2022 State of the Industry CNC Machining

Between supply chain constraints, labor shortages, and increasing market competition, manufacturing leaders have had their fair share of challenges to contend with.

How has the industry reacted to these challenges over the past year?

Since 2017, MachineMetrics has collected data directly from the controls and sensors of thousands of machine tools. These machines span hundreds of companies in the United States, representing all kinds of machine tools in all types of industries.

Read on to see how you match up against others in the industry. Or watch our State of the Industry Report.

Data in the manufacturing industry continues to be siloed by individual companies, with each manufacturer keeping their data for themselves. This is understandable, as without a neutral third-party, sharing data can feel risky and unwarranted.

This isn’t to say that third-parties haven’t attempted to collect industry data. Industry associations have conducted national surveys for decades through traditional means. These surveys are all voluntary surveys that require data from the contributor in return for survey results. Companies send their data up to the Association and receive overall industry trends in exchange for their data. While this may seem like the most straightforward way of getting insights into the industry, the approach actually has an array of drawbacks.

Economic downturns or slowdowns in business often cause non-reporting, as more imperative business matters trump using resources to report to a survey. This, unfortunately, is when your business needs industry information the most -- in a month where there’s a blip in sales, knowing where you stand and what segments to focus marketing efforts on can be of paramount importance to recovery.

With the State of Discrete Manufacturing report, manufacturers don’t need to worry about reporting or not reporting. The insights will be there regardless, as the data is autonomously collected and anonymized.

Utilization Data

Pulled directly from machines

Though MachineMetrics can capture a large variety of data points, for the purposes of this report, we are using one primary data point to represent the productivity of equipment. Utilization is the percentage of time a machine is reporting an active state. An active state is sent by the control of the machine based on certain heuristics defined based on the domain of the machine.

For example, on some machines, if a G-Code program is running, the machine is considered active. So, if a machine has 33% utilization in a day, it means that 8 out of 24 hours the machine was actively running a program. It does not mean that the spindle was active that whole time, but rather that it was reading and executing a series of commands from a G-Code program, which may include built-in pauses, setup time, etc. If a G-Code program is interrupted or there is no program running at the time, the machine goes into an inactive state.

Another type of machine may have its active state determined by a current transducer, which is attached to the spindle power source for the machine. When the power draw exceeds a certain limit, we mark the machine as active. Pairing it with a lag factor to also include quick pauses (ex. 10 seconds), we can very closely approximate true usage of a machine based on this set of heuristics.

Density Plot

We can compute utilization for each of the companies that we work with by averaging over all of the machines in their individual shops. What happens when we look at the distribution of these company-level utilizations among our customers? Unsurprisingly, the curve is quite similar to the density plots over machines. Though average utilization stands at about 26%, most companies appear to perform around 17-20% utilization, with a fat tail of high-performers stretching into the 60’s. A manager can get an immediate sense of how competitive they are by just learning where they live on this plot.
Utilization by hour

When we look at average utilization over the course of a day, certain “key hours” are revealed. Factories seem to have “high utilization” hours from 8 am to 3 pm, with a slow and steady ramp-down period from there until the following day. If we look at the line plot to the right we can see that 4 AM is the slowest period, with 10 AM being the time at which most machine shops are firing on all cylinders.
Utilization by day of week

Aggregating utilization on day of week, we confirm some biases that may have been common sense to factory owners, but putting numbers behind it has been hard until now. It’s known that weekends tend to have lower utilization, but an interesting find is that Mondays and Fridays are also significantly lower than middle of the week utilization.

DAY OF WEEK UTILIZATION OVER TIME

When we break down our aggregated trend over the past calendar year by day of week, we can of course immediately infer that weekdays are more productive than weekends. But we also see that utilization becomes less stable as we move away from mid-week. There also exists some correlation between weekend and weekday utilization.
Correlation to economic indicators

We’ve been tracking our utilization data to several economic indicators, and have found it to be highly correlated to several key economic series including: Industrial Production for Miscellaneous Metal Goods (the Fed’s proxy for Medical Device Manufacturing) and Value of Manufacturers’ Shipments for Motor Vehicle Components. This makes sense to us, as automotive and medical are two of the biggest industries discrete manufacturers serve. When MachineMetrics’ customers manufacture more of the component parts of cars and medical devices, their utilization goes up. The output of machined goods serves as a very tight correlate to the production of the products they ultimately go into: motor vehicles, trucks, metal implants, etc.

“The data will always be honest”

BENCHMARKING IN ACTION

Using this data, customers have the ability to make decisions on if they need new equipment, or if existing capacity already exists. One customer mentioned to us that if they had these reports, they would go straight to the bank for funding for new machines, citing third-party evidence that they were best-of-class and already above the industry norm in terms of utilization. He would also bring it to customers and potential customers to demonstrate that his shop is one of the top shops, and that they had data to prove it.

We release a MachineMetrics index of manufacturing, which is calculated by indexing the utilization of January 2018 to 100. Through this index, we can get a good idea of how manufacturing is progressing over time.

MachineMetrics customers can benchmark themselves against these reports to understand where they stand in relation to the industry.

Want to see how we capture this data from machines and enable manufacturers to make data-driven decisions?

Watch a video demo of MachineMetrics. Or set up some time with our team.

Density Plot

Utilization by hour

Utilization by day of week

DAY OF WEEK UTILIZATION OVER TIME

Correlation to economic indicators