Resources > APICS Magazine > October 2004 > Eureka!

Eureka!
Realizing the power of MES—at last

By Marty Weil

At-a-Glance

Manufacturers finally are beginning to appreciate that a manufacturing execution system (MES) can be applied to numerous enterprise functions, including data collection, performance metrics, and enhanced visibility into process improvement and supply chain management. Research shows that MES implementation can pay for itself within six to 24 months of execution. MES is most valuable as an integrated, single solution that controls and collects data, helping companies make informed decisions and verifying that products are manufactured correctly.

Neuroscientists recently identified the brain region involved with the famous “Eureka!” moments. According to researchers at Northwestern University and Drexel University, the moment of insight is accompanied by a telltale burst of neural activity in the right hemisphere of the brain.

If the entire manufacturing sector were to subject itself to a giant brain scan while the subject of manufacturing execution systems (MES) was suggested, those right hemispheres would be popping like camera flashes on Super Bowl Sunday. It has taken a while, but the lights have switched on when it comes to MES.

Due to their close interface with controls and operators—the speeds and feeds of the production environment—MES tools historically have had access to process performance information at the heart of manufacturing. Perhaps it is because of this strong association with the factory floor that manufacturers tend to relegate MES to that domain, ignoring or failing to appreciate how the technology can be leveraged for broader enterprise purposes.

But that is clearly changing.

“Over the past three to five years, we’ve started to see an evolution in MES, as manufacturers and vendors have begun to realize the value of information available through MES data,” says Alison Smith, senior research analyst at Boston, Massachusetts-based AMR Research. “For whatever reason, this wasn’t recognized early on; but rather suddenly the ‘Aha!’ has occurred.” She says people now recognize that MES data can establish relationships, develop performance metrics, and shed light on manufacturing asset behavior.

ROI Beyond Operations
In a report co-authored by Smith, AMR Research interviewed more than 20 manufacturers across various industry segments about the return on investment (ROI) they were seeing from their MES. Survey findings include the following.

• MES paid for itself for traditional cost-reduction measures within 6 to 24 months of going live.
• Returns accrued over a long-term period far exceeded initial justification hurdles, with some manufacturers seeing returns in the 6- to 10-times greater range per year.
• Companies that use the visibility that their MES systems provide to make continuous improvements throughout the manufacturing value chain get the greatest ROI, turning the value of product and process information into new revenue opportunities.

Most manufacturers continue to justify their MES investments on operational cost-reduction metrics (such as labor, inventory measures, lead times, maintenance, data accuracy, and reporting), but significant ongoing benefits result from the cumulative effect of near real-time visibility into the production process.

“The fact of the matter is that manufacturing execution systems are an important component of [information technology] infrastructure for any manufacturing organization that has complex execution and traceability requirements,” Smith says.

The more complex the routings are, the more likely MES is to deliver value; and the more complex the traceability requirements are, the more value MES will deliver. And as production operations become increasingly dispersed across a globally distributed network of assets—what AMR calls supply network operations—the more value an MES delivers.

“The vendors with the most flexible, best integrated, broadest reaching analytical capabilities are leading the way here,” Smith adds, citing Apriso, Camstar, Datasweep, and Visiprise as leaders. “They are thinking beyond analytics per se to measuring the performance of globally distributed manufacturing assets. This is where the payback is—understanding how the virtual factory is behaving.”

The AMR survey supports this, showing that the largest benefits of MES come from using the visibility that MES provides to produce continuous process improvement and supply chain management strategies. The endorsement is unequivocal: “At a fraction of the cost and time of an [enterprise resources planning] initiative, an MES platform provides visibility into accurate, high-velocity information about production performance. This enables manufacturers to recognize and then seize opportunities both internally and in the marketplace.”

The Power of Analytics
While one can easily break down MES into components—as an analytical tool or as a control tool that manages the production process—its real power comes as an integrated, single solution that both controls and collects data about what it is controlling, reports Carter Johnson, vice president of strategy and business development at Alpharetta, Georgia-based Visiprise.

“The analytical information created out of that does several important things for manufacturers,” he says. “One, it gives companies the ability to make informed decisions about their processes a lot faster … Two, it provides them the confidence and peace of mind that comes with verifying that product is being manufactured as it was intended to be manufactured.”

For example, two of the analytics that are critical in electronics manufacturing are first-pass yield and second-pass yield. When a new board enters a specific operation, the board can pass or fail. The ratio of failures to passes is used to calculate the yield of the board. Subsequent revisits of the board within the same operation are used to generate the second-pass yield. This opportunity is important in measuring the success of building a quality product.

By collecting MES data from the various servers, along with the reports that the system generates, test engineers quickly can identify problems the testers have indicated. Failures may include such things as component- and solder-related defects, and analytic reports are used to correct the manufacturing process to reduce the occurrence of defects or even to suggest how repairs should be made to failing boards.

“We have the capability to suggest to an operator what the proper course of action is to take on the board,” says Johnson. “For example, it may be cheaper to scrap it than to rework it. The resident knowledge is in the MES analytics, which can make that suggestion to the operator.”

Visiprise’s solution contains a field that highlights the component that has failed, and that can be used to identify the possible repair actions to be performed. This information is displayed to the operator in the form of a Pareto chart, which ranks the most common solutions to failures based on prior successful repairs at the identified process. Combined with online schematics and physical board layouts from computer-aided design data, this greatly improves an operator’s ability to resolve manufacturing defects.

In this instance, on one analytical measure for key performance (for instance, yield), the results of improving that measure can be dramatic. Daimler-Chrysler’s automotive electronics manufacturing facility in Huntsville, Alabama, implemented Visiprise’s MES solution to such effect. In the four-year period after execution, test yields improved by an average of 7 percent throughout the facility. Every single percent increase in overall test yield saves the corporation about $9 million in wasted processing and scrap costs. Overall savings derived from test yields were more than $65 million.

“We view MES as having evolved into a critical component of enterprise software, providing the last mile of a supply chain manufacturing solution,” says John Banks, director of professional services at San Jose, California-based Datasweep.

“MES is not isolated to one area,” adds Carolyn Hughes, marketing manager at Datasweep. “People like to talk about the shop floor when they talk about MES, but its real foundation is providing decision support across the manufacturing environment.”

Banks and Hughes agree that providing effective MES decision support requires a broad application and infrastructure that supports complex reporting requirements, as well as intricate situations customers can deploy across multiple factories or plants on a global basis.

AMR’s Smith notes that today’s manufacturing landscape demands that MES software architecture provides visibility into the shop floor, quality, and other manufacturing components across the entire enterprise. “You have an innovation site, where new product development is done,” she says. “They do the first manufacturing run. Then a company contracts for volume manufacturing. In a scenario like that, the holder of intellectual capital needs to share information with the contract manufacturer. What we’re talking about is having this ability across the extended supply chain—not only how to build a product, but the product’s quality and compliance specifications; and across the range of contract manufacturers, having the ability to gather data back from them, as well. Once you start to have visibility into that process, the amount of time you spend correcting errors and chasing down problems, all the way back to warranty claims, is cut dramatically, simply by automating the exchange of information.”

Banks cites an example of a Datasweep customer with four plants, dispersed globally, with more than 800 operators. Before implementing Datasweep’s MES solution, the company had operators manually enter their hours on timesheets, which would be compiled to derive labor costs. “Obviously this was problematic in terms of time, cost, and accuracy,” he says. “By implementing our solution, they were able to track labor costs per factory, per unit, per line, essentially in real time. The cost savings on this process alone nearly covered the investment cost for the system.”

What’s the Value?
Smith emphasizes that the ROI from analytics has less to do with the technology than what a company chooses to do with it. She says that companies should pose the following types of questions in order to assess the value of MES analytics.

• If I am making an active biologic that I can sell on the market for millions of dollars, then what is the value of an analytic that tells me if my process is going awry while I still have time to fix it and not scrap the product?
• If I am trying to decide whether to spend $4 million on a new piece of milling or stamping equipment because I believe I’m running at capacity, then what is the value of analytics that show me where my inefficiencies are so that I can fix them, reclaim capacity, and defer the capital expenditure?
• If I’m printing newspapers and out-of-round feed stock rolls cause me to repeatedly shut down my press, what is the value of an analytic that can tell me up front whether the stock is suitable for use before I waste setup time, energy, resources, and labor, not to mention potentially missing my delivery schedule?
• If I have to decide which grade of fine chemicals to run through my reactor next month, what is the value of an analytic that can tell me, based on current operating costs and market pricing, which grade will give me the highest margin, whether I’m running at fullest capacity or not?
• If I am in power generation, what resources, based on spot markets, should I use today to meet contractual commitments? And which plants should I run?
• As I compare the performance of my 15 manufacturing sites with an eye to consolidating capacity and increasing margin, which should I keep? Which should I sell or decommission?

Implicit in these questions is the idea that the right information be delivered to the right levels within the organization. “Bottom line: Upper management is much more interested in rolled-up information anyway,” says Smith. “They don’t care about how an individual machine is doing. They care about how I did today against my schedule. To some extent, they’re not even going to care why they performed the way they did, they’re just going to want to know how they did—and if the performance was bad, they want to know that somebody fixed it.”

At each level in the organization, there’s an appropriate amount of information and granularity that need to be present. Considering all that MES systems can do, there is plenty for upper management to contemplate. These features include analytics, rollups, data aggregation, and, in particular, the ability to take financial data from enterprise resources planning and order management systems and correlate it with the appropriate product build information to give financially oriented results and reports. But once an organization has access to all this information, it doesn’t want to flood those at the top with information that is not actionable. Smith is optimistic. “From my perspective, it should be very easy, applying some common sense, for an organization to understand who needs what, where.”

Marty Weil is an independent journalist based in Charlotte, North Carolina. He can be reached via e-mail at marty@weilmarcom.com.