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This chapter introduces definitions of OEE categories, a sample production report, summary results with OEE calculations, and a reconciliation of the various OEE results and losses. The categories that follow are suggested as a basic set for nearly every key manufacturing area. The purpose of the categories is to provide enough detail to focus priorities and reveal areas of major opportunity. All events must be categorized without using categories such as “miscellaneous” or “other.” At the same time, the categories should not be so detailed that they are overwhelmed by too much incremental information. Larger processes should accumulate information for each key step.

The categories should allow the company to identify its opportunities in a reasonable time frame. They should also form the baseline for detailed analysis. Using common categories enables a company to benchmark similar areas both internally and externally. To be successful at benchmarking, all events must be categorized; total reconciliation is then supported and credibility is maintained. More discussion on benchmarking can be found in section 8.10.

A sample product report of the important categories follows in section 2.3. This report, which covers a production period of 40 hours, looks at a full range of problems and includes a log sheet that categorizes the various events. A suggested report is attached along with the TPM (Nakajima) OEE formulas¹ and three methods of computing OEE. Regardless of the approach used, the OEE and various Loss percentages should total 100 percent.

Key Definitions:

Asset Utilization. The percent of Total (calendar) Time that the equipment runs.

Downtime (DT). All Unplanned Machine downtime events should be categorized into the following categories:

DT Technical. Downtime due to any equipment failures affecting the machine or process, including periphery equipment, (utilities, sprinklers, doors, humidifiers etc.), equipment failure due to maintenance errors, and equipment-caused dirt or scratches.

DT Operational. Downtime caused by not following procedures, operating outside of specifications, operator error, etc.

DT Quality. Downtime caused by nonconforming supplies and raw materials, process control problems, unplanned testing, non-manufacturable product, and dirt from the product or process.

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 cycle counters, run hour clocks and other measuring devices. Simple chart recorders can be extremely valuable because the frequencies and duration of events can be easily captured and analyzed.

Figure 2-1 provides a form that lists the minimum information that should be gathered.

This information collected for each product run can quickly form the database to begin examining OEE and to start driving productivity improvements. For example, comparing start/stop time vs. run time measures efficiency, start/stop cycle time vs. run time measures speed information, and units vs. transferred output measures quality. Comparing input materials vs. units produced captures waste and inventory information. Comments from the crew leader help cross-functional teams work on root cause elimination of limiting problems. One goal is to understand the actual functions that have failed, as well as the actual equipment and technical problems. Another goal is to reconcile the actual output with the computed OEE, confirming that true OEE is being captured.

Figure 2-1 Example Run Order Report Form

A decision must be made about how to handle re-work. In many processes, manufactured items cannot be transferred or shipped with out being re-worked first. (In such cases, the first effort of bottleneck has failed. OEE for that manufacturing time is zero.) Re-work efforts can fall into the following three categories.

1.The re-work can be completed off-line using non-critical equipment. It may even simply involve re-packaging and can be completed manually. In either case, the rework does not impact the bottleneck system. It becomes a manufacturing cost decision. OEE of the bottleneck does not change. However, the measure for factory units produced should note how much re-work was finally transferred so that reconciliation between OEE and first pass yield can be determined.

2.The re-work can be completed online at a time when the equipment was not originally scheduled for production, perhaps on weekends or overtime. As with the first category, this work essentially is completed with off-line equipment and, again, it becomes a manufacturing cost decision. As before, the first pass yield number needs to be identified. This type of action should be identified when examining the TEEP metric; it involves activity on a key asset that would have conflicted with regular production had it been scheduled.

3.The re-work must be completed online, competing with regular production time. In this case, the re-work material should be looked at as new input material. The time, speed, and quality factors should compute into the current OEE. A note needs to be made so that the incoming inventory is adjusted appropriately now that waste has been turned into good units.

Consider the following example:

Assume that 100 percent OEE (running at ideal speed with no downtime and no quality losses) for a production area is 100 units per hour. Normal production has been running at 75 percent OEE (75 units per hour).

During week 1, the work area ran production for 168 hrs and produced at a normal rate for 160 of those hours. However, during 8 of those hours, the product was placed in the wrong colored boxes, creating 800 units of re-work. In sum, for 8 hrs, OEE is zero and for the remaining 160 hrs OEE is 75 percent. The week’s report would indicated an OEE for the area of 71.4 percent, calculated as follows:

During Week 2, a holiday week, the area worked 144 hours including the re-work. The equipment ran normally. However, the 800 rework units had to be manually fed into the system. The time for this rework took 12 hrs, resulting in only 780 good units. Because 780 units in 12 hours averages 65 units per hour, the equivalent OEE is 65 percent for those 12 hours. The rest of the production for the remaining 132 hrs was at a normal OEE rate of 75 percent. The week’s report would indicate 132 hrs at 75 percent and 12 hrs at 65 percent, yielding an OEE of 74.2 percent.

The overall OEE for the two week period is 160 +132, or 294 hrs, at 0.75 percent, 8 hrs at 0 percent and 12 hrs at 65 percent. This yields a combined OEE of 72.7 percent.

In general, good data collection is a key requirement for successful OEE strategy. The success of any factory is greatly affected by how effectively accurate information is collected and analyzed.

2.3 Practice Production Report

The spreadsheet in figure 2-2 follows and provides a sample 40-hour production report. It includes many different types of interruptions that illustrate the different OEE categories. Assume this area has a normal waste rate of 3.5 percent and that it produces finished units at the rate of 4 per minute (ideal or theoretical rate). Each column of the spreadsheet represents 10 minutes of calendar time.

Each event is identified with a letter and a brief description. The height of each shaded area represents the rate at which units are being produced, with each row representing 2 units per minute. Thus, an area 2 rows high has an expected rate of 4 units per minute. By summing the shaded areas of production, the number of units produced can be determined (see section 2.5). The units produced for the experiment represented by the block following letter W are excluded from this number.

The analysis that follows computes OEE and TEEP for the specific 40-hour time period in the spreadsheet. Do not confuse the production report for a weekly report. (If the 40 hours did represent the planned production schedule for a week, OEE would remain the same, but TEEP would be computed on the basis of 168 hours.)

2.4 Summarizing the Production Report

Figure 2-3 provides a table that can be used to summarize the basic information from the production report in section 2.3. You may use this table to practice classifying the events with the definition categories from section 2.1. (I recommend that you complete the practice summary before continuing through this chapter.) This exercise is typical of the information gathering and analysis that should be part of your daily routine.

A completed summary of the basic information is also provided in figure 2-4 so that you can compare your selections with mine. Your summary sheet may be laid out differently and may contain different abbreviations for the descriptions and categories, but the basic information should be similar. Note not only the duration of events but also the frequency. The frequencies will help provide reliability analysis; they will help you identify and eliminate problems.

The summary sheet does not list the actual chronology of events, only a generic sequence. The actual chronology would be useful and should be considered for capture as well. I have been in problem solving sessions where we needed to know not only the sequence of products/processes, but also the length of each run and the specific raw material lots associated with each order. At times it can be advantageous to coordinate the crew leaders’ notes and remarks into the summary sheet so that their unique observations are directly visible with the corresponding order. However, for our immediate purpose – understanding how OEE can be derived and computed – the basic sheet is sufficient.

When you summarize date data, you should also consider boundary parameters. Setting boundaries at finished orders usually helps keep production events intact. Sometimes the summary will be by shift or by daily shift break (e.g., start of A shift) to keep crew information intact. Sometimes monthly or quarterly financial breaks may be mandated, even though they may fall awkwardly in the schedule. I recommend using completed orders or process changes. These will provide the data that is easiest to use for driving OEE improvement.

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 on no more than three key projects at a time and complete them as quickly as possible. Do not let your resources be diffused on a multitude of jobs. Good progress will occur if you select and eliminate the right limiters.

In general, the loss analysis step is a point where synergy between OEE and other key parameters occurs. During this step, the detailed equipment performance records will help identify significant root cause limiters. Cross-functional teams properly trained in objective problem solving and focused on the areas of large losses often make breakthrough gains in OEE improvement. Detailed observations that are provided by an effective equipment performance system database will be of assistance. Once the key root cause limiters are identified and eliminated, significant improvement in performance will occur.

Section 2.1 identified several types of loss that together equal total loss. These are waste loss, speed loss, ST (stop time) operational loss, ST induced loss, and DT (downtime) loss. Examine the example that has been used throughout this section. Note that 4680 units were produced and 4362 units were good units. The difference in these numbers (318 units) is the quality loss and the theoretical factory time to produce these units is the lost time due to quality. Also, 340 minutes were used in operating at 1/2 rate (2 units/min) which results in 1/2 of this time (170 minutes) as 100 percent speed loss. Therefore the losses are as follows:

Total Loss = (4.3 + 9.3 + 9.3 + 3.3 + 14.2) = 40.4 percent

Recall from the previous section that OEE = 59.6 percent.

Therefore,

Total Loss + OEE = 40.4 percent + 59.6 percent = 100 percent

The reconciliation is complete.

This reconciliation step should be completed on a routine basis. If the OEE values do not correlate with factory output, then the lowest value should be assumed until the discrepancy is resolved. It takes discipline to correctly collect data and to confirm that the database is correct. But this discipline is necessary to be sure everyone is working with good information.

A sample report follows (see figure 2-5). The values are filled in for the results of the practice example. This type of form is useful when you are looking at similar process systems and developing areas for best practices. It is also useful for demonstrating improvement over time for the same equipment system.

The report displays various losses and OEE, showing that they can be reconciled to 100 percent. Also, the input for simple computation of OEE is available and can be used to confirm that true OEE is provided. If this format is used for monthly reports, the various OEE values can then be properly weighted relative to Scheduled Time to determine OEE for the quarter or year. You may also want to incorporate the number of frequencies of each category into the report. This information is necessary and valuable in computing reliability parameters.

With the Loss categories in mind, figure 2-6 Visualizing OEE Formulas, page 46 will help to understand OEE and TEEP relative to theoretical factory or process time.

Reference:

1. Nakajima, Seiichi. Introduction to TPM: Total Productive Maintenance. Cambridge, Massachusetts: Productivity Press, 1988.

Figure 2-5 Sample Report Form

Figure 2-6 Visualizing OEE Formulas

This visual graph of the OEE and TEEP formulas can be laid out over any timeframe that you want to investigate. The overall length A becomes the calendar time of the time period you are looking at.

B is the amount of production schedule time within A.

C is the amount of actual equipment uptime or runtime.

D is the amount of good production time. This should reconcile to your computed Theoretical factory time from the amount of good product transferred.

If you only look at a planned production time then TEEP = OEE.

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