Overall equipment effectiveness

Overall equipment effectiveness (OEE) is a hierarchy of metrics which evaluates and indicates how effectively a manufacturing operation is utilized. The results are stated in a generic form which allows comparison between manufacturing units in differing industries. It is not however an absolute measure and is best used to identify scope for process performance improvement, and how to get the improvement. If for example the cycle time is reduced, the OEE can also reduce, even though more product is produced for less resource. Another example is if one enterprise serves a high volume, low variety market, and another enterprise serves a low volume, high variety market. More changeovers (set-ups) will lower the OEE in comparison, but if the product is sold at a premium, there could be more margin with a lower OEE.

OEE measurement is also commonly used as a key performance indicator (KPI) in conjunction with lean manufacturing efforts to provide an indicator of success.

OEE can be best illustrated by a brief discussion of the six metrics that comprise the system. The hierarchy consists of two top-level measures and four underlying measures.

The two top-level metrics

Overall equipment effectiveness (OEE) and total effective equipment performance (TEEP) are two closely related measurements that report the overall utilization of facilities, time and material for manufacturing operations. These top view metrics directly indicate the gap between actual and ideal performance.

• Overall equipment effectiveness quantifies how well a manufacturing unit performs relative to its designed capacity, during the periods when it is scheduled to run.
• Total effective equipment performance (TEEP) measures OEE against calendar hours, i.e.: 24 hours per day, 365 days per year.

The four underlying metrics

In addition to the above measures, there are four underlying metrics that provide understanding as to why and where the OEE and TEEP gaps exist.

The measurements are described below:

• Loading: The portion of the TEEP Metric that represents the percentage of total calendar time that is actually scheduled for operation.
• Availability: The portion of the OEE Metric represents the percentage of scheduled time that the operation is available to operate. Often referred to as Uptime.
• Performance: The portion of the OEE Metric represents the speed at which the Work Center runs as a percentage of its designed speed.
• Quality: The portion of the OEE Metric represents the Good Units produced as a percentage of the Total Units Started. Commonly referred to as First Pass Yield FPY.

Calculations for OEE and TEEP

What follows is a detailed presentation of each of the six OEE / TEEP Metrics and examples of how to perform calculations. The calculations are not particularly complicated, but care must be taken as to standards that are used as the basis. Additionally, these calculations are valid at the work center or part number level but become more complicated if rolling up to aggregate levels.

Overall equipment effectiveness

OEE breaks the performance of a manufacturing unit into three separate but measurable components: Availability, Performance, and Quality. Each component points to an aspect of the process that can be targeted for improvement. OEE may be applied to any individual Work Center, or rolled up to Department or Plant levels. This tool also allows for drilling down for very specific analysis, such as a particular Part Number, Shift, or any of several other parameters. It is unlikely that any manufacturing process can run at 100% OEE. Many manufacturers benchmark their industry to set a challenging target; 85% is not uncommon.

Calculation: OEE = Availability x Performance x Quality

Example:

A given Work Center experiences...

Availability of 86.7%

The Work Center Performance is 93.0%.

Work Center Quality is 95.0%.

OEE = 86.7% Availability x 93.0% Performance x 95.0% Quality = 76.6%

Total effective equipment performance

Where OEE measures effectiveness based on scheduled hours, TEEP measures effectiveness against calendar hours, i.e.: 24 hours per day, 365 days per year.

TEEP, therefore, reports the 'bottom line' utilization of assets.

Calculation: TEEP = Loading x OEE

Example:

A given Work Center experiences...

OEE of 34.0%

Work Center Loading is 71.4%

TEEP = 71.4% Loading x 34.0% OEE = 24.3%

Stated another way, TEEP adds a fourth metric 'Loading', Therefore TEEP = Loading x Availability x Performance x Quality

Loading

The Loading portion of the TEEP Metric represents the percentage of time that an operation is scheduled to operate compared to the total Calendar Time that is available. The Loading Metric is a pure measurement of Schedule Effectiveness and is designed to exclude the effects how well that operation may perform.

Calculation: Loading = Scheduled Time / Calendar Time

Example:

A given Work Center is scheduled to run 5 Days per Week, 24 Hours per Day.

For a given week, the Total Calendar Time is 7 Days at 24 Hours.

Loading = (5 days x 24 hours) / (7 days x 24 hours) = 71.4%

Availability

The Availability portion of the OEE Metric represents the percentage of scheduled time that the operation is available to operate. The Availability Metric is a pure measurement of Uptime that is designed to exclude the effects of Quality, Performance, and Scheduled Downtime Events.

Calculation: Availability = Available Time / Scheduled Time

Example:

A given Work Center is scheduled to run for an 8 hour (480 minute) shift.

The normal shift includes a scheduled 30 minute break when the Work Center is expected to be down.

The Work Center experiences 60 minutes of unscheduled downtime.

Scheduled Time = 480 min – 30 min break = 450 Min

Available Time = 450 min Scheduled – 60 min Unscheduled Downtime = 390 Min

Availability = 390 Avail Min / 450 Scheduled Min = 87%

Performance

The Performance portion of the OEE Metric represents the speed at which the Work Center runs as a percentage of its designed speed. The Performance Metric is a pure measurement of speed that is designed to exclude the effects of Quality and Availability.

Calculation: Performance = (Parts Produced * Ideal Cycle Time) / Available Time

Example:

A given Work Center is scheduled to run for an 8 hour (480 minute) shift with a 30 minute scheduled break.

Available Time = 450 Min Sched – 60 Min Unsched Downtime = 390 Minutes

The Standard Rate for the part being produced is 40 Units/Hour or 1.5 Minutes/Unit

The Work Center produces 242 Total Units during the shift. Note: The basis is Total Units, not Good Units. The Performance metric does not penalize for Quality.

Time to Produce Parts = 242 Units * 1.5 Minutes/Unit = 363 Minutes

Performance = 363 Minutes / 390 Minutes = 93.0%

Quality

The Quality portion of the OEE Metric represents the Good Units produced as a percentage of the Total Units Started. The Quality Metric is a pure measurement of Process Yield that is designed to exclude the effects of Availability and Performance.

Calculation: Quality = Good Units / Units Started

Example:

A given Work Center produces 230 Good Units during a shift.

242 Units were started in order to produce the 230 Good Units.

Quality = 230 Good Units / 242 Units Started = 95.0%

Automated OEE Systems

Although OEE can be manually calculated based on collected production data, the advent of plant floor networks and OPC technology have opened the gateway to a plethora of automated OEE systems. OEE systems range from simple single sensor systems all the way up to high level systems integrated into MES, ERP or CMMS software. Innovators in the field of automated OEE include Ampla by Schneider Electric, Ampla Performance,^[1] Inductive Automation, Inductive Automation,^[2] FactoryMetrics,^[3] ActivPlant (acquired by CDC software), Capstone Metrics,^[4] Plantnode by Shoplogix,^[5] Informance (acquired by Solarsoft), Parsec Automation,^[6] Zarpac Performance Index,^[7] RS-Production (developed by Good Solution AB),^[8] Memex Automation Inc.,^[9] Provideam,^[10] PerformOEE^[11] from OEEsystems and EIT™ from Sidel Engineering EIT™ efficiency improvement tool™,^[12] Manifact Cause Findr Manifact CauseFindr,^[13] Vorne Industries XL Appliances,^[14] Idhammar OEE Systems^[15] from Idhammar Systems Ltd, ProduMax from Live Monitoring.^[16]

Further reading

• Koch, Arno (2007), "OEE for the Production Team", FullFact, ISBN 978-90-78210-08-5 (Dutch: 978-90-78210-07-8, German: 9-783940-775-04-7)
• Productivity Press Development Team (1999), "OEE for Operators: Overall Equipment Effectiveness", Productivity Press, ISBN 978-1-56327-221-9
• Hansen, Robert C (2005), Overall Equipment Effectiveness (OEE), Industrial Press, ISBN (978-0-8311-)3237-8
• Dwyer, John (2008), OEE – The Great Energy Saving", The Manufacturer, February 2008 pp. 52 – 55
• France, Alan (2010), "Delivering on the Promise of OEE; Best Practice Implementation", Idhammar Systems

OEE as a heuristic

OEE is useful as a heuristic, but can break down in several circumstances. For example, it may be far more costly to run a facility at certain times. Performance and quality may not be independent of each other or of availability and loading. Experience may develop over time.

OEE has properties of a geometric mean. As such it punishes variability among its subcomponents. For example 20% * 80% = 16%, whereas 50% * 50% = 25%. When there are asymmetric costs associated with one or more of the components, then the model may become less appropriate.

Consider a system where the cost of error is exceptionally high. In such a condition, higher quality may be far more important in a proper evaluation of effectiveness than performance or availability. OEE also to some extent assumes a closed system and a potentially static one. If one can bring in additional resources (or lease out unused resources to other projects or business units) then it may be more appropriate for example to use an expected net present value analysis.

Variability in flow also can introduce important costs and risks that may merit further modeling. Sensitivity analysis and measures of change may be helpful.

See also

• Total productive maintenance

References

1. ^ Automation and Control. Schneider Electric. Retrieved on 19 October 2011.
2. ^ MES Software – OEE Downtime Module – Overview. Inductive Automation. Retrieved on 19 October 2011.
3. ^ Qualisys Software and Technologies – Factory Metrics. Qualisyss.com. Retrieved on 19 October 2011.
4. ^ OEE Calculation Software by Capstone Metrics. Capstonemetrics.com. Retrieved on 19 October 2011.
5. ^ Manufacturing Software For Manufacturing Profitability. Shoplogix. Retrieved on 19 October 2011.
6. ^ Real-Time Manufacturing Operations and Performance Management Software by Parsec TrakSYS. Parsec-corp.com. Retrieved on 19 October 2011.
7. ^ Zarpac Performance Index – Downtime OEE system fueling Continuous Improvment and Six Sigma Goals in manufacturing and processing facilities. Zarpacpi.com (24 November 2010). Retrieved on 19 October 2011.
8. ^ GOOD SOLUTIONS AB – Lönsamhet genom uppföljning av TAK, OEE och produktionseffektivitet. Goodsolutions.se. Retrieved on 19 October 2011.
9. ^ Memex Automation. Memex.ca. Retrieved on 19 October 2011.
10. ^ OEE software for extra productivity in manufacturing UK, Ireland and worldwide. Provideam. Retrieved on 19 October 2011.
11. ^ PerformOEE™ – OEE Software from the OEE experts. Oeesystems.com. Retrieved on 19 October 2011.
12. ^ Efficiency Improvement Tool (EIT™). Sidel-ec.com. Retrieved on 19 October 2011.
13. ^ Manifact AB – Improve faster. Manifact.com. Retrieved on 19 October 2011.
14. ^ XL Productivity Appliance™. Vorne.com. Retrieved on 19 October 2011.
15. ^ Discover your hidden factory with Idhammar OEE Software. Idhammarsystems.com. Retrieved on 19 October 2011.
16. ^ Products. Livemonitoring.co.za. Retrieved on 19 October 2011.