alt="image"/>
Figure 2-2 Sample Record of a 40 hr Production Run
2.5 OEE and TEEP Formulas and Results
This section begins by listing formulas that are important for computing OEE. The language originally used by Nakajimal appears in italic. All three methods used to compute OEE are derived from the Nakajima formulas. All three provide the same OEE values.
Even the simplest of the methods, the third one, gives a true measure of the hidden factory. The inputs for this simple method are scheduled time, quantity of good units, and ideal rate – easily reconciled with actual factory records that are usually available on a regular basis. Remember that the ideal rate for the plant bottleneck will be the highest accredited rate for the specific process being run. The ideal rate for non-bottleneck areas is discussed in the definition of ideal cycle time in section 2.1. In such cases, the speed factor should be limited to 1.0 (if rate is higher than ideal) with proper notification for inventory control.
The nomenclature in italics and basic formulas are stated in “Introduction to TPM” by S. Nakajima1.
Figure 2-3 Downtime Report Form for figure 2-2
Figure 2-4, the completed summary sheet from section 2.4, provides input values for the three methods used to compute the following OEE values. The basic information from the practice production report (section 2.3) is used each time.
Total Time = 240 blocks × 10 min/block = 2400 min
Ideal (Theoretical) Rate = 4 units/min (15 sec cycle time)
Assume a 3.5 percent waste or 96.5 percent yield for normal production activity.
Figure 2-4 Completed Downtime Report for figure 2-2
Then, Actual Units Produced =
Given that 160 units were contaminated and, therefore, designated as No Good (NG),
Number of Good Units Produced = (4680 − 160) × 0.965 = 4362 Good Units
Method 1: OEE Using Nakajima Formulas
Loading Time = Total Time − Excluded Time =2400 min − 570 min = 1830 min
From above, Total Units Produced = 4680
Performance Efficiency = 1 × Operating Speed Rate = 1 × 0.873 = 0.873
OEE = Availability × Performance Efficiency × Quality Rate
= 73.2 percent × 0.873 × 0.932 = 59.6 percent
Note: Nakajima doesn’t calculate TEEP
Method 2: OEE Using Event Time Records
Scheduled Time = Total Time − Excluded Time = 2400 − 570 = 1830 min
Runtime = 1000 + 340 = 1340 min
| OEE | = | Availability × Speed Rate × Quality Rate |
| = | 73.2 percent × 0.873 × 0.932 = 59.6 percent |
| TEEP | = | Asset Utilization × Speed Rate × Quality Rate |
| = | 55.8 percent × 0.873 × 0.932 = 45.4 percent |
Method 3: OEE Based On Good Units Transferred
Accurate OEE can be determined by multiplying Theoretical Cycle Time, Number of Good Units, and Schedule Time. An event time record is not required, except for detailing profitable OEE opportunities. Recall from above that 4362 Good Units were produced and should be equal to the amount of product transferred. If all product is transferred without reduction for off specification units in your area, then modify the transferred amount by historical quality levels. Theoretical Cycle Time is known to be 4 units/min, and Scheduled Time is 1830 min., a known production value.
This result is exactly the same as that reached by methods 1 and 2.
This section is key to understanding the factors used to compute OEE. It demonstrates that true OEE can be found by several approaches. Furthermore, it reconciles with plant output as seen in the next section.
2.6 Reconciliation and Loss Analysis
Once OEE is calculated, the various losses are computed from the summary sheet information. Analyzing these losses will help you identify areas that have major opportunity for improving OEE. Obviously, improvement in any area will help OEE. However, the greatest opportunities for OEE improvement are those areas with large losses.
OEE is not the only factor behind company productivity. Therefore, the different potential programs must be ranked for their overall benefit. For example, some industries may have specific quality or financial considerations that must be incorporated into their lists of priorities. All programs should not only be evaluated for their anticipated benefits, but also be congruent with the goals of the company. When completed, they should be measured for evidence of their success. Evaluating the trends of most key parameters will usually identify the impact of a program before and after its completion. Chapter 5 discusses a value fulcrum, a concept that can help rank nearly equal projects on a reactive to proactive scale.
When setting goals, you should link throughput improvement with desired progress of other parameters. Take this step when you initially assess the current baselines of all parameters. It often takes creativity to define the relationship between parameters. However, by clearly communicating the desired outcomes, the priorities are understood and supported by the entire community. I recommend that you focus