A small Texas shop cut one titanium part from 32 minutes to 10 using machine data
Neo Industries, a small machine shop in Colleyville, Texas, used automatic production monitoring to see how much of each cycle every tool was responsible for, then optimized tool by tool.
Evidence: Vendor-published customer story with named shop owner. Source date: 2026-05-20 · Checked 2026-10-23 · Tech: CNC controller data, production monitoring software (Datanomix)
The problem
Neo runs titanium parts on 24-36 hour turnarounds. Without data, cycle-time improvement meant guessing which tool or path was the slow one.
What they did
They connected their machines to Datanomix, which records every cycle and tool change without operators typing anything in. The owner treats it as a journal: compare batch to batch, find the tool that owns the most cut time, try a better insert or feed, repeat.
Reported results
On one titanium part run on a Hyundai WIA lathe with a bar feeder, cycle time went from 32 minutes to 21, then to 10 after further tuning. Across the shop, the vendor reports 35% higher utilization, 19% less downtime and roughly 150 extra production hours per machine per year.
Our take
Note there's no fancy AI here. The win came from simply seeing tool-level data and acting on it consistently. The owner's logic is the useful bit: a $600 tool that saves three minutes a part pays for itself fast. Numbers are from a vendor-published story, so treat the ROI figure as a best case.
Try this on Monday: Even without software: time each tool on your highest-volume part with a stopwatch and list them by share of cycle. Start with the biggest one.
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