Statistical Methods For Mineral Engineers -

Twelve percent. It felt like a lie.

Then she closed her laptop, patted Montgomery’s textbook, and smiled. Statistics didn't move rock. But they told you which lever to pull, and when to leave it alone. That was the real art of mineral engineering.

She drew a Shewhart control chart on a whiteboard in the control room. Upper control limit. Lower control limit. And in the center, the target P80 of 150 microns. Statistical Methods For Mineral Engineers

The daily average? It had dropped to 1,150 tonnes per hour. But the shift tonnage—the real money—was actually up 5% because the mill never stopped.

“For the last six hours,” she said, pointing to a string of seven points all below the centerline, “we have been running fine. But this run of seven points all below the mean? That’s a Nelson Rule violation. It’s not out of control statistically, but the probability of this happening by chance is less than 1%. It’s a trend. The mill is grinding finer because the new media supplier’s ball hardness is different. We need to back off the feed rate now—not in two hours.” Twelve percent

Elara calculated the correlation coefficient between feed rate and product fineness. It was -0.85. Strong, negative, and ignored.

Elara typed back: “Averages hide process stability. We stopped chasing ghosts.” Statistics didn't move rock

Gus blinked. “Speak English.”

“You’re chasing your tail,” she said. “The crusher power draw spikes, you back off. It drops, you tighten. But the lag in your feedback means you’re always reacting to what happened five minutes ago. By the time you fix it, the feed has already changed. You’re creating the instability you’re trying to solve.”