Published On: May 6th, 2022Categories: Machine Shop

There is a myriad of ways to be measuring manufacturing efficiency, ranging from simplified utilization percentage measurements to calculating production efficiency with complex OEE calculations involving numerous loss factors.  But what almost all existing methods of measuring efficiency miss, and what all machine shops suffer from to varying degrees, is the disconnect between spindle time and charged time, or the amount of time that an employee allocates to a job either through time cards or an ERP system.  Let’s start with some basics on efficiency measurement, before touching on how we can get the real picture of efficiency.

The basic efficiency approach: Utilization

The majority of machine shops think of efficiency in terms of utilization, which in its simplest form captures how much of available capacity (either people or machines) is being used.  Simply put, 100% efficiency would mean that a machinist working an 8-hour shift actually worked on one or more jobs for all of those 8 hours.  Or, for a machine that is scheduled to run for 8 hours actually ran for 8 hours.

The benefit of this approach is its simplicity; it’s easy to understand, easy to track and report, and easy to improve.  However, the main drawback of this approach is that it does not differentiate between “good” and “bad” activity.  For example, an operator can improve their efficiency metrics by simply slowing down a job that would otherwise have been finished and resulting in an idle time when complete.  Further, it does not account for scrap, rework, or other non-productive activities – and instead treats them as productive time.

The better efficiency approach: OEE

To address the above factors, manufacturing engineers came up with the concept of Overall Equipment Effectiveness (OEE), which is a standardized metric that is intended to identify the percentage of planned production time that is truly productive.  OEE was a major step forward over basic utilization, which incorporates utilization among other components of loss and addresses the shortcomings of the basic efficiency approach described above.  The loss components of OEE include:

Availability Loss: This is simply the utilization metric above – representing the amount of time that a machine sits idle when it is scheduled to be running.

Performance Loss: This factor captures how long it takes to run a job relative to the theoretical minimum / planned time (or the standard, for shops that use standard costing) to run a job.

Quality Loss:  This factor captures the time that the machine spent producing discrepant parts that do not meet quality standards.

Below is a graphical illustration of OEE which is calculated as the percentage of Fully Productive Time relative to Planned Productive Time.

Legacy OEE Summary for calculating production efficiency

The problem with OEE: Garbage in, Garbage out

We all know the phrase “garbage in, garbage out”.  In the case of OEE, there is a single metric that is most often misunderstood and misreported – run time.  And unfortunately, this also happens to be one of the most important components of OEE, because it drives the calculation of both availability loss and performance loss.  When you have a bad run time metric, OEE can leave you chasing efficiency ghosts.

The easiest and most common way to measure run time is to look at employee time cards and/or labor tickets in your ERP system, otherwise known as charged time.  And while this can be a proxy for run time, it is disconnected from the actual amount of time that a CNC machine’s spindle was running.  There are many factors that drive this disconnect, including:

  • “Normal” Interruptions: Employees often remain clocked into a job when taking short breaks; for example, it would not be reasonable or practical for an employee to clock out when taking a restroom break, but the machine may be waiting idly for the operator to return. While part of the normal course, this time adds up and is important to understand.
  • Bad Habits: Employees may clock on to one job for a period of time or even an entire shift when in reality they are not actually working on that job the whole time. This could just be for convenience or because they forgot to clock out.  Long stretches of clocked-in time with no actual machine utilization can significantly skew the stats.
  • Bad Actors: Some employees game the system by clocking in on jobs to appear utilized in the reports that rely on the data, but will then either not run machines or run machines intentionally slow to prolong work and minimize effort.

The second, better, and harder, way to measure run time is using spindle time, which requires a PLC to be integrated with each machine you want to monitor, or in the case of newer machines, MT Connect / OPC monitoring software.  While this is a step up from using charged time, the challenge with using spindle time is that for it to be useful, it needs to be married with production data.  So when the spindle runs for 5 minutes, the data needs to be matched up with charging data to determine what job was actually running during that 5-minute period, how many parts were produced, and how that compares to the expected production time.  This is easier said than done, but possible with sufficient investment in custom integration.

Assuming you have been able to get this far, you’re still not out of the woods on determining the root cause of your efficiency issues, because using spindle time as run time will show one big performance loss element, that includes both labor inefficiencies and machine inefficiencies – and with no way to segment between the two.

So the real question is – what run time are you using for your OEE calculation?  If you’re using charged time, you’ll be convincing yourself that your shop is a lot more efficient than it really is, because you won’t be able to see some of the most important drivers of inefficiencies which are masked by labor charging.  And if you’re using spindle time, you will have one big efficiency nut to crack, and you’ll be weaving through a lot of data to try to determine the root cause.  There must be an easier way, right?

The solution: Break it Up!

To REALLY measure and understand manufacturing efficiency you need to look at both spindle time and charged time.  The former is your machine performance benchmark, and the latter is your labor performance benchmark – and also what drives your financial statements if you are on a cost accounting system.  In an ideal world, these two should be equal, but they never are.

The chart below illustrates the efficiency loss associated with spindle time and charged time.

Improved OEE Summary for measuring manufacturing efficiency

Once you are measuring both spindle time and charged time, you can zero in on the root cause of your losses – and have an accurate picture of availability loss, operator loss, and machine loss.  No more guessing as to the root cause of the loss, no more bad information leading you on wild goose chases.

But wait – how do I actually do this?

That’s the easy part – just reach out to Harmoni, get yourself some terminals and plug them into your CNC machines.  Out of the box, with only a few basic configuration steps, Harmoni terminals integrate with your ERP system.  And if you don’t have an ERP system, Harmoni will serve as your ERP system – tracking and managing many of the same performance metrics.  Give us a call at 330-697-3883 or send us an email at and we would be happy to discuss how Harmoni can help you reach your efficiency goals.

About the Author: Adam Ellis