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OEE:Where Quality Meets Asset Performance & Productive Operations

Overall Equipment Effectiveness (OEE) is a well-known, well documented performance metric and is today part of the Lean or Agile organisation’s ‘tools’ which impact both the Asset Performance Management (APM) and the Operations Management (OM) perspective. Less likely understood is OEE as a quality metric despite articles and surveys indicating that operations management and quality management personnel ranked it as a key metric (closely following behind customer complaints and on-time delivery).

In its most basic form, OEE provides a simple way to “keep score” of production performance. However, the true power of OEE as a dedicated application lies in the ability to use it as a change-enabler, or tool for continuous improvement and lean manufacturing initiatives.

OEE is not an onerous and heavy commitment; there are off-the-shelf software packages available, and very often, OEE is provided as a ‘plug and go’ feature in CMMS systems such as FRACTTAL, so there’s little excuse not to make use of it.

So the general view is that OEE as a very important metric and many manufacturing operations across a wide scope of processes use it to manage Quality and understand where to focus efforts in reducing waste and downtime.

The Quality Element in OEE

There are many different approaches to measuring manufacturing efficiency and generally most companies will have some measures already in place. Many now argue that none of these are as comprehensive or far reaching as the OEE score which should be considered as a fundamental KPI (key performance indicator).

Measuring performance against standard (or performance to standard), is a good way of bench-marking production levels against competitors or industry averages, as a measurement system it lacks ambition. If production teams are generally meeting their target performance rates, complacency may creep in and continuous improvement becomes lip-service only.

OEE provides a way to measure the effectiveness of manufacturing operations from a single piece of equipment to an entire manufacturing site or several manufacturing sites in a group. In doing so OEE provides a complete picture of where productive manufacturing time and money is being lost and uncovers the true, hidden capability of the factory. It becomes the key manufacturing decision support tool for continuous improvement programmes.

OEE measurement is made up of three underlying elements, each one expressed as a percentage and accounting for a different kind of waste in the manufacturing process:

  • Availability: a measure of the time the factory/production line was actually available for production compared to the manufacturing requirements. Any losses in this area would be due to major breakdowns or extended set up time.
  • Performance: the rate that actual units are produced compared to the designed output. Losses in this area would be due to slow speed running, minor stoppages or adjustments.
  • Quality: a measure of good quality, saleable product, minus any waste. Loses for this element would be damaged rejects or products needing re-work.

OEE = Availability x Performance x Quality

It’s normally viewed as a percentage, with above 75% being really world class. So if you have 90% availability, with 90% performance and 95% quality output, then there is 0.9 x 0.9 x 0.95 = 0.77 or 77% OEE.

Availability is traditionally thought of as an asset performance metric while Productivity is generally considered a key operation metric, Quality is obviously the quality metric. In OEE quality is defined as a percentage calculated by dividing the number (or quantity) of good units produced by the total number (or quantity) of product started in the production process.

Using OEE – an example

Imagine a factory where a particular production line experiences 2.5 hours down time during 10 hours of planned production time; this would give us an availability figure of 7.5/10 hours or 75%.

At the same time the line, capable of a cycle time of 1000 pieces an hour is only producing 700 pieces an hour; this gives us a performance rate of 70%. Supposing that 30 of those 700 pieces are faulty, the resulting quality element would give provide us with 96% good pieces.

Availability

7.5 out of 10 hours

75%

Performance

Slow running 700/1000 units per hour

70%

Quality

Is good, only 30 units faulty

96%

OEE

Availability X Performance X Quality

50%

Separately we may not regard each element as too significant, but taken together they result in an OEE of 50% or half of what should be expected and giving rise to 50% of potential improvements. Working further on this example we would then need to address the two weaker elements, firstly the major breakdowns which appear to result in low availability, and secondly the causes of the poor performance rate.

We must however take care not to reduce the good quality in our efforts to improve slow running. It will be useful to add at this point, that accurate performance measurement with OEE should also be used to uncover the issues behind each loss. Significant interruptions to production are just as likely to be the result of waiting for raw materials or changeovers as equipment breakdown. Frequently People or Process issues are quicker and cheaper to resolve than equipment re-designs.

The 1% Effect

Using the example above, let's make some assumptions to illustrate the savings which could be made with just a 1% improvement to the OEE score.

Planned production time is 10 hours
Planned output is 1000 units per hour

Production cost per unit is $5

 

NOW

1% IMPROVEMENT

DIFFERENCE PER HOUR

OEE

50%

to 51%

 

Actual units/hour

700

770

70

Revenue generated/hour

$3500

$3,850

$350

Lost opportunity cost in revenue/hour

$1500

$1150

$350

A 1% improvement has generated $350 per hour in additional revenue for the company, or looked at from a different perspective; it has reduced the loss due to waste by $350. That’s $3 500 for the entire 10 hour shift, and $17 500 over a five-shift period in a week. Now just imagine what the company would achieve with a 10% improvement, a realistic figure we could expect to see in the first 3 months of introducing an OEE system.

Factors Impacting Quality on the Shop Floor

There are a number of factors that influence quality on the shop floor. Some of them are related to the manufacturing environment and some are supply chain related. Clearly, if raw materials do not meet quality specifications producing quality finished goods becomes a far more difficult task, if not impossible. While ensuring the quality of the incoming raw materials is not a direct operational activity, verifying that only quality checked and conformant products are introduced into the manufacturing process certainly is. Ensuring other operationally related activities that directly impact quality include:

  • Proper work instructions are followed in the manufacturing process
  • Specified jigs, fixtures and tools are used during assembly or manufacturing
  • Correct specified measurements and checks are performed
  • All required production information, batch quantity, formulation, due date, serial number sequence, and traceability is collected.

Quality Is Dependent on Proper Asset Performance

Just as there are direct linkages between operational performance and quality, so too these also exist between asset performance and quality. Production assets that are operating outside their normal parameters due to malfunctions, misalignment, or outright failure cannot be expected to produce goods that meet quality specifications. A machine tool that has excessive play can’t possibly hold tolerances just as a chemical process reactor that cannot maintain proper temperatures or pressures cannot produce quality products. This is why asset performance is so closely linked to quality.

If an asset needs to be frequently shut down for repair or adjustment due to maintenance issues, there is likely a negative impact on quality as well. Quality production is more readily maintained during steady-state operation. Start-up or shutdown cycles produce greater product variability, further reducing quality. Likewise raw materials introduced into the manufacturing process that far exceed normal design parameters can cause equipment damage. Attempting to punch pieces from a 3 mm piece of sheet metal in a machine limited to a 2.5 mm capacity will likely lead to downtime, sooner if not later. Another example would be where operationally a machine is operated at pressures or temperatures that are too high due to poor operational work instructions. Maintaining process quality is important.

OEE is the product of three variables. All three are closely interrelated and, to some degree, dependent on each other. The failure of any one will cause a drastic effect on OEE. This is one of the reasons we explain to customers that Operational Excellence requires the balancing of quality, asset performance, operations and energy management and a functioning Safety, Health, Environment (SHE) system. A poorly performing asset will not only directly impact availability; it will also indirectly impact quality, productivity, energy loss, and may impact the environment. Since poor quality or operational issues can impact asset reliability this becomes a cascading problem that can quickly lead to deteriorating results.

OEE is indeed a key part of Quality Management.


FRACTTAL offers you the ideal tools to gain an in depth understanding of the operation and effectiveness of your maintenance management department. This knowledge will allow you to readjust your processes, to raise productivity levels and extend the useful life of your assets, minimize downtime and perform tasks, generating greater value to your organization.

If you are not yet a FRACTTAL user, we invite you to take up a FREE 2-user CMMS and see how we can help you better manage your operations.

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