Methods For Mineral Engineers — Statistical

She left him with a process behavior chart and walked to the grinding mill.

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

The average was just a ghost. The plant was either choking or starving, never steady. Statistical Methods For Mineral Engineers

She pulled up the last 72 hours of data from the conveyor belt scale. The plant reported the daily average: 1,200 tonnes per hour. But when she plotted the individual one-minute readings, the story changed. The chart looked like a seismograph during an earthquake. Peaks at 1,600 tph, troughs at 800 tph.

Her first stop was the primary crusher. The operator, a veteran named Gus who chewed tobacco and hated change, saw her coming. She left him with a process behavior chart

Elara was the site’s mineral processing engineer, but her secret weapon wasn't a froth flotation cell or a high-pressure grinding roll. It was a battered copy of Montgomery’s Introduction to Statistical Quality Control and a stubborn refusal to trust averages.

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. Strong, negative, and ignored

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.”

“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.”