Intrinsically Intelligent

As components get smarter—and even more autonomous—OEMs have new opportunities to drastically improve machine productivity and flexibility.

Intrinsically Intelligent
Intrinsically Intelligent

Think about the gadgets we carry, the houses we live in and the cars we drive. Our phones have embedded chips and apps that can track our location and give us directions, our homes have sensors and fixtures that can turn on the lights and adjust the thermostat when we walk in, and cars—well, soon, due to all of the built-in intelligence within the machine, they will drive themselves. Things are getting “smarter,” so it only makes sense that the machines that we build and use in manufacturing become more self-aware and digitally savvy, as well. 

Thanks to 50 years of Moore’s Law (the prediction that computing power would increase and cost decrease at an exponential pace), the Internet of Things (IoT) and ubiquitous deterministic networks, the manufacturing industry has reached a tipping point. Specifically, with faster, smaller and cheaper processing units, intelligence is no longer delegated to a central controller, like the PLC, but is being distributed throughout the components and instruments within a machine and a network of systems. 

As a result, technology suppliers are rethinking the way in which processes are controlled on the factory floor. 

“We’ve forced control to be applied on the process…it’s been an add-on or an appendage to the process,” says Don Clark, vice president of global application consulting and Schneider Fellow at Schneider Electric. While addressing attendees at the company’s Foxboro User Group meeting last year, Clark explained a profound new approach to process control. “New technology is going to shift that old paradigm so control will be performed in the process. If you embed autonomous control within the process itself, so that it is no longer ‘stuck on,’ it allows you to think in new ways and to go back to the roots of the fundamental control loop of one.” 

Schneider Electric is working toward creating cyber-physical systems (CPS), in which intelligence, I/O and communication are happening between assets in a low-level mesh network. In this environment, devices and instruments are self-operating and self-optimizing. It’s about putting measurement and control inside sensors, valves, pumps and motors, which are communicating in a localized network—but also operating autonomously. 

The plant floor is evolving into a “system of systems,” that has embedded intelligence everywhere. So, when components and instruments become self-optimizing, manufacturers will be able to approach energy management more effectively, they will be more predictive in maintenance, rather than reactive, and they will be able to meet new customer demands that come in the form of mass customization.

Technologically, we are not to the point where components are intelligently autonomous, but the industry is getting there, as devices can now monitor and report on vibration, electrical current or temperature, and do some self-diagnostics and reporting. Eventually, these smart components will evolve into networks of cyber-physical systems. But, before that can happen, the collective manufacturing mindset must change, and there’s some resistance to change.

 

Price vs. value

ARPAC, a provider of packaging equipment and integration services, understands the value of a “smart machine,” and, to that end, the company is leveraging IoT, cloud computing and production analytics as part of its service, called BeConnected, to remotely collect data and monitor a machine, enabling the OEM to proactively maintain customer equipment. 

This is just one of many “intelligent offerings” the OEM is already providing or exploring, but there are two obstacles that ARPAC and every machine builder must overcome: machine design and customer interest. 

You can add in sensors and intelligent components, “but the hardware is only a quarter of the cost. It takes more time to design, program and test,” says Brian Ormanic, lead engineer at ARPAC, “We have about 100 different machine models and customizations, so it’s hard to find the time. And, you have to have customers care about it, and willing to pay for it. Customers are always pushing us for the lowest machine price, but they should understand the value of information.”

ARPAC uses Rockwell Automation technology as part of BeConnected, and Rockwell understands its role in educating the manufacturing masses. “We have been working hard to help manufacturers understand the potential value so that they can have conversations with the OEMs,” says Steve Mulder, Rockwell’s North America packaging segment lead. “It’s critical to have the conversation with the end users’ operations side so they understand how impactful it will be to production and the bottom line to utilize intelligent components and smart machines.” 

John Kowal, director of business development at B&R Industrial Automation agrees that the manufacturing end users are not always aware of the huge value-add of built-in intelligence in servo motors, drive systems, gearboxes, etc. But neither are all machine builders.

“We have an I/O slice with intelligence onboard that is cost effective because Moore’s Law has made field-programmable gate arrays very affordable,” Kowal says. “It’s processing the input and output that it is controlling directly in the slice...so it doesn’t have to go back to the PLC CPU to process, and it can respond within microseconds.”

The approach, used in packaging, allows extremely time-critical subprocesses to be managed using standard hardware, all programmed within the IEC 61131 environment, while cutting costs by reducing the load on the controller and optimizing performance to match high-end packaging machine demands. Nevertheless, not all OEMs understand the value at first. “I asked a flow wrapper builder, what if we could detect an empty wrap in a matter of microseconds, would that have value to you? He said, ‘yes,’” Kowal remembers, noting that the value to the OEM is the ability to shrink the footprint of the machine by responding faster and more precisely, and requiring less distance between detection and rejection stations. 

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