How manufacturers make the most of machine data

Digitizing the manufacturing process via ERP systems can greatly improve ROI. However, it doesn’t come without challenges.

collage with gears machine data

For many manufacturers, there is a disconnect between what goes on in their factories, including their engineering departments, and the core business processes supported by their ERP systems. It creates significant lag times for management to access, analyze and act on data from the manufacturing and development processes. Not having this data in real time could create problems with planning, inventory control, the supply chain or meeting customer expectations.

Barriers to incorporating data from machines on the shop floor into ERP are dropping. Much of the newer equipment is now internet-enabled, and some older machines can be adapted for connectivity. Companies like GE and Siemens are working to standardize platforms for machine-to machine communication. The leading ERP vendors have all taken advantage of this new connectivity to incorporate the machine data into relevant workflows.

So why aren’t all manufacturers connecting their shop floors to their ERP systems? The same old reasons for avoiding any significant technology project: cost, resistance to change and lack of understanding of the ROI.

[ Related: 8 ways to get the most out of your ERP system ]

Complexity can be a factor, too. Mike Lackey, global vice president of solutions management for SAP, gives the example of a company that has dozens of machines from multiple vendors. “The true value [of digital transformation] is tying all the machines together to see what they are producing, the cost structure, performance, and the quality of the output,” he says. “You can’t look at the data off the machines in silos.”

Industrial digitization and its impact

“Industrial digitization concerns two dimensions or core processes,” says Magnus Wilkerson, professor of production systems at Matardalen University in Sweden. “First, the order-to-delivery process, or operational process, integrates data across system layers and throughout the value chain. Critical activities are the integration of MOM/MES (manufacturing operations system/manufacturing execution system) layer into the architecture as well as the supply chain data integration. Second, the industrial digitization concerns the product and production development process. It integrates data across development platforms and stakeholders and enable virtual builds of new products and virtual verification of new processes.”

Those stakeholders might be people internal to the organization such as product managers, engineers or planners. They could also be external such as contract manufacturers, suppliers, or partners. Lackey spoke of an SAP customer, a large medical device manufacturer, that was designing and building a large and highly specialized piece of equipment used in cancer treatment. Because the manufacturing and engineering processes were digitized and connected, what SAP calls a component of Industry 4.0, all the stakeholders from the customer to the people designing and building the unit were on the same page.

The stakes were high. “Their client [a hospital] had spent more than $1 million setting a room up for this equipment,” says Lackey. “With S/4 HANA, bottlenecks and shortages were identified sooner allowing the manufacturer to respond faster managing customer expectations and insuring an on-time delivery.”

The tools to measure ROI are available. Robert Sinfield, director of portfolio marketing at ERP vendor Epicor Software, gives the example of rubber and plastics manufacturing. “It’s very repetitive manufacturing, and manufacturers want to maximize efficiency,” he says. “Solutions to measure efficiency give visibility into the manufacturing process. They can detect deviations in small volumes of time that normally you would not be able to identify.”

For example, the system might identify a machine running at 3 percent lower efficiency over the past three days and send an alert to the service department. That drop might not have been noticed if the machine were not connected to the internet with a monitoring solution that was integrated with the manufacturer’s ERP system. This is important, because even a tiny increase in efficiency in a high-volume manufacturing process can yield significant returns.

Scrappage, or material wasted due to quality issues in the manufacturing process, is another area where intelligence at the machine level can improve efficiency. Sinfield says one Epicor customer cut its scrap average from around 4 percent to 1.37 percent, which also contributed to a 3.1 percent decrease in downtime and consequently lower cost of sales. Annual cost savings for this company were $600,000. “This puts the ROI down to months,” says Sinfield.

The benefits don’t stop there, however. “Where it gets clever, [the efficiency data] is presented to finance so that they can understand energy consumption and make judgments about overall equipment effectiveness (OEE) measures. Looking at downtime, they can see if it makes sense to continue servicing the existing equipment or purchase a new machine,” says Sinfield.

Connecting people as well as data

Getting a steady flow of actionable data from the shop floor to business managers and back is important, but just having access to that data might not always be enough. That’s why Epicor has embedded a social framework to support teams associated with a project or process. “Social is built into the fabric of Epicor. It supports a fundamental shift to allow interaction both internally and externally,” says Sinfield. “It’s not just about collecting and analyzing information. It’s really about letting a team collaborate around a project.”

1 2 Page 1
Page 1 of 2
Download CIO's Roadmap Report: 5G in the Enterprise