Overall Equipment Effectiveness (OEE)
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In today's economy, you're expected to continuously improve your Return on Total Capital. And as capital to build new, more efficient plants becomes more difficult to obtain, you often have to meet growing production demands with current equipment and facilities — while continuing to cut costs. There are several ways you can optimize your processes to improve profitability. But it can be difficult to understand the overall effectiveness of a complex operation so you can decide where to make improvements. That's especially true when the process involves multiple pieces of equipment that affect each other's effectiveness. To meet this challenge we can use OEE or Overall Equipment Effectiveness. It helps in controlling not only human resources but also equipment usage.
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HOW TO USE OEE?
WHY USE OEE?
In today's economy, you're expected to continuously improve your Return on Total Capital. And as capital to build new, more efficient plants becomes more difficult to obtain, you often have to meet growing production demands with current equipment and facilities — while continuing to cut costs.
There are several ways you can optimize your processes to improve profitability. But it can be difficult to understand the overall effectiveness of a complex operation so you can decide where to make improvements. That's especially true when the process involves multiple pieces of equipment that affect each other's effectiveness.
One metric that can help you meet this challenge is Overall Equipment Effectiveness, or OEE. OEE measures the health and reliability of a process relative to the desired operating level. It can show you how well you're utilizing resources, including equipment and labor, to satisfy customers by matching product quality and supply requirements.
Overall Equipment Effectiveness (OEE) measures total performance by relating the availability of a process to its productivity and output quality.
OEE addresses all losses caused by the equipment, including
• Not being available when needed because of breakdowns or set-up and adjustment losses
• Not running at the optimum rate because of reduced speed or idling and minor stoppage losses
• Not producing first-pass A1 quality output because of defects and rework or start-up losses.
OEE was first used by Seiichi Nakajima, the founder of total productive maintenance (TPM), in describing a fundamental measure for tracking production performance. He challenged the complacent view of effectiveness by focusing not simply on keeping equipment running smoothly, but on creating a sense of joint responsibility between operators and maintenance workers to extend and optimize overall equipment performance.
First applied in discrete manufacturing, OEE is now used throughout process, batch, and discrete production plants.
The overall performance of a single piece of equipment or even an entire factory will always be governed by the cumulative impact of the three OEE factors:
Availability, Performance Rate and Quality Rate.
OEE is a percentage derived by multiplication of the three ratios for the factors mentioned above. The OEE percentage is used for analysis and benchmarking.
What is OEE?
OEE = Availability X Performance Rate X Quality Rate
OEE is calculated by multiplying three factors: availability, productivity, and quality.
% OEE = ( % Availability ) * ( % Productivity ) * ( % Quality )
The values used can reflect an entire processing plant, a process line, or an individual piece of equipment.
For individual equipment, the performance of the equipment is compared to earlier values for the same equipment or to similar pieces of equipment. Changes in OEE or its elements are tracked and trended over time. OEE for a process line treats the entire line as a single unit, regardless of how much equipment it includes. For multiple-recipe or batch operations, OEE is calculated for each product produced. Like a process line, a process plant performs as a whole, and OEE is therefore calculated for the entire plant as a unit.
Percent of scheduled production (to measure reliability) or calendar hour’s 24/7/365 (to measure equipment utilization), that equipment is available for production
Equipment availability isn't just assumed to be the length of the shift in which it is operated. Instead, it's based on actual operating time, as a percentage of the possible production time.
Actual production time
% Availability = __________________________
Possible production time
A process line is operated 24 hours a day, 5 days a week (120 hours). Planned downtime for preventive maintenance is 1 hour each week. Unplanned downtime due to equipment failure and equipment adjustment is 7 hours.
% Availability = (120-1-7)
(120 - 1)
Even the best operations have some downtime. What makes them the best is keeping availability as high as possible. Here are some typical availability values to benchmark your own process against.
Process Type Quartile
Worst 3rd 2nd Top
Continuous <78% 78-84% 85-91% >91%
Batch <72% 72-80% 81-90% >90%
Chemical, Refining, Power <85% 85-90% 91-95% >95%
Paper <83% 83-86% 87-94% >94%
Flour Global Services — Benchmark study — NA, AP, EU — 1996
For large complex assets or fleets of capital equipment, availability typically runs between 85%-95%.
The 5%-10% of non-availability is split between "planned downtime" (scheduled maintenance) and "unplanned downtime" (breakdowns).
How can I measure and improve availability?
Availability is simply a way to quantify how much of the time your equipment or process is up and running as it should. The higher the availability, the more you can produce — and the greater your Return on Assets.
Your goal, therefore, is to minimize downtime — especially unplanned downtime — by improving process and equipment reliability. This course provides an overview of availability as a factor in OEE.
Percent of parts produced per time frame, of maximum rate OEM rated production speed at. If OEM specification is not available, use best-known production rate.
Productivity can be calculated by looking at the actual output produced by the equipment as a percentage of the theoretical output, given its optimum speed and actual running time.
The sustained capacity of a plant is 600,000 tons per year. Last year it produced 560,000 tons.
% Productivity = Actual production
= ¬560,000 tons
How can I improve OEE by increasing productivity?
While the availability portion of Overall Equipment Effectiveness describes the percentage of available operating time that equipment is actually running, productivity measures how much is produced during that run time.
Many process plants are capable of higher productivity than they currently achieve. The difference between current and potential productivity is an opportunity to increase output — and profits.
This course covers some of the causes of low productivity in process plants, an approach for improving productivity, and how to calculate the results as part of Overall Equipment Effectiveness.
Percent of good sellable parts out of total parts produced per time frame.
Calculating quality rate
The quality rate used in OEE calculations is defined as:
% Quality = ¬Product produced -- (scrap & rework)
For example, a plant produced 550,000 tons of product, but only 485,200 tons met specifications on the first pass.
% Quality = 550,000 - (550,000-485,200)
550,000 - 64,800
How can I improve the quality factor in Overall Equipment Effectiveness?
The third factor that affects profitability is product quality — the percentage of "on-spec" output produced during the first pass through the production sequence.
Improved regulatory control
A regulatory control system can help you produce a uniform product that consistently meets customer quality demands at the lowest cost. It does this by minimizing variance throughout the processing cycle — whether that variance is caused by changing feedstock quality, ambient conditions, equipment performance, or a host of other factors.
Without an effective regulatory control system, each successive unit operation can introduce variation that can accumulate throughout the process. The cumulative variation is reflected in final product quality and the overall cost of production.
Industry studies indicate that 20 - 40% of process controllers are operated in manual mode, missing the opportunity to reduce variability through automated control.
Studies have also shown, however, that more than 30% of the loops that are automated loops actually increase variability over manual control because of poor tuning. Many of these loops have equipment problems, including oversized and undersized valves; excessive hysteresis, resolution, or stick-slip in the valves; and measurement problems.
The enhanced functionality and performance of intelligent field devices help minimize these problems, allowing operators to turn on "auto" control. Easy access to device data enhances loop inspection capabilities to eliminate factors affecting variability in a control loop and ensure the reliability of the field measurements. Critical control loops can now be effectively tuned to achieve the next level of additional revenue generating opportunities.
Advanced control systems control the process as each variable relates to overall productivity or effectiveness. These systems are not single-loop controls, but a multi-variable envelope representing the constraints of pressure, temperature, and other factors. Within the envelope, the process is continuously maximizing effectiveness.
Advanced control systems run continuously; responding to changes, reducing the impact of upsets, and exploiting opportunities to create more profit. They are especially valuable where production targets or the quality and availability of raw materials can all change relatively quickly, so that the operating constraints and the scope for improvement vary from day to day.
HOW TO USE OEE?
Implementing the Overall Equipment Effectiveness formula in your facility can take on many different forms. It can be used as an analysis and benchmarking tool for either reliability, equipment utilization, or both. Don't let indecision on how to best use OEE become a barrier that prevents you from using it at all. Start out small if necessary, picking your bottleneck to collect the OEE metrics on.
Once you see first hand what a valuable tool it is, you can gradually take OEE measurements on other equipment in your facility. If you work in manufacturing, there is no substitute for going out to the shop floor and taking some rough measurements of OEE. You will be surprised by what you find!
While monitoring OEE per equipment brings focus on the equipment itself, it may not provide true cause of major costs, unless the cause is obvious. For example OEE can appear improved by actions such as purchasing oversize equipment, providing redundant supporting systems, and increasing the frequency of overhauls.
To improve your OEE percentage, you will need to use other tools and methodologies available to you, like TDC, RCA, FTA etc. TDC is a relatively new methodology that focuses on True Downtime Cost for justification and making better management decisions.
WHY USE OEE?
Overall Equipment Effectiveness (OEE) can be used to save companies from making inappropriate purchases, and help them focus on improving the performance of machinery and plant equipment they already own. OEE is used to find the greatest areas of improvement so you start with the area that will provide the greatest return on asset.
The OEE formula will show how improvements in changeovers, quality, machine reliability improvements, working through breaks and more, will affect your bottom line.
As you strive towards World Class productivity in your facility, this simple formula will make an excellent benchmarking tool. The derived OEE percentage is easy to understand and displaying this single number where all facility personnel can view it, makes for a great motivational technique. By giving your employees an easy way to see how they are doing in overall equipment utilization, production speed, and quality, they will strive for a higher number!
It is highly recommend using an automated equipment monitoring system with an LCD display for your OEE in each respective area of your facility so all can monitor. To the employee in each area, it will become as common to glance at, as the speedometer on a car.
The OEE calculation provides focus and simplicity to aid in decision making. It can help you
• Identify areas for improvement
• Assess incremental revenue opportunities
• Benchmark your operation against similar or competitor processes
For example, by tracking the factors that determine OEE, you can determine whether your equipment experienced more downtime (planned or unplanned) than expected, or was running at a slower pace or with minor stops, or produced more defects.
Root cause analysis begins by focusing on the type and extent of loss, not the OEE percentage rating itself. Both Operations and Maintenance should be involved in making improvements — whether reducing unplanned downtime, increasing process productivity, or improving product quality.
Published benchmark values for the factors of OEE are also excellent indicators of a process's competitiveness in the market. For example, when measuring Overall Equipment Effectiveness for the first time, process plants may find they are only achieving around 40%-70% OEE (batch) or 50%-80% (continuous process). International best practice figures are recognized to be +90% (batch) and +95% (continuous process).
Overall Equipment Effectiveness
Benefits include significantly reducing downtime caused by equipment failure, as well as avoiding the higher repair costs of unexpected catastrophic failures.
Predictive maintenance also reduces the need to schedule downtime for preventive servicing, which guarantees increased availability.
The new economy required management technology not only for active control of human resources but also an equally or even greater control on equipment usage. This OEE has full exploited the new manufacturing technology and has raised the level of competition and increase the range of competitive standards.
2. googleseminar and presentation on oee
5. Overall Equipment Effectiveness, Robert C. Hansen
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