What is OEE?

A light in the dark for mining and manufacturing

· 3AG blog,analytics

OEE. It’s a term almost everyone in mining and manufacturing is familiar with, but one that very few would profess to truly understand. Its application seems almost too simple, yet its calculation can stump even the brightest leaders.

An OEE definition and some broad applications

OEE, or overall equipment effectiveness is like the headlamp on a miner’s helmet: It shines a bright light where you need to focus your work and highlights how best to do that work—so you can be as efficient (with your time and other resources) as possible.

OEE is frequently employed across mining and manufacturing. Part of its appeal is its obvious usefulness; it simply shows what percentage of your manufacturing time is productive. A score of 100% means you’re producing good products as quickly as possible.

To expand a little, OEE measures how many good products an organization creates in a given timeframe divided by how many it theoretically could have produced if all machines and processes ran perfectly. It can be calculated by looking at actual production for a time period (tons, units, etc.) or by measuring the “good” time that equipment is running. This flexibility in measurement is both a blessing and a curse, as any site superintendent can tell you.

Regardless of such minor variations, OEE relies on elementary mathematics; for example, if your production line is designed to create 1,200 units per shift but only 900 are completed, your OEE score is 75%. Or, say, your mill can crush 5,000 tons every shift but only 3,000 tons are produced, your score would be 60%.

Its broad applicability has made OEE a valuable standard for determining productivity in manufacturing. OEE is usually broken down into three ratios, regardless of industry:

Availability compares equipment run-time against shift length. This may be affected by scheduled maintenance, unexpected breakdowns, staffing changes or disruptions, running out of supplies or supply chain interruption.

Performance looks at what is produced versus what could have been produced or how much time was spent producing units vs. total run time. This is usually affected by the relative health of the machine being measured.

Quality is the ratio of much good, sellable product you produce vs. total production (including defects, rework, etc.).

Each of these three ratios can be further categorized based on the associated loss.

  • Equipment Failure includes broken or damaged tools or machines, unexpected repairs, missing materials, or absent equipment operators—anywhere along the product line. This issue affects Availability.
  • Setup and Adjustments refer to machine set-up or start-up, staff changes, significant equipment or tool reconfigurations, or scheduled cleaning, maintenance, and quality inspections. This also affects Availability.
  • Idling and Minor Stops in production may result from improper machine settings, faulty sensors, sub-optimal equipment design, or on-the-fly maintenance. This issue affects Performance.
  • Reduced Speed can occur when machines require cleaning, repair, or replacement; when they’re operating in poor environmental conditions or operators make mistakes; during warm-up and shutdown. This also affects Performance.
  • Process Defects can result from any of the above, and primarily affects Quality.
  • Reduced Yield can result from inefficient staff changeovers, incorrect settings being applied when new machine parts are used for the first time, long equipment warmup periods; using machines designed without lean manufacturing in mind can also compromise output. This also affects Quality.

It’s worth noting, OEE should not be treated as an absolute measure of company-wide productivity. Rather, it’s best used to discover where processes and machines can be made more effective, which should in turn show how to accomplish these improvements.

What about TEEP?

Total effective equipment performance (TEEP) shares similarities with OEE but uses a broader time period for its calculations. With TEEP we expand total run time to include every minute of the day; in other words, a TEEP score of 100% would indicate that the machine was running perfectly all the time, with no stops.

 

Since we are concerned with changes in metrics as opposed to the number itself, it makes more sense to focus on OEE. OEE is a simple concept with a straightforward approach to calculation, in part because it’s best performed on one process or machine at a time. Here’s how to go about it:

How to calculate OEE

The OEE formula is relatively simple:

OEE = time spent producing good product ÷ shift length

OR

OEE = good product made ÷ the amount of product that could have been made

OR

OEE = Availability × Performance × Quality

Which of the above approaches you use will depend on what you produce:

  • For continuous manufacturing—which produces bulk dry or fluid materials like concentrates, flour, or crude oil—companies typically apply the first formula based on time period measurements.
  • For discrete manufacturing—which produces distinct, final products, such as toys or tools or car parts—organizations generally apply the second formula based on number of units produced.

However, by applying the third formula, we get a better understanding of where losses and waste occur. For example, the diagram below shows that our biggest issues arise from availability, which could indicate that equipment is breaking down more frequently than expected.

Expressing OEE as its component losses

How NOT to use OEE