[Quality Systems] Overall Equipment Effectiveness

Is your equipment operating at maximum effectiveness? Is its availability, performance or quality output affecting your production?
How do you know?

Overall Equipment Effectiveness (OEE) is a quality systems management tool that enables a manufacturer to assess the effectiveness of its equipment based on the combined acquisition and assessment of three metrics: availability, performance and quality. Using OEE as a tool, the manufacturer can identify major losses, said John Kravontka, president, Fuss & O’Neill Manufacturing Solutions, “creating a road map to find problems and enhance capacity.”

“You can’t fix it if you don’t know it’s broken,” added Thomas Cutler, president and CEO of the manufacturing marketing firm TR Cutler. “You have to know where the problem is.” Sometimes you will discover that it is an employee issue, sometimes an equipment issue, he said. “But most importantly, you find out where you are losing optimized effectiveness.”

To detect problems causing this loss, OEE looks at availability, performance and quality of each individual machine, which can then be assessed against the whole in complex production equipment. “The individual parts are constituents of the whole,” said Jim Feltman, sales manager, Vorne Industries. If each of the three metrics operated at 100 percent, your equipment would be working at its optimal rate, “but any one metric can affect the others greatly.”

THE CALCULATION. Attaining what is considered to be world class equipment effectiveness through OEE is, in fact, a difficult achievement. It is determined by multiplying three metrics — availability, performance and quality.

In this equation, availability is operating time/planned production time; performance is total pieces/operating time/ideal run rate; and quality is good pieces/total pieces.

Translated into numbers, a very good OEE is considered to be 85 percent, with specific metrics achieving rates of:

• Availability — 90 percent
• Performance — 95 percent
• Quality — 99.9 percent

Because each metric has an impact on the others, the total is less than each of the parts. Say, for example, you make doughnuts. If your optimal output is 12,000 doughnuts per hour, but only 90 percent of your equipment is available, you can only produce 10,800 doughnuts. If the performance of the available equipment is running at 95 percent, you will only be able to produce 10,260 doughnuts instead of 10,800. If only 99.9 percent of those doughnuts meet your quality standards, you will be producing 10,250 doughnuts per hour. Dividing 10,250 doughnuts by the optimal output of 12,000 doughnuts equals an 85 percent effectiveness rate. (This chart further illustrates this equation.)

While these calculations can be extremely valuable, they also can be deceiving and under-utilized.

For example, a plant may calculate the OEE total to be higher for one shift, but if that is a result of high equipment availability and performance but low quality, the final product is adversely affected, potentially to the point of creating unrecoverable loss. “You can run half the time at half the speed, but you can never run at half the quality,” Feltman said.

USE THE DATA. In addition, Kravontka said, while the tool can be used to determine current output and baseline your equipment, if the plant stops there, it is simply playing a numbers game and losing the real value of OEE.

Implementing the full scope of OEE means taking the next step to assess the collected data, determine the cause of equipment inefficiencies and implement corrective action. “Using OEE as a tool, you can pinpoint what to go after,” Kravontka said. “Collect it, then use it.”

Through equipment inefficiencies, plants can incur billions of dollars in waste, Kravontka explained, including costs of increased labor, overtime charges, penalties for late product, lost sales, lost customers, cost of quality and scrap, and extra production to compensate for equipment failure. Incorporating OEE helps the plant to reduce or eliminate such costs by identifying causes so that corrective action can be implemented. 

In particular, OEE addresses six root causes of loss found in today’s manufacturing: breakdowns; setup and adjustments; idling and minor stops; reduced speed; startup rejects; and quality defects and rework. 

Although OEE has been used in America for decades, Kravontka estimates that less than half the people in the industry probably even know about it, and fewer apply it in their plants. But, as statistics across industries show, the current state of manufacturing is indicating a real need for the type of intervention and improvement provided through OEE. In today’s typical manufacturing conditions:

• breakdowns occur regularly
• temporary repairs are the norm
• a run-to-failure mentality is predominant
• constant adjustments interrupt production
• minor stoppages occur frequently
• processing speeds decrease
• equipment does not repeat
• operator training often is inadequate

And, because no one is charged with tracking these losses, no one is held accountable.

ELIMINATING WASTE. The ever-increasing rigor of tracking and tracing in the food industry is continuing to decrease the margins under which food companies must operate and causing manufactures to seek increased efficiencies in all areas. “That kind of rigor costs a lot of money,” Cutler said, explaining that plants are approaching the costs by asking, “Where can we eliminate waste on the plant floor?” and “We think our production is X, but how do we know?”

The only way to know, he said, is to track production and determine if the target was achieved. And if it did not hit its target, “you have to find where it is slipping through the cracks.” Often, he added, it is the so-called little things that add up to significant loss. As an example, Cutler cites a plant that realized, “If we could save just 20 minutes a day in our changeover, we would pay for our new QC director.”

Cutler also sees OEE as more than a lean process, rather, he expects it to increasingly impact industries as regulatory requirements continue to increase. “I don’t think you can look at OEE in a bubble,” he said. “Food is often where this starts because there has been great speculation in regulatory bodies that if there is another terrorist strike, it will come through the food chain.”

“Food manufacturers, in particular, have some very interesting challenges, and that’s that they produce their product with ingredients that can be perishable,” Feltman said. When a line goes down, the plant literally needs a timer because after a minimal amount of time, the product perishes, the line has to be purged and a wash down executed.

DON'T TWEAK THE METRIC. OEE can be quite challenging when it is first utilized in a plant, Feltman said, so plants often will be tempted to hide or tweak the numbers at the outset. In fact, if the data is being collected manually and the results are divisible by five, he said, “you’re probably guessing.”

“Don’t tweak the metric. Don’t change things to fit the situation,” Feltman cautioned. “Scores of 20 to 45 or 50 percent as an initial measurement are very, very common.” More important than the score at this point is the understanding of the issues and detection of inefficiencies — and continued improvement in assessment and efficiency.

Both Feltman and Kravontka recommend that plants begin the process manually. “Walk out to the machine and spend an hour watching how the operator works with it,” Kravontka said. Feltman recommends manual data collection in order to become better connected with the process and understand how the equipment and personnel function on an efficiency level.

Once you are connected, “now identify the problems. Look at where your biggest holes are,” Feltman said. “The major goals of OEE are to expose hidden inefficiencies.” Collect the data, use it intelligently for improvement, and your entire plant will gain value.  “It doesn’t cost a whole lot to do, and your plant will become more competent from within.” 
 
The author is staff editor, QA magazine.