted to address the amount of traffic on the shop floor before it became a safety hazard. “We became uncomfortable with the interaction between pedestrians and forklifts, so we decided to separate those factors completely by eliminating forklifts in spaces where people are present.” In places requiring movement of materials across great distances, NSK deployed AMRs (autonomous mobile robots). “It wasn't as simple as going back and forth between point A and point B. We needed a couple hundred different points, and they needed to be variable, so we worked with a vendor to create a fully autonomous system for AMRs.”
The AMRs use LiDAR (Light Detection and Ranging) to ensure safe navigation. They can make their own decisions or be summoned. “The team member can say ‘Come get my finished product’ and the AMR will automatically bring an empty pallet to replace the one it is taking. Just two AMRs can serve approximately 100,000 square feet of our plant.” The benefits go beyond safety. “We have always had processes in place to ensure that our plants maintained a high level of cleanness and organization, but the AMRs have forced us to an even higher level of discipline and standardization. Now people are thinking even more about where they place, for example, a toolbox to avoid interrupting the AMR.” Overall the program has been successful and NSK is looking for expansion opportunities in other parts of its operations.
