Inside one shop's tool-level approach to production data, with a 35% lift in utilization, a 19% drop in downtime, and a 5x ROI per machine.
From 32 Minutes to 10: How Neo Industries Turned Production Data Into Compounding Returns
From 32 Minutes to 10: How Neo Industries Turned Production Data Into Compounding Returns
Case Study from | Datanomix
When Every Spindle Hour Has to Earn Its Place
Margins are tighter. Skilled operators are harder to find. And every spindle hour either earns its keep or quietly costs money. Manufacturers of every size are looking for ways to do more with the equipment they already have, and the shops moving fastest are the ones running on real data instead of instinct.
For decades, machine monitoring was positioned as a tool for shops large enough to justify the software investment on volume alone. That framing is breaking down.
Production monitoring is now delivering measurable gains across all sizes of CNC operations, from small machine shops to multi-facility manufacturers, because the underlying problem is universal: you cannot optimize what you cannot see. And in a tight labor and demand environment, the cost of running on instinct only goes up.
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Tight Windows, Hard Materials, Aggressive Goals
Neo Industries is a small machine shop in Colleyville, Texas, just outside the Dallas-Fort Worth metroplex. President Bob McGregor built Neo to take on the kind of work that demands both precision and speed: titanium parts on aggressive turnaround windows, sometimes shipping within 24 to 36 hours, sometimes the same day they are quoted.
That kind of work has zero margin for guessing. Titanium is unforgiving. A wrong feed, a worn insert, or a tool path that nobody bothered to optimize can blow through cycle time and tool life in the same shift.
Neo's operating philosophy was clear from the start: Make every operator and every machine count, run reliable processes that require minimal supervision, and build a clear line of sight to greater automation. The question was how to get there with the team and budget they had.
Turning Tool Paths Into Decisions
Neo brought in Datanomix, which Bob utilizes as a journaling system. Every cycle, every tool change, and every variation between runs is captured automatically. The team analyzes runs batch-to-batch and identifies exactly where to invest and where the next round of optimization will pay off.
The shift was immediate. Instead of guessing whether a setup took 30 seconds or three minutes, Bob and his team could see exactly what each tool contributed to the total cycle. Datanomix shows what percentage of the cut each individual tool owns, which means tooling decisions stop being instinct calls and start being data-backed bets.
"If I have to buy a $600 tool but I'm gonna get three minutes a piece back, it pays off pretty quickly," Bob said.
From 32 Minutes, to 21, to 10
Take one titanium part, Neo runs through an Edge bar feeder on a Hyundai WIA turning center. The job uses six to eight tools, each contributing differently to the total cycle. Without tool-level data, optimization would have meant chasing the obvious culprits and hoping for the best.
With Datanomix, Neo could see exactly which toolpaths were consuming the most time and where a different insert or a tighter feed would pay off. Tool by tool, path by path, the team dialed the job in.
The original cycle time on that part was 32 minutes. After the first round of optimization, it ran in 21 minutes. Continued tuning, guided by the same data, has since brought it to 10 minutes.
That progression matters more than any single number. It is the difference between a one-time efficiency project and a compounding asset. Every run produces information. Every batch produces a chance to improve. And those gains stack up at every scale, from a small machine shop to a multi-facility manufacturer. Southern Machine Works, another Datanomix customer, used the same tool-level approach to unlock measurable capacity gains across a much larger operation.
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Beyond the Cycle Time
Beyond that one part, Datanomix is paying off across every machine. Neo increased utilization by 35% and cut downtime by 19%, reclaiming roughly 150 additional production hours per machine per year, worth about $12,020 in new productivity at a standard $80 shop rate. The result is a 5x return on the Datanomix investment, and for a shop running aggressive turnarounds on demanding materials, the difference between fitting in the next rush job and turning it down.
More importantly, Bob and his team now operate with the confidence that every tooling decision has data behind it, every process is observable, and every improvement is repeatable. That is the groundwork on which greater automation gets built.
"We always know what's going on with Datanomix," Bob said.
Watch the full video interview with Bob, including a walk-through of the shop and the systems behind these results.
Datanomix provides production monitoring software purpose-built for CNC manufacturers. By delivering real-time visibility into utilization, downtime, cycle times, and capacity, Datanomix helps manufacturers eliminate variability, improve operational consistency, and unlock hidden productivity within their existing equipment. Manufacturers use Datanomix to move from guesswork to data-backed decisions that improve performance and protect margins. Learn more at datanomix.io.
The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow
Datanomix
Datanomix empowers manufacturers of all sizes to increase productivity and profitability through its Data-Powered Production™ solutions. Its product portfolio includes Production Monitoring, G-Code Cloud™ + DNC, TMAC AI™, and ToolAnalytix™ - all designed to turn machine data into actionable insights with zero operator input. Headquartered in New Hampshire, Datanomix software analyzes real-time production signals to identify bottlenecks, improve quality, and provide prescriptive coaching to drive continuous improvement. For more information, visit www.datanomix.io.
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