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Systems Integrators Deliver the Smart Factory

IoT projects, AI, smart factory

Plant managers are on a mission to improve overall equipment effectiveness and optimize their lean manufacturing approach. Unplanned downtime and product quality are their key concerns, which requires knowing that the machines on the factory floor are running well. If not they face the consequences of reduced productivity and quality, with increased wastage and costs.

Leveraging the power of innovative technologies allows for greater understanding of critical equipment health—eliminating unwelcome surprises. This requires the ability to collect and make sense of the right data at the right time. Predicting and planning for downtime on an identified-needs basis, and not just a calendar, reduces these surprises—the holy grail of smooth operations management.

AI, computer vision, and real-time analytics are making this a possibility, enabling the digital transformation that companies need to be more agile in an ever-growing competitive environment.

Not only do these technologies and solutions create new opportunities for manufacturers, they do so for the system integrators (SIs) that they have come to rely on. But do traditional SIs skilled in daily manufacturing operations have the IoT experience required to deploy these advanced edge-to-cloud IoT platforms?

By working with IoT solutions integrators—which can help source, deploy, and manage advanced edge-to-cloud systems—the answer is a resounding yes.

Partnerships Streamline IoT Projects

One company that’s guiding IoT innovations for its customers is the integrator Arrow Electronics, Inc., a technology provider with a portfolio that spans a broad range of IoT and other solutions. “We’re bringing all the right parts and pieces together, and the skills and expertise from our partners to make something great,” says Andy Smith, director of OT Alliances, EMEA, at Arrow.

For example, with partners like ADLINK, a manufacturing solutions provider, and SAS, a leader in data analytics, Arrow helps SIs bring the latest technology solutions to their customers in the simplest way possible. And Arrow can provide holistic smart factory solutions instead of working under a break-fix, fee-for-service model that can be expensive and inefficient.

“Imagine knowing how many hours a machine could run before requiring maintenance,“ says Smith. “That kind of knowledge allows customers to plan accordingly and ensure backups are ready to keep production humming. Now extend that level of insight to all machines across the entire operation. The impact on productivity and savings is remarkable.”

This kind of predictive maintenance is an obtainable goal with a scalable, end-to-end platform like the ADLINK Edge MCM Quick Start.This advanced solution delivered by Arrow is a prime example of what’s possible when an ecosystem of partners joins together to solve common manufacturing problems (Video 1).

Video 1. AI-enabled predictive maintenance cuts manufacturing costs and increases machine uptime. (Source: ADLINK)

This advanced solution, delivered by Arrow is a prime example of what’s possible when an ecosystem of partners joins together to solve common manufacturing problems.

AI Goes a Long Way

The ADLINK system was designed as a turnkey solution to monitor the health of tooling on CNC machines via vibration detection. And because thousands of consumable parts break and wear down in a factory environment, the same technology can be applied across the whole shop floor.

The solutions edge software ingredients include data aggregation, normalization, alerting, and device management. And SAS Event Stream Processing provides advanced analytics and automated decision-making. This end-to-end combination allows SIs and their customers to build a health score for all those consumable parts, not just CNC tools.

“So this product is just the tip of the spear for leveraging digital transformation to monitor asset and equipment health at scale on the factory floor,” says Daniel Collins, Senior Director of Edge Solutions for ADLINK.

And while using vibration detection to predict failure of CNC machine parts isn’t new, ADLINK’s edge-to-cloud strategy makes its solution unique. “We don’t believe that every piece of data needs to go to the cloud for it to become valuable; that can get expensive fast,” explains Collins.

That’s why data aggregation, normalization, and analytics run at the edge on an Intel® processor-based gateway. And it becomes more powerful when data is sent strategically to and from the cloud—useful for measuring trends across an entire fleet of machines over time.

Even more important, manufacturers don’t need a data scientist to run it. “This solution was built for the operations and plant managers—with a simple GUI that’s easy to use and leverage,” adds Collins.

Smart Factory Savings

One small parts manufacturer was changing cutting tools almost daily to prevent failures and plan for downtime. As a result, these tools were being replaced far ahead of their true failure point—a waste of human and financial resources.

Moreover, because people were an integral part of stopping and starting the machines, errors were inevitable. It wasn’t always obvious when a machine was running the wrong job until it finished, resulting in lost time, scrapped parts, and ruined tooltips.

With Arrow’s help, the company deployed the ADLINK system, which provided the visibility necessary for more accurate asset life cycle analysis based on the machine running each job. Because the solution ties a health score to a likely failure, the manufacturer can now predict with much greater precision when tools need replacing. The results are lower costs and increased uptime.

With the combined expertise of a solutions integrator such as Arrow, an ecosystem of partners, and powerful edge computing, systems integrators can better help their customers benefit from similar results—and generate new revenue streams in the process.

About the Author

Erica Stevens has written about technology and finance for magazines and directly for clients since 2005. Before that, she earned a master’s degree in cognitive psychology from the University of Toronto—where she first learned to translate complex, technical topics into engaging prose. Since then, she's done the same for global brands like Intel, Vanguard, Discover Financial Services, Bank of America Merrill Lynch, and more.

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