target="_blank" rel="nofollow" href="#fb3_img_img_5127da67-fbf8-5a0b-918a-316d1ae686c3.jpg" alt="image"/>Excluded Time. This is (normally) planned time not scheduled for production. This would be scheduled maintenance downtimes (preventative maintenance and shutdowns planned at least a week in advance), scheduled meetings, experiment time (if the product is not going to be sold), planned training (if no product is made), Headroom time such as Holidays/Sundays/weekends, and “no product scheduled”. It should also include unplanned time when completing orders early due to good performance. Good performance should not be detrimental to OEE.
Ideal Cycle Time or Theoretical Rate. Also called Ideal Speed Rate. The best rate of speed or cycle time for key equipment or the flow line bottleneck, given a size and format of product. For example, key equipment or a flow line bottleneck is designed and accredited for 17 sec cycle time, or 3.53 units/min for a certain size. This rate should then be used for all products of that size and format. If a slower rate is used for difficult product within that family of products, then the reduction in OEE should be noted in the Comments column. In this way, any loss due to non-manufacturable product can be recognized and communicated. (This step is important for pricing products properly). If the equipment system is not the bottleneck of the product flow, then the ideal speed rate should be defined as the desired rate to feed the bottleneck. OEE is then measured against desired speed with the understanding that the maximum speed factor is 1.0. (Overspeed should be used only for scheduled make up situations, and noted in the remarks so that inventory balancing can be reconciled.)
Loading Time. Also called Scheduled Time or Planned Production Time. The time that normal operations intend to make production. It includes all events that are common to meeting delivery schedules, such as product changeovers or transitions, set ups, information downloads, all production run time, and unplanned stoppages for equipment, people, quality, and testing.
Overall Equipment Effectiveness (OEE). How effectively (makes good product at rated speed) the process runs when it is scheduled to run, see section 2.5 for the formula.
Operating Time. Also called Runtime or Uptime. The portion of loading time when the system is actually making product.
Quality Rate. The number of good units divided by the total units produced. The rate can be measured by items, square feet, cubic feet, gallons, barrels, etc.
Quantity of Good Product. Product that conforms to specifications. This count should not include volume that is on hold or may be condemned. Product that is transferred and later found to be No Good (NG) should be included under Waste (see below). However, if the loss is due to a specific root cause, then that loss should be noted in the comments under Waste. (See the example in the report, figure 2-5).
Speed Loss. The percent reduction of OEE due to running the equipment slower than Ideal Rate for the size and format or product family. It represents the difference between the theoretical time for the rate or cycle and the actual time used to make the product.
Stop Time (ST) can be Planned or Unplanned.
ST Operational. Planned stop time. It includes operational actions such as product changeovers and size changes, as well as standard testing, planned material loading, and required documentation.
ST Induced. Unplanned stop time when the line is down due to external (non-machine) reasons such as lack of materials and supplies, lack of people, lack of information, and unplanned meetings.
Theoretical Rate. See Ideal Cycle Time.
Theoretical Run Time. This is the minimum amount of time to produce the amount of good product. It is equal to the amount of good product divided by the ideal cycle time.
Total Effective Equipment Performance (TEEP). The percent of Total (calendar) Time the equipment runs at ideal speed making good product.
Total Time. Every minute of the clock. For a year, this measure is total calendar time (60 min × 24 hr × 365 days); sometimes called Calendar Time.
Waste. The total waste rate of the normal process. This should include structural waste, incident waste, testing waste, and recall waste. Unplanned waste that is generated while running the equipment should be captured here with a reference to the root cause of the incident. (Note: Companies often exclude structural waste to avoid visibly acknowledging its existence.)
2.2 Data Collection Review
Data collection and analysis for OEE is sometimes thought of as good in theory but not in practice. The arguments against it use excuses such as “We have too many different products” and “Our process is changed for different style outputs.” In these situations, the best approach is to step back and review the boundaries of the system. Start where materials are input into a systematic flow with an expected product or subassembly for the next factory step. This transformation step is often linked with others in a series of steps that have few if any fixed buffers. The process has an expected flow or cycle time.
OEE is appropriately applied to bottlenecks, critical process areas, and high expense areas. An appropriate test is to ask, “If the effectiveness of this transformation step is improved, will the bottom line be significantly impacted?’ If the answer is yes, then putting effort into generating true OEE and driving improvement is worthwhile.
As an example, I once observed a work center that successfully used OEE on the shop floor as follows. The company was highly automated; it used shop floor computers to gather much of its information. Its Equipment Performance System (EPS) collected not only the various downtime causes and frequencies, but also run time and speed monitoring. From this database, the company could easily compute OEE for each product.
Essentially, the company picked a standard process that represented its most common product. This product-process format was used as the benchmark for OEE. Because the format was used so routinely, significant production history was available. Furthermore, the product was manufactured on all of the work center’s different equipment flowlines. Next, the work center defined how other formats and sizes with the same product should compare with the benchmark process. This comparison generated an OEE coefficient. The comparison was repeated for different product families and formats as well as for different process setups. The information gathered was valuable when communicating with superintendents and plant managers about capability questions and the impacts of different product mixes. It also provided the yardstick for shop floor crews to use when examining their real time productivity on shifts.
This plant had the advantage of having automatic data monitoring and information feedback for nearly all the products it produced. However, at the very minimum, plants can simply gather the information for each product run, usually manually from
