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Inspectioneering Journal

Leading Edge Inspection Data Practices — Acquire It Faster, Manage It Better, and Improve Its Use

By Ed Bryner, Director of Engineering at Gecko Robotics. This article appears in the March/April 2020 issue of Inspectioneering Journal
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Introduction

In the inspection world, data is everything. Every piece of data gathered during an inspection is another clue into the history of the asset. Whether it’s a picture of a defect, an ultrasonic thickness measurement, or a simple timestamp on an inspection wall-chart; each piece of data helps tell the story of the history and condition of the asset.

Because of the investigative nature of inspections, it’s typically more advantageous to gather an excessive amount of data – just in case. We often find ourselves going into detective mode having to analyze every piece of information available for an asset. With photographs, it’s easy to understand why more data is better. Oftentimes, a slightly different angle or different lighting will provide more clarity to the asset’s condition.

The same benefits apply to ultrasonics. Ultrasonics provide readings that show the thickness of an asset. More thickness data equates to higher confidence and accuracy of the asset’s thickness profile. In addition, by overlapping thickness readings and interpolating between adjacent data points, you’re able to create data redundancies that essentially “double-check” the results. This is similar to having two photos at slightly different angles or vantage points. One of those pictures can assist in identifying an anomaly in the other picture.

So, what’s stopping us from getting every bit of data we possibly can on a component during our inspection? What’s stopping us from getting the full picture, without missing a single detail?

Historical Limitations

Historically, hold-ups were caused by physical limitations, such as a lack of data storage space or slow data transfer speeds, among others. In our everyday lives, we have often faced these dilemmas with our own computers and devices.

To overcome these hardware limitations, technology companies continue to refine and improve their products. Data storage continues to evolve and has become increasingly more affordable and compact. Computer hardware and infrastructure has improved, allowing faster and more reliable data and transfer speeds.

These technological advances have minimized the hardware limitations of data. To put the rate of this evolution into perspective, for example, today’s smartphones are millions of times more powerful than all of NASA’s combined computing capabilities in 1969 – when humans first set foot on the moon.[1] With these advances in technology, it was only a matter of time before hardware no longer limited what we could store and maintain.

New Challenges

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