Getting the measure of big data

Hyperscan1
Hyperscan1

INSPHERE’s chief technical officer, Oliver Martin reveals how automated, non-contact measurement systems can deliver the Big Data required to realise the full potential of Industry 4.0.

Safety critical applications - such as those found in aerospace - demand high levels of confidence in part and assembly manufacture. Manufacturing confidence can be achieved through good quality inspection data. Collecting and analysing this data can lead to a greater understanding of the manufacturing system and provide insights into sources of variation.

Conventional hand-tool oriented inspection methods are time-consuming and labour-intensive operations with potential to mis-record the results. On the other hand, automated metrology solutions traditionally utilise co-ordinate measuring machines (CMMs). CMMs are commonly gantry-based with three to five axes and a tactile touch-trigger probe. They tend to be somewhat inflexible, monolithic installations. Recent developments have made CMMs more appealing by increasing the relative speeds and introducing non-contact scanning heads. However, the CMM still falls short in certain applications.

CMMs are often an impractical solution when the inspection of large components (5m+) needs to be quick, in-line and non-contact. HYPERSCAN is a new system created by INSPHERE that offers a standard cell configuration for large volume, accurate, non-contact and data-rich measurement. It is a system that uses industrial robots for measurement sensor positioning and an external metrology system to provide global accuracy. This has the advantage of being able to scale at a relativity low cost to large volumes of around 30m, as the positioning system – robotics and linear rails - does not require inherent accuracy over such distances. This particular technology is naturally well-suited to large aerospace components such as those found in wing manufacture.

Non-contact measurement systems provide information-rich datasets, not only enabling features to be evaluated, but also providing good diagnostic information to help understand manufacturing trends, deformations and surface details.

A close-up of the laser scanning sensor collecting 3D point cloud data

All shapes and sizes

Aerospace components are particularly challenging to measure with non-contact systems; components may be freshly machined aluminium (very shiny) or may be carbon fibre (both absorptive and reflective), and these can be at the limit of capability for non-contact sensors, particularly when inspecting against tight aerospace tolerances. The traditional alternative – the CMM – with its tactile technology – is very slow in comparison and cannot achieve the same throughput, however the achievable accuracy is a known quantity.

For any new or disruptive inspection system, robust capability assessment is essential, and INSPHERE have conducted extensive research to ensure the HYPERSCAN system can measure the required features with an acceptable tolerance consumption.

By using high quality linear rails and robotics, the laser line scanner is very repeatably positioned and follows the same paths each time. This in turn makes the measurement much more robust and repeatable; subsequently these paths can be optimised for the feature including material reflectivity. Often a feature that is difficult to scan using a handheld laser scanner, will be inspected far more successfully when the scan pass and scan settings have been optimised – which of course can only be achieved with a robotic system.

Generating Big Data

A recurring theme of Industry 4.0 is the intelligent use of ‘Big Data’. This is often discussed in theoretical terms, without much consideration of what this data is or how it can be collected. Consistent measurement of parts and assemblies is an important step in generating such datasets. If a process is not measured, then informed process change cannot take place. Without taking steps to collect high-integrity datasets on manufacturing outcomes, the promised manufacturing insights that sit at the heart of i4.0 cannot be realised. HYPERSCAN is an integral component to gathering Big Data that will drive highly-automated, stable manufacturing processes.

Robotic positioners hold the potential for other sensor heads to be deployed, and this allows the HYPERSCAN to use the most appropriate metrology for the feature type; this could be a laser line scanner, fringe projection, through-thickness sensor, etc. Furthermore, multiplatform cells such as HYPERSCAN can include integrated measurement guidance systems for wireless hand tool operations, where automated metrology solutions currently fall-short of the manufacturing requirements. Such an approach allows the advantages of automation to be realised, while still maintaining safe integration with more manual approaches where required. This holistic measurement approach ensures that consistent, high integrity datasets are generated.

www.insphereltd.com

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