Overall equipment effectiveness: an old metric offers new ways of boosting performance

New business realities are leading manufacturers back to an old technique to improve plant performance. Overall equipment effectiveness (OEE)—a metric introduced in the 1960s during the first total quality/continuous-improvement era—is making a comeback, particularly among manufacturers with product mixes that require frequent equipment changeovers.

“OEE has become one of our most important manufacturing-related key performance indicators [KPI],” declares John Tilbrook, group VP of manufacturing processes at Hamburg, Germany-based Hermes Abrasives Ltd.

Since adopting OEE as a KPI, Tilbrook says, Hermes has found its plant-floor operators “looking for ways to improve their numbers each day in much the same way we all look to improve our personal achievements.”

Hermes and other manufacturers are finding that good OEE numbers typically lead to many more positive statistics, including:

• Reduced equipment downtime;
• Increased labor efficiency;
• Higher product quality; and
• Lower production costs.

Some manufacturers are finding OEE helpful in making critical business decisions such as:

• When to buy new production equipment;
• Which plants to ship orders to; or
• Whether some orders should be accepted at all.

As the term implies, OEE is a measure of how well manufacturing equipment is running in relation to a company's ideal level of performance. The formula for calculating OEE is: availability x performance x quality.

Availability refers to the machine being available for production when scheduled. It compares scheduled run time to actual run time.

Performance equates to the speed at which equipment runs. The key variable is how much waste is created by running at less-than-optimal speed.

Quality is a measure of time wasted producing parts that do not meet quality standards.

Julie Fraser, a principal with Cummaquid, Mass.-based Industry Directions, believes interest in OEE is resurgent because it is, in many ways, the ideal metric for today's frenetically paced manufacturing environment.

Because OEE relies on sensors connected directly to production equipment to generate the data that feeds its formula, the metric can deliver a real-time picture of plant performance. The data collected also forces plant operations to be analyzed from multiple angles, which often inspires everyone in a plant to take an interest in how the entire facility is running—not just the specific area or machine to which they are assigned.

“Historically, people in plants have had extremely granular metrics,” says Fraser, who also notes that new advances in manufacturing-oriented software are allowing companies to incorporate OEE in broad-based performance-improvement initiatives.

“A lot of software vendors have capabilities for OEE today,” Fraser says. “Some are very basic, while some are very advanced, with multilevel drill-downs.”

The advanced systems enable isolating the causes of poor OEE numbers—which could be anything from faulty incoming material to improperly calibrated equipment—and that's why Fraser predicts, “There will be more of these systems” coming onto the market.

James Feltman is sales manager and lead trainer for Vorne Industries, a supplier of systems that collect plant data and use it to calculate OEE numbers. He also expects the use of this metric to continue spreading.

“Manufacturers realize it's not only a great management metric, but it's also great for the people on the plant floor because they can use the constituent variables to provide some real-time information that can be used to make improvements,” Feltman states.

Vorne offers three products for calculating OEE. The XL400 can push real-time production data to the plant floor and a company network. The XL600 adds color changes or flashes to enhance awareness of the data. The XL800 adds integrated Ethernet communications to facilitate enterprise-wide data sharing.

Feltman says real-time data collection is one of the biggest benefits of OEE. “In many cases, managers attempt to perform an 'autopsy' from manufacturing reports with data that is a week old,” he points out. “They are trying to figure out what happened, and then implement solutions that end up being reactive.”

With real-time OEE data, it's possible to identify and address problems as they arise. Also, the data can be pushed down through various levels of the organization, with supervisors and even line workers being trained to identify and address problems.

“OEE can aid in the decision about whether or when to purchase new equipment,” explains Feltman. Right now, Vorne is working with a privately held company with three plants. The owner is committed to purchasing new equipment when it's actually needed to meet increasing customer demand. However, he had concerns about how to determine that. The company installed two of Vorne's devices and quickly realized that there was a lot of opportunity to improve the performance of existing equipment.

OEE can be useful in determining which plants to send orders to, though there is a caveat. “The only way this can be done successfully is if every plant is standardized on the metrics, and all have agreed collectively that these are the metrics they want to use to determine which plants are more efficient and should thus get the orders,” Feltman explains.

OEE also can be used to determine how many orders to accept in the first place. One of Vorne's customers makes cardboard boxes, a highly competitive business in which customer satisfaction of the utmost importance. As such, this particular company did want to accept more orders than it could handle.

“On the other hand, the company wanted to find any hidden capacity that was available so that it could use that capacity to accept more orders,” Feltman says.

When the company started collecting data for each product, it found that it was more efficient than it thought with some products, and could actually become more competitive with its pricing. “Conversely,” says Feltman, “it found that the discounts it had been giving on some actually were unprofitable.”

Hermes Abrasives started looking at OEE as a key performance indicator in its U.S. operations in May 2006. At the time, the company had just hired a new chief operating officer from the automotive industry who was familiar with OEE, and knew how beneficial it was in driving a continuous-improvement philosophy.

“We started using Vorne's XL800 data recorder in August 2006,” says Hermes' Tilbrook. The device, which collects plant data automatically, comes with a bright digital display that can post performance-related numbers for all operators to see.

“We overcame the inevitable 'big brother' questions by assuring the operators that the device was a scoreboard against which they could judge whether they were 'winning or losing,' and thus modify their own performance,” Tilbrook explains. “Giving them autonomy to make changes was important to ensuring successful implementation.” Hermes also allowed the operators to decide what data they wanted to see displayed. As a result, the equipment now displays target and actual output numbers, downtime minutes, and run time, in addition to the availability, performance, and quality figures.

Building on that success, Hermes now has an investment program to add Vorne XL800s to all of its key manufacturing lines in the U.S.—14 more in total.

Acumence, a supplier of manufacturing intelligence software, put OEE capabilities into the latest version of its product suite in response to customer demand.

“OEE is a very specific performance measurement, but our customers frequently use it in conjunction with other metrics,” states David Brochu, an Acumence executive VP.

The Acumence customer base is heavily populated with companies that fit the profile industry analysts believe can benefit most from the OEE metric: manufacturers that run multiple products on the same lines, which forces them to make frequent equipment changeovers. Brochu says these companies “want to apply efficiency and performance measures across the organization, so a typical solution will include OEE metrics at the machine, line, plant, and enterprise level; as well as many other metrics and efficiency measures.”

The beverage can unit of Rexam, a London-based manufacturer of packaging for consumer products, turned to Acumence after struggling to get traditional control-level solutions and legacy systems to deliver high-value production data to all levels of the company. Rexam management also wanted a system that could report short-duration downtime events—i.e., a minute or less—which, if left unchecked, can eat away at productivity and ultimately profit.

Acumence solves these problems by offering a high-performance plant-measurement solution that can be easily configured for beverage can manufacturing, and also tie into other enterprise systems. The resulting standardized measures can focus attention on plant bottlenecks and empower management to drive improvement, especially in throughput.

“Right now, the Acumence Manufacturing Business Intelligence Solution is probably the most valuable systems tool we have in our arsenal,” states Dave Wilke, operation excellence process manager for Rexam. “For one reason, it provides us with real-time information.”

The biggest challenge for Rexam was determining what data it needed to collect to generate valid performance metrics.

“We needed to make sure we got data that would clearly help us understand how our operation was running,” Wilke relates. “Once we got that set up, the rest was easy. Now Rexam can see, in real time, exactly how well each plant is performing.”