True believers in continuous improvement are continuing to spread the good news about the strategic value of overall equipment efficiency (OEE). One such believer is Jeanette Provan at Spokane, Wash.-based Clearwater Paper Corp. After becoming plant manager at the paper manufacturer’s Chicago converting facility in Elwood, Ill., she began preparing fellow employees and putting new controls on the equipment for tracking and improving OEE.
As she explains, OEE has become a preferred performance metric among manufacturing professionals like her because it provides a common ground for quantifying and comparing the major factors that determine efficiency. OEE is the product of multiplying three factors—availability, performance (throughput), and quality—expressed as percentages of their ideal values (see nearby equations). For example, performance is the actual production rate or throughput expressed as a percentage of the designed capacity of the equipment.
“Using percentages equalizes the playing field to some extent,” notes Provan. To explain how, she offers an example of two hypothetical machines, one built to operate at 1,000 feet per minute and the other at 2,000 fpm. If both are operating at 1,000 fpm, one is running as fast as it can, so there is no use wasting resources by trying to get more from it. The other machine, however, has another 1,000 fpm of potential that a facility can tap before having to invest in a new line. Similar analyses of the other two OEE factors, availability and quality, can release even more potential, she says.
Because generating these benefits requires data, Provan asked a systems integrator to tie together the PLCs in her processes. “We now capture most electronic signals from the equipment—when it starts and stops, speeds up and slows down, and changes settings,” says Provan. The information flows into an historian, and the software calculates the OEE and other metrics for each process.
Collect data automatically
To get useful results, Provan and others stress the importance of collecting data automatically through a control network. Relying on people to enter it in a log after the fact is fraught with too many problems. “No matter how well intended operators are, they are not going to be able to recall everything that happened and when,” explains Provan. Operators, moreover, can only assume that a problem is occurring where it is manifesting itself, which can be a bad assumption if the problem that they are observing is actually a symptom of a fault that happened two or three steps upstream.
Without the objectivity and speed that automation provides, “folks in manufacturing can spend more time arguing about the data than they do focusing on the problems,” adds Todd Smith from Milwaukee-based Rockwell Automation (www.rockwellautomation.com). “Our recommendation is to take the data-integrity argument off the table by harnessing the control system infrastructure to collect performance data. That way, not only do we know that we’re getting accurate data, but we also are also getting granular data in a timely manner.”
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Provan is among those who are exploiting this granularity by using the analytical tools available in software packages to drill down into the detail. A reader responding to an Automation World online questionnaire suggested that users also apply statistical process control and other analytics to OEE data. “If you add to an OEE value on a dashboard or other display some indication as to whether it is stable, that can trigger management to drill down when things aren’t,” says Jeff Cawley, vice president of industry leadership at Northwest Analytics in Portland, Ore.
Another reader, Brian Romano, urges users to take advantage of today’s display technologies to disseminate information in formats that make sense for their circumstances. Because most management software that tracks OEE logs the relevant data in an SQL database, he often writes scripts to retrieve and display information on Web pages, dashboards, e-mail messages and marquees. “The Web pages allow for general distribution of data to anyone who needs to see it without having special software,” says Romano, who is managing member and systems engineer at PACsys LLC in Terryville, Conn.
Custom displays can serve other purposes, too, such as teaching and encouraging employees to use OEE. At Clearwater Paper, for example, Provan converted OEE statistics into cases, the metric that operators and other employees were used to seeing. The custom screens display the number of cases made and how the tally stands against the budget, as always. But they also show employees lost opportunity expressed as the number of cases thrown away as waste or not made because of downtime or slowdowns in the line. “Once we laid it out in terms of cases—waste cases, speed lost cases, and downtime lost cases—the picture became very clear to people,” she says.
Go where the data lead
Another important piece of advice is to go where the data takes you and to be open to what it is telling you. “You’ve got to commit to fixing the things that you find,” says Rockwell Automation’s Smith. “You may find out that your number one efficiency problem is something that you never thought was that significant.”
A case in point is an automated shrink-wrapping machine at the end filling line at a soda manufacturer. Because it continued to spit out its normal stream of wrapped product without any operator intervention, nobody had reason to pay it any attention. The machine got a lot of scrutiny, however, after operations installed Rockwell’s OEE monitoring software. “The data revealed that it was stopping hundreds of times per shift,” recalls Smith. The cause was an undersized heater.
As product entered the machine, the tunnel would cool down, causing the conveyor to stop until the temperature rose again. Although this cooling and heating cycle occurred so fast that nobody ever noticed it, the frequency was high enough to affect throughput. A simple upgrade of the heating elements increased throughput and, therefore, the machine’s capacity.
Do your homework
To garner the intelligence necessary for rooting out this kind of wasted capacity, Dave Basile found it necessary to invest time upfront to develop OEE calculations for his process and integrate those definitions into recipe and sequence controls. “Those are the two places where we spent the most of our time,” says Basile, who is director of continuous improvement and automation at Actavis Inc., a pharmaceuticals company headquartered in Elizabeth, N.J.
The effort was for some newly installed packaging machines currently undergoing validation at the plant in Edison, N.J., which is Actavis’ first formal implementation of OEE at the company’s New Jersey SOD (solid oral dose) sites. “There has been a lot of buzz around the metric for at least the last five years,” notes Basile. “And some of our manufacturing facilities overseas have been using it.” Management has since decided to adopt OEE as a common metric for assessing plant performance across multiple sites worldwide.
The adoption is occurring as the Edison plant upgrades to a new controls platform from B&R Industrial Automation (www.br-automation.com) of Roswell, Ga. First to receive the controls and the ability to track OEE were the new packaging machines that Actavis had ordered from Modular Packaging Systems Inc. of Randolph, Mass. Systems integrator iAutomation (www.i-automation.com) of Beverly, Mass. will be helping Basile and his team to apply the lessons learned in the packaging operation to the manufacturing processes.
Basile identifies the upfront work that he did to develop the initial requirements as the most important part of the project. Not only did he seek input from operations and other departments early in the process, but he also gathered the necessary background from as many sources as he could. “We attended a couple of seminars, had discussions with one of our internal Lean partners, and did some research on the web,” recalls Basile. “Then, we applied the best of what we learned.”
Among his discoveries was that, although the calculation of OEE is fairly uniform across industry, a few slight variations exist in how one defines some of the factors in the equation. An example is available time. “Some include setup time, some may not,” he says. Others disagree slightly over what constitutes planned downtime versus unplanned downtime.
“We tried to go with the most common definitions of those terms to avoid straying too far from the mainstream,” Basile says. He thinks it prudent to operate in the way that most of the industry is moving. Not only does the direction usually reflect best practice, but it also serves as the basis for any industry standard that may come along in the future, he adds.
Seek input early
A related success factor mentioned by users and experts alike is to involve the stakeholders from production, maintenance, operations and suppliers in the project early. “The more people that you can have involved early on, the smoother the implementation will be,” notes Peter Sarvey, an iAutomation engineer who contributed to the project at Actavis. Not only is their expertise vital for extracting the right details for performing the necessary calculations, but also receiving their input later in the process tends to generate extra work in revisions and testing that can cause delays.
The input is not limited only to definitions, control architecture and software. It can lead to improvements in machines themselves. “Equipment design impacts your ability to make improvements to OEE,” says Alex Lee, global account manager at Bosch Rexroth Corp. (www.boschrexroth-us.com), Charlotte, N.C., “Simple things like quick changeovers using servos in place of traditional mechanical adjustments can dramatically improve efficiency.”
Experts also often recommend limiting the scope of OEE projects, especially for the first implementation. “The challenge is to define a scope that is acceptable to all those involved,” says Valerie Biester, value-added services manager in the machine tool business unit of Siemens Industry Inc. (www.usa.siemens.com), Alpharetta, Ga. “Upper management wants to see how effective the entire plant is running, and the production staff wants to know why a particular machine is not being utilized as fully as possible.”
She recommends starting with a pilot project that focuses on basic, top-level information like production status and downtime. “Getting bogged down in detailed discussions on what to track too early on will complicate implementation,” she explains. It is usually better to add other details once the pilot is up and running and the staff becomes familiar with OEE and its concepts. Here, it can be helpful to seek advice from a trustworthy solution provider.
Although vendors can provide consulting services in a variety of ways, Phoenix-based Honeywell Process Solutions (www.honeywell.com/ps) prefers to start the process with a workshop that leads participants though looking at their past histories and categorizing the potential gains. This process has two benefits, according to Tom Williams, Honeywell’s program manager for operator effectiveness. “It ensures that we and the user are using the same definitions and that there is enough gain to expend the effort to track the right things,” he says. “If a customer’s OEE for a given area is already world-class, then trying to squeeze the unsqueezable makes little sense.”
Because most operations have much to gain, the workshop usually helps the participants to identify the low-hanging fruit. Hence, it is one of many tips for getting and maintaining good OEE.
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