Brad Kuvin Brad Kuvin
Editorial Director

IIoT for the Fab Shop: Connect , Measure, Analyze and Improve

November 5, 2020

Metal formers and fabricators continue to seek tools to help solve production pains, an exercise that increasingly leads them to discovering the benefits of software solutions―many anchored in the Industrial Internet of Things (IIoT). Such software products can remove the blind spots that prevent managers from gaining a clear and accurate picture of shop performance. Using IIoT software, managers can collect and analyze production data, and when that information flows directly into a facility’s ERP/MRP system, they can take swift and decisive action to improve productivity and profitability.

Nested Sheet 4K“ERP integration is key,” says Amada America software product manager John Parenzan. “Fabricators regularly ask during product demonstrations about the ability to integrate directly with ERP systems when nesting and also to move data collected from their turret presses, laser cutting machines and other equipment directly into their ERP systems for quick and timely access and analysis.”  

While this capability also can enhance other shop operations,―turret press punching, for example—it’s particularly suited to helping improve the performance of laser cutting machines.

“With a turret press,” Parenzan explains, “fabricators typically focus on tool restrictions and part orientation, but with a laser there’s more flexibility in how jobs are nested and completed. The bi-directional flow of data from the machine on the shop floor to the ERP system and then back to the machine control can allow fabricators to adjust their programs and optimize workflow.”

Estimates vs. Actual Production a Common Blind Spot

“One thing we’ve noticed,” adds Casey Greer, Amada’s lead IIOT professional service consultant, “is that very few shops report actual part-nest run times to their ERP software. So, the issue isn’t just integrating the laser cutting software to the ERP system, it’s deciding what data to send. And now that the newest software tools on the market (including Amada’s Influent software) can send actual run times to the ERP, shops can compare run-time estimates to actual production—per part on a nest, or for the entire nest.  This has been a blind spot for a lot of fabricators, and we’re starting to see that blind spot disappear.”

The trick to IIoT, however, is not so much how to gather the data, but what data to capture and then how to use the data. With the software alluded to by Greer and Parenzan, shop managers can compare sheet-nest run times―by operator and shift―look for inconsistencies and address any root causes. Mangers also can obtain accurate processing times and, with the sheet nests integrated into the process, calculate with some level of precision how much each part within a nest is costing them to cut.

Machine Dashboard“Many shops will time the first run of a part or part nest in order to calculate part costs, but operator inconsistency over time and over numerous production runs often will result in a range of run times that differ by operator and shift,” explains Greer. “Operator skill is a factor, and in many cases the same machine will run at different speeds during different shifts. Our customers now want more accuracy and accountability, and the ability to consistently gather run times per part and nest can dramatically improve job-quote accuracy.”

OEE the Tip of the Iceberg

“While the industry has been able to monitor machines remotely for some time, since 2005 or so,” says Greer, “now we’re able to capture meaningful productivity-related data such as green-light uptime, downtime and downtime codes, alarm history, and how long alarms were in place. And, not only can we capture data from our own machines, but we also can capture data from other machines in the shop—and normalize that data to make it easy to compare and contrast the performance for different machines.”

Greer emphasizes that data collection and analysis goes much deeper than the typical—and important—discussion of overall equipment effectiveness (OEE).  

“With OEE,” he says, “you can evaluate three metrics: quality, performance and machine availability. When a manager identifies an underperforming machine, he begins his diagnosis by asking two questions: What parts is the machine running, and who was running it?”

The data-collection and analysis process to address those questions must start as quickly as possible after identifying the issue.

“What these new integrated software platforms offer,” Greer continues, “is the ability to collect the relevant data from the machines in real time and send it straight to the ERP system, giving managers instantaneous insight so that they can immediately see which operators ran which jobs. The software oversees all labor transactions on the plant floor—we know what every employee worked on and can provide the data at the fingertips of the managers.”

“So, while OEE suits a purpose,” says Greer, “by identifying which machines are performing well and which ones are not—and trust me, most managers think that their machines are running much more efficiently than they actually are—software that integrates machine-performance data directly to ERP systems paints the accurate throughput data needed to optimize shop management.”

Look Ahead, Not Behind

“ERP systems on their own are looking at data from yesterday, or from last week,” says Greer. “What fabricators want from IIoT is the ability to address what is happening right now on the plant floor. If a machine is underperforming now, today, they want to be able to address it immediately. With state-of-the-art software, they can set production goals for each machine, monitor performance and send alerts to the plant manager, a shift foreman or even a maintenance manager to trigger immediate action.”

Greer and Parenzan note that the industry addressed productivity issues with press brakes several years ago, at a time when it didn’t appear that press brakes could run any faster and still be safe for the operator. That led to the development of tools to quicken programming and machine setup, such as simulation software and automatic tool changers. “Now we’re trying to do the same with laser cutting machines,” says Parenzan.

Specific to laser cutting machines, data available from the machines include material utilization from the part nests, which the software can compare to preset requirements and send alerts when nests underperform. And, concerning the laser-programming software itself, newer software products  now have integrated press brake forming simulation and programming, rather than requiring use of separate bending software.

“Programmers now can bring in their part CAD models,” explains Parenzan, “simulate the bending operation to generate an accurately dimensioned flat part, and then send the part profile directly to the blanking software. They then can develop the nests and the cutting program, and simulate any laser cutting machine-automation activity, including part sorting.

“In the end,” he summarizes, “the fabricator is verifying manufacturability in a virtual environment, and very accurately calculating run times as well. This approach eliminates any errors in flat-blank development caused by using the wrong bend-reduction calculation.” MF

Industry-Related Terms: Bar Coding, Bending, Blanking, CAD, Forming, Gas Metal Arc Welding GMAW, LASER, Manufacturability, Material Utilization, Nesting, Run, Turret
View Glossary of Metalforming Terms


See also: Amada North America, Inc

Technologies: Management


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