Digital twin solutions are emerging throughout smart factories everywhere. Virtual replicas of factory floors provide real-time information about processes, system health, performance and more. But why not apply digital twin methodology in other manufacturing stages, such as quality control?

As manufacturers worldwide seek to enhance their machines and equipment with online connectivity—an example of the Industrial Internet of Things (IIoT)—they are realizing this technology’s remarkable potential. I

Netilion Health visualizes the diagnostic data provided by an instrument and receives instructions to address the issue. This improves the ability to respond in cases where maintenance or service is required.

The cornerstone of every manufacturer’s success is the ability to shift gears from one product generation and business model to the next while finding new ways to excel at quality.

Data collection on the factory floor can be a challenge. Even the smallest enterprise can generate massive amounts of data, and collecting this data is only a first step on the path to a successful IIoT project.

ATS Automation Tooling Systems Inc. unveiled Illuminate™ Manufacturing Intelligence, a next-generation factory optimization Industrial Internet of Things (IIoT) platform solution.

Easy ain’t easy. Sounds like something said by cultural catchphrase artist and legendary baseball player Yogi Berra, but it sums up a conversation I had at a recent tradeshow in Atlanta.

If you talk to anyone in manufacturing today about the future of the industry, you’re likely to hear a quizzical, “Do you mean Industry 4.0?”

Machine vision sensors in today’s factory produce massive amounts of data. Edge computing through acceleration is a smart solution to handling these large datasets.

Manufacturers typically use two different techniques to assess part conformance and process control: either in-process gaging or final inspection. In-process gaging is measuring the part while it is still in the process of being manufactured and using that data to, sometimes, adjust the process, other times for part conformance.