OEE For Dedicated – Single Part – Processes
Definition:
Dedicated – Single Part – Process: A process that produces a single product or slight variations on a theme and does not require significant tooling or equipment changeover events.
A single part process is the easiest application for a OEE pilot project. The single part process also makes it easier to demonstrate some of the more advanced Lean Thinking tools that can be applied to improve your operation or process. In our “Variation, Waste, and OEE” post, we introduced the potential impacts of variance to your organization. We also restated our mission to control, reduce, and eliminate variation in our processes as the primary objective of LEAN.
We need to spend more time understanding what our true production capabilities are. The single part process makes the process of understanding these principles much easier. The lessons learned can then be applied to more complex or multipart processes. In multipart or complex operations, production part sequencing may have a significant impact on hourly rates and overall shift throughput. How would you know unless you actually had a model that provided the insight?
Process Velocity: Measuring Throughput
Let’s start this discussion by asking a few simple questions that will help you to get your mind in gear. Do you measure variation in production output? Do you measure shift rates? Do you use the “average” rate per hour to set up your production schedules? How do you know when normal production rates have been achieved? Does a high production rate on one shift really signify a process improvement or was it simply a statistically expected event?
Once again an example will best serve our discussion. Assume the following data represents one week of production over three shifts:
Machine A: Production Process Performance Report
| Cycle Time (Seconds): | 57 | |||||
| Shift Standard (440 minutes) | 440 | |||||
| Day | Shift | Planned | Quantity | |||
| Production Time | Total | Test | Scrap | Accept | ||
| Mon | 1 | 440 | 420 | 1 | 2 | 417 |
| Mon | 2 | 440 | 390 | 1 | 1 | 388 |
| Mon | 3 | 440 | 320 | 1 | 3 | 316 |
| Tue | 1 | 440 | 361 | 1 | 1 | 359 |
| Tue | 2 | 440 | 392 | 1 | 5 | 386 |
| Tue | 3 | 440 | 365 | 1 | 2 | 362 |
| Wed | 1 | 440 | 402 | 1 | 7 | 394 |
| Wed | 2 | 440 | 317 | 1 | 6 | 310 |
| Wed | 3 | 440 | 430 | 1 | 1 | 428 |
| Thu | 1 | 440 | 453 | 1 | 5 | 447 |
| Thu | 2 | 440 | 419 | 1 | 3 | 415 |
| Thu | 3 | 440 | 366 | 1 | 1 | 364 |
| Fri | 1 | 440 | 400 | 1 | 2 | 397 |
| Fri | 2 | 440 | 411 | 1 | 4 | 406 |
| Fri | 3 | 440 | 379 | 1 | 2 | 376 |
| Totals | 15 | 6600 | 5825 | 15 | 45 | 5765 |
The following table is an extension of the above table and shows the unplanned downtime as well actual, standard, and ideal operating times.
| Day | Shift | Unplanned | Operating Time | ||
| Down Time | Actual | Standard | Ideal | ||
| Mon | 1 | 25 | 415.0 | 399.0 | 396.2 |
| Mon | 2 | 55 | 385.0 | 370.5 | 368.6 |
| Mon | 3 | 122 | 318.0 | 304.0 | 300.2 |
| Tue | 1 | 84 | 356.0 | 343.0 | 341.1 |
| Tue | 2 | 65 | 375.0 | 372.4 | 366.7 |
| Tue | 3 | 82 | 358.0 | 346.8 | 343.9 |
| Wed | 1 | 45 | 395.0 | 381.9 | 374.3 |
| Wed | 2 | 130 | 310.0 | 301.2 | 294.5 |
| Wed | 3 | 30 | 410.0 | 408.5 | 406.6 |
| Thu | 1 | 5 | 435.0 | 430.4 | 424.7 |
| Thu | 2 | 40 | 400.0 | 398.1 | 394.3 |
| Thu | 3 | 90 | 350.0 | 347.7 | 345.8 |
| Fri | 1 | 45 | 395.0 | 380.0 | 377.2 |
| Fri | 2 | 45 | 395.0 | 390.5 | 385.7 |
| Fri | 3 | 60 | 380.0 | 360.1 | 357.2 |
| Totals | 15 | 923 | 5677 | 5533.8 | 5476.8 |
The table below shows the OEE calculations for each day and shift worked. Note that this table is also an extension of the above data.
| Day | Shift | Overall Equipment Effectiveness (OEE) | |||
| Availability | Performance | Quality | OEE | ||
| Mon | 1 | 94.3% | 96.1% | 99.3% | 90.0% |
| Mon | 2 | 87.5% | 96.2% | 99.5% | 83.8% |
| Mon | 3 | 72.3% | 95.6% | 98.8% | 68.2% |
| Tue | 1 | 80.9% | 96.3% | 99.4% | 77.5% |
| Tue | 2 | 85.2% | 99.3% | 98.5% | 83.3% |
| Tue | 3 | 81.4% | 96.9% | 99.2% | 78.2% |
| Wed | 1 | 89.8% | 96.7% | 98.0% | 85.1% |
| Wed | 2 | 70.5% | 97.1% | 97.8% | 66.9% |
| Wed | 3 | 93.2% | 99.6% | 99.5% | 92.4% |
| Thu | 1 | 98.9% | 98.9% | 98.7% | 96.5% |
| Thu | 2 | 90.9% | 99.5% | 99.0% | 89.6% |
| Thu | 3 | 79.5% | 99.3% | 99.5% | 78.6% |
| Fri | 1 | 89.8% | 96.2% | 99.3% | 85.7% |
| Fri | 2 | 89.8% | 98.8% | 98.8% | 87.7% |
| Fri | 3 | 86.4% | 94.8% | 99.2% | 81.2% |
| Totals | 15 | 86.0% | 97.5% | 99.0% | 83.0% |
The results from the table above suggest that the process is running just short of world-class OEE (83% versus 90% for dedicated processes. Note that 85% is considered world-class for multipart variable processes). As you can see from the daily and shift results, a lot of variation is occurring over the course of the week. This is the opportunity that we need to pursue further. A quick scan of the data suggests that Wednesday 2nd shift and Monday 3rd shift are the main contributors to the reduced OEE. We will investigate the data a little further to really understand what opportunities exist.
A dedicated, continuous process should yield a higher OEE since the process is not subject to continual setup and change over. Although some model changes or variations to the existing product may exist, they are typically less disruptive. A OEE of 90% may be an achievable target and is typical for most dedicated operations.
FREE Downloads
We are currently offering our Excel OEE Spreadsheet Templates and example files at no charge. You can download our files from the ORANGE BOX on the sidebar titled “FREE DOWNLOADS” or click on the FREE Downloads Page. These files can be used as is and can be easily modified to suit many different manufacturing processes. There are no hidden files, formulas, or macros and no obligations for the services provided here.
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Until Next Time – STAY Lean!
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