Jump to content

Overall equipment effectiveness

From Wikipedia, the free encyclopedia

This is an old revision of this page, as edited by 196.47.129.20 (talk) at 22:43, 11 June 2013 (→‎Quality). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Overall equipment effectiveness (OEE) is a hierarchy of metrics developed by Seiichi Nakajima[who?] in the 1960s to evaluate how effectively a manufacturing operation is utilized. It is based on the Harrington Emerson[who?] way of thinking regarding labor efficiency. 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 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 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 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 that 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 that represents the speed at which the Work Center runs as a percentage of its designed speed.
  • Quality: The portion of the OEE Metric that 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.

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.

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 = uptime/ available time

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.

MUMTAZ ALAM

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.

Automated OEE Systems

Although OEE can be manually calculated based on collected production data, the standardization of plant floor networks and OPC technology has led many industrial vendors to introduce automated OEE systems, ranging in complexity from a single sensor to complex integrated MES, ERP or CMMS systems. Industrial OEE vendors are shown in the following table:

Product Name Vendor
Productivity Improvement System TACTA Productivity Improvement[1]
ProduMax Live Monitoring[2]
Proficy Plant Applications GE Intelligent Platforms[3]
AxOEE Memex Automation[4]
Ampla Schneider Electric[5]
AssetManager InfoServe365
OEE Management Software Capstone Metrics[6]
Objective.MES De Clercq Solutions[7]
OFS Operations Feedback[8]
Zarpac Performance Index ZPI Inc.[9]
Ignition MES Module Inductive Automation[10]
PlantRun Tascomp Ltd[11]
RBC OEE RBC Automation Limited[12]
Idhammar OEE System Idhammar Systems Ltd[13]
FactoryTalk Metrics Rockwell Automation[14]
TrakSYS™ Parsec Automation Corporation[15]
OEE Cockpit Van Lente & De Vos[16]
Operator MES Operator Systems[17]
Wonderware MES Performance Invensys Wonderware[18]
ATS Intelligence ATS International B.V.
Equipment Performance Monitoring System Mexter Technology Bhd[19]
OEEsmart MDE OEEsmart[20]
ProductionACE Production Process[21]

Further reading

  • Dwyer, John (2008). "OEE – The Great Energy Saving" (PDF). The Manufacturer: 52–55. {{cite journal}}: Unknown parameter |month= ignored (help)
  • France, Alan (2010), IDHAMMAR WHITEPAPER – Implementing OEE Systems: Delivering on the Promise of OEE, Idhammar Systems Ltd
  • France, Alan (2010), IDHAMMAR WHITEPAPER – The Business Case for OEE Systems: The operational and financial return on investment, Idhammar Systems Ltd
  • Hansen, Robert C (2005). Overall Equipment Effectiveness (OEE). Industrial Press. ISBN (978-0-8311-)3237-8. {{cite book}}: Check |isbn= value: invalid character (help)
  • Koch, Arno (2007). OEE for the Production Team. Makigami. ISBN 978-90-78210-08-5 (English), 978-90-78210-07-8 (Dutch), 9-783940-775-04-7 (German). {{cite book}}: Check |isbn= value: invalid character (help)
  • Productivity Press Development Team (1999), OEE for Operators: Overall Equipment Effectiveness, Productivity Press, ISBN 978-1-56327-221-9

See also

References

  1. ^ "TACTA Productivity Improvement". TACTA. Retrieved 14 March 2013.
  2. ^ "Live Monitoring Solutions". Live Monitoring. Retrieved 14 April 2013.
  3. ^ "Manufacturing Software MES - Proficy". GE Intelligent Platforms. Retrieved 14 March 2013.
  4. ^ "AxOEE - Increase Productivity". Memex Automation Inc. Retrieved 19 April 2012.
  5. ^ "MES software solution - Ampla". Schneider Electric. Retrieved 19 October 2011.
  6. ^ "Welcome to Capstone Metrics, the Line of Sight to Manufacturing Excellence". Capstone Metrics LLC. Retrieved 17 July 2012.
  7. ^ "De Clercq Solutions for Operations Execution". De Clercq Solutions bvba. Retrieved 9 February 2012.
  8. ^ "Operations Feedback Systems". Operations Feedback Pty. Ltd. Retrieved 22 November 2012.
  9. ^ "Zarpac Performance Index – Downtime OEE system fueling Continuous Improvement and Six Sigma Goals in manufacturing and processing facilities". ZPI Inc. 24 November 2010. Retrieved 19 October 2011.
  10. ^ "Ignition OEE & Downtime Tracking". Inductive Automation. Retrieved 19 October 2011.
  11. ^ "OEE - Overall Equipment Effectiveness". Tascomp Ltd. 16 May 2012.
  12. ^ "RBCSoft - OEE智能优化仪自动统计分析OEE，使提高设备效率和生产效率不再困难". 版权所有 (Pou Software). 2009. Retrieved 8 June 2012. {{cite web}}: Unknown parameter |trans_title= ignored (|trans-title= suggested) (help)
  13. ^ "OEE Software – Idhammar". Idhammar Systems Ltd. 20 June 2012.
  14. ^ "Performance & Visibility: FactoryTalk Metrics". Rockwell Automation. Retrieved 1 August 2012.
  15. ^ "TrakSYS™: Manufacturing Operations and Performance Management Software". Parsec Automation Corporation. Retrieved 21 August 2012.
  16. ^ "Home". Van Lente en de Vos, Organisatie Optimalisering. Retrieved 7 September 2012.
  17. ^ "Operator MES". Operator Systems. Retrieved 3 January 2013.
  18. ^ "Wonderware". Invensys Operations Management. Retrieved 13 December 2012.
  19. ^ "MexEPMS". Mexter Technology Berhad. Retrieved 28 May 2013.
  20. ^ "OEEsmart". OEEsmart. Retrieved 9 May 2013.
  21. ^ "ProductionACE". Production Process. Retrieved 6 June 2013.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Overall_equipment_effectiveness&oldid=559460955"