Like Lean Manufacturing and Six Sigma, Overall Equipment Effectiveness (OEE) is a key tool for achieving operational excellence. Although the pharmaceutical industry is five to 12 years behind discrete manufacturing in applying this concept, more pharmaceutical companies, including AstraZeneca and Merck, are including OEE as part of their operational excellence toolkits and discovering how it can help quantify efficiency and improve overall operations.
This article will present a brief overview of OEE and show how the concepts behind it can help drive manufacturing excellence at your operations. It will also highlight the critical link between OEE data and business metrics, notably Income from Operations (IFO). This connection is essential in communicating to management, and in helping you develop the most effective strategy for achieving operational excellence at your facility.
OEEs roots can be found in Total Productive Maintenance, a term coined by Seiichi Nakajima  that quantifies all losses or deviations from perfect manufacturing. TPM is completely in line with Lean Manufacturing and the Toyota production system.
Simply defined, OEE is: The amount of ideal production time relative to the actual scheduled time used, or the amount of good product produced relative to the amount of total product that could have been made with 100% first-pass yield at the ideal rate for the actual scheduled time used.
Availability = actual run time ÷ actual scheduled time used
Speed Rate = ideal speed rate ÷ actual speed rate (maximum of 1.0)
Quality Rate = amount of good product ÷ total amount of product made.
Also important to OEE is Total Effective Equipment Performance (TEEP), or the amount of ideal production time relative to the actual calendar time used, or the amount of good product produced relative to the amount of total product that could have been made with 100% first-pass yield at the ideal rate for the actual calendar period used. This metric is used to determine overall asset usage before investing capital for capacity expansion. A simple back of the envelope calculation can be done, and usually the TEEP number is significantly lower than the current OEE value, particularly for pharmaceutical companies that work a relatively low number of shifts and weekends when compared with other industries.
Figure 1 may be helpful in allowing you to visualize OEE and TEEP. The gold portion of the chart represents the amount of perfect production time, or Theoretical Factory time, arrived at by dividing the total amount of good product produced by the ideal speed rate of units per time increment.
Losses generally take one of the following forms:
- Planned Unlike TEEP, OEE excludes all planned downtime. Planned downtime would include major shutdowns, periods during which there are no orders, planned holidays, weekends, shifts not worked, planned lunches and breaks and meetings, experiment time, and downtime for completing orders early.
- Operational These losses occur when the equipment is not running, such as during changeovers, pit stop maintenance, process stops for cleaning and unplanned equipment problems, quality problems, lack of manpower, lack of information or lack of supplies. Operational losses can be planned or unplanned, and data collection is critical in eliminating unplanned losses and mitigating planned downtime. Automated data collection can be particularly useful, especially data organized based on product run.
- Speed These types of losses occur when operations do not run at the ideal speed, or the highest accredited speed or equipment design speed limits. (This factor must be 1.0 or less. If it is greater than 1.0, it means that a new ideal speed has been established.) Minor equipment stops and jams accumulate as speed losses. So do instances where runtime speed is reduced.
- Quality This type of loss results when any produced units are not transferred on the first pass. Rework has zero OEE value until it is corrected and transferred.
If the specific equipment system being reviewed is not the bottleneck of the product flow, then the ideal speed rate could 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. All events that require higher than desired speed to meet order rate should be recorded for analysis and improvement opportunity.
OEE is important for operations, such as pharmaceutical manufacturing and packaging, that run fewer than 24 hours per day, or are not sold out. TEEP is the important metric for 24/7 or sold out operations.
Recently, demonstrated world-class OEE levels were determined for the pharmaceutical industry (Pharmaceutical Manufacturing, January 2006, p. 11). Levels were determined for different business conditions, depending on the number of products produced by the equipment system. The following was information combined from Granulation, Compression, Film Coating, C/E, and hybrid operations:
|Number of Stock Keeping Units (SKUs)||% OEE|
|Low SKU* (1-2 SKUs)||83%|
|Medium SKU (3-5 SKUs)||80%|
|High SKU (6-12 SKUs)||73%|
|Very High (≈20 SKUs)||63%|
Since the drug industry is highly regulated and extremely safety-conscious, SKU changeovers are critical events. For even the most efficient pharmaceutical companies, the best demonstrated changeover time is still close to 2 hours. Compare that to the times achieved by other industries, some of which have reduced die changes from over 12 hours to less than 10 minutes. Changeover time reduction is likely to remain a top goal for pharmaceutical companies.