Glen Lawson was certain that additional automation technology would improve his plant’s throughput. As production manager at a new Salem, Ore., plant owned by SpaceKraft, an Indianapolis-based container manufacturer, Lawson knew that profitability would improve with added technology. The corporate managers back in Indianapolis at the Weyerhaeuser-owned company, however, wanted proof.

Lawson delivered that proof in tangible before-and-after numbers derived from his overall equipment effectiveness (OEE) data collection system. “I’ve spent some money on automation. I’ve documented the improvements to my machine,” he says. “Now I come back to my financial vice president and justify the spending based on machine data.” Lawson used OEE data to gain credibility with company bean counters, which allows him to continually improve the Salem plant—provided he continues to prove the case financially.

Lawson relied on plant metrics software supplied by Milwaukee-based Rockwell Automation Inc. to identify the actual cause of inefficiencies and machine downtime. “You can’t manage what you don’t understand,” Lawson observes. “So I knew we needed a tool that could collect, store and analyze production data over time.”

With the hard OEE data in hand, Lawson was able to identify constraints in the production line. “With our OEE system, we can analyze where our weaknesses are and where our opportunities are,” he explains. “If you know where the constraint is, you can improve the operation by doing X, and you can monitor the improvement.”

In the distant past, manufacturers could justify additional technology simply because it was new. Then came concerns over possible computing problems associated with the year 2000 (Y2K), and companies invested deeply in information technology (IT) to ward off potentially damaging system crashes. Y2K was followed by an explosion of IT offerings, and that was quickly followed by the stock market “dot com crash” and worldwide recession.

Tight purse strings

Financial managers grabbed the purse strings and said “no” to virtually all capital investment unless the return on investment (ROI) was both clear and profound. “Most manufacturers have to do some sort of financial justification for technology investment,” says Charles Rastle, a Rockwell Automation manufacturing consultant. “If you’re a cheese manufacturer and you can increase the yield of whey, you can justify the investment.”

One significant recent change is that plants now have to go begging for capital improvement dollars. “The IT buyers are holding the purse string these days,” says

Alison Smith, senior research analyst at Boston-based AMR Research Inc. “Plants don’t have the autonomy they used to have. Plant budgets are small and you need to have a pretty strong story to tell the finance guy.”

That story must be very, very good, others agree. Technology marketing managers on the front lines talk of the brutal demands made on vendors before the buy signs light up. “The finance managers want to see a big improvement. They want to see a return of ten times or more on the technology investment,” says Jim Frider, product marketing manager for DT Analyst, an application that measures OEE and is produced by WonderWare, an Invensys company based in Lake Forest, Calif.

That ROI also has to come quickly. Though capital spending budgets have rebounded somewhat, the long recession and subsequent freeze on capital spending has left a lot of unfilled needs in company operations. To get some of the budget, plant users must prove that ROI on an investment will arrive within a few short months. “The financial people are still looking for quick paybacks,” says Rockwell’s Rastle. “You have to show you’ll get ROI in six to 12 months.”

Currency of proof

To demonstrate clear ROI, plant operators have turned to hard metrics that can be easily translated into dollars. Many of those metrics are now coming from the plant’s OEE numbers. If plant users can boost throughput, reduce waste, reduce downtime or raise product quality, they can translate those improvements into dollars. The OEE metrics are the currency of proof. They’re hard numbers that can’t be fudged. If users can produce 10 percent more product in the same amount of time using the same equipment, they’ve made an appreciable and measurable contribution to a company’s bottom line.

But the ability to get more product out of the same raw materials by reducing scrap also translates into dollars saved. “The other side of throughput is waste or scrap. It’s easy to justify reducing it,” says Rastle. “Each pound of waste can be turned into a dollar.

Other vendors vouch for the effectiveness of OEE “currency.” One is Tom Mueller, business manager for asset optimization at ABB Inc., in Norwalk, Conn. “There are a number of reasons to invest in new technology—improve quality, competitive advantage—but in the end it comes down to dollars,” says Mueller. “OEE is a universal key performance indicator that assesses not only the availability of the equipment but product or asset utilization.”

Automation vendors are using OEE metrics to prove ROI, but they’re also using OEE to find opportunities for improvements. “If manufacturers have an idea of the cost per unit, we can use OEE to tell them how much the business impact of new technology will be,” says Tom Barczak, vice president at InSource Software Solutions, a Richmond, Va., value-added reseller (VAR) for Invensys’ Manufacturing Intelligence Group. “It not only proves out a project that has already occurred, but it also identifies opportunities ahead of time.” He notes that since OEE measures overall performance, from downtime to throughput and waste, it can point out inherent inefficiencies in a plant.

Subtle improvements

A manufacturer’s sensitivity to ROI depends somewhat on where the plant is located. In North America and Europe, manufacturing is mature, so new technology essentially takes a relatively efficient plant and makes it more efficient. Because the gains are incremental rather than drastic, OEE measurements are more important. “In the United States and Europe, they’re not building as much capital infrastructure, so there’s a lot of pressure to improve operations by showing a solid ROI,” observes David Ochoa, director of strategic planning in the Asset Optimization Division of Emerson Process Management, in Austin, Texas. “Manufacturers are using some aspects of OEE to justify their discretionary spending on new technology.”

In developing countries, ROI is not as critical because many of the plants are being updated from the stone age. “In the Americas, you have to justify the improvements,” says Pewter Jofriet, marketing manager for the Americas for the refining vertical at Morristown, N.J.-based Honeywell Inc. “In other regions such as Eastern Europe, they’re playing catch-up, so the improvements from automation are obvious.

The OEE metrics are useful for discrete manufacturing, but they don’t help much in the process industries. Instead, plant operators at process plants seek other hard numbers. These numbers are often measured in operator efficiency. Another approach is to use simulation software to show a before-and-after picture that can show improved efficiency from new technology.

Honeywell’s Jofriet notes that 42 percent of equipment failure comes from operators. “We’ve done a number of studies that create metrics about the operator,” says Jofriet. “It may be how many alarms they’re getting, and the new technology is justified when those alarm incidences are reduced. That reduction can improve throughput, and then it’s very simple to justify.”

Jofriet also uses simulation software to help prove a return on technology investment. Honeywell recently purchased Hysis simulation software from Aspen Technology. “With Hysis, we create models to show the best process,” says Jofriet. “We can use the simulation model to find optimization opportunities.” As well as finding opportunities, the simulation helps demonstrate the improvement when the model is compared to the simulation of processes before the technology investment.

However you measure plant improvements, financial managers want hard data before they’ll let go of the company’s purse strings. At discrete manufacturers, plant managers are turning to OEE metrics. At process manufacturers, operations managers use operator improvement data and simulation to prove the case for additional automation technology. ROI isn’t credible on paper alone any longer. Managers have to show measurable improvements that can be translated into dollars before they get new technology.

For more information, search keywords “OEE” and “return on investment” at www.automationworld.com.

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