An automotive conveyor belt in the field was experiencing unusual wear that made typical wear evaluation techniques impossible. As such, manual measurement of the belt was required. I took this as an opportunity to generate Intralox's first belt-scale visualization of wear, which I successfully used to identify the root cause of the atypical wear.
The ~12 ft x 6 ft belt section was disassembled, and belt pitch measurements were taken at three points along the length of each module using calipers and calibrated steel rods. Pitch elongation is used commonly as a wear metric.
The pitch measurements were input into excel, with center measurements duplicated to accommodate the bricklay pattern that modular conveyors employ. A heatmap was then applied to the values.
The heatmap was resized and tiled to create a broader image of the belt, then vehicles were added in the positions they occupied in the plant.
High wear was occuring behind the contact points between the belt and the car, which contradicted general knowledge about belt load distribution.
While studying a new image from the field, I noticed a shape in the dirt on the belt surface that I had seen in my heatmap. To explore this further, I executed a perspective distort in photoshop to get a top-down view of the belt.
Overlaying the heatmap above the top-down view of the belt revealed a strong correlation between belt wear and embedded dirt and grime.