Time to jingle the bells with an impact testing copilot!
A test engineer’s Christmas
The most wonderful time of the year is just around the corner! As Christmas tones and music echo through the streets and markets, let’s use our creativity to jingle some bells with an impact hammer, and leveraging the power of Simcenter Testlab Neo to create a harmonious and impactful combination.
Alright, time to crack this nut to see what’s inside and understand why the impact testing copilot selected similar notes (E’s) but rejected different ones (G,C,D). For now, think of the copilot as an ‘assistant’; let’s focus first on what it does rather than who it is.
The challenges with impact testing
To conduct impact testing, test engineers are required to hit an exact pre-defined point on an object with an impact hammer and then measure the output at a different point on the object. Even if respected test engineers believe they are one-of-a-kind heroes who can hit that exact point perfectly, they will still need to hit consistently the same point multiple times and average the results.
But that’s when things can go south, since not all hits can combine to produce a reliable average. For instance, hits that are too hard, too soft, or mistakenly involve a double impact can make the overall average less reliable and ultimately cause more harm than good. Even if these issues are avoided, the hits may still fail to land close enough to that target point on the object and should therefore be rejected.
To evaluate the quality of each hit, the respected test engineer may invite a peer to join the test session and oversee the process from the PC. As the test engineer hits, the peer checks and manually decides whether the hit should be included in the average. However, this is a slow, error-prone and often non-repeatable process – not to mention it consumes two valuable resources simultaneously.
How an impact testing copilot can help
A smarter solution is to let the impact testing copilot in Simcenter Testlab Neo assist the test engineer by performing automatic impact selection. The copilot thoroughly evaluates each hit (in real-time) and decides whether to qualify it for final averaging. In the first stage, it pre-screens and rejects hits that exhibit overload, double impacts, or fall outside the peak force range. In the second stage, a procedure called smart hit selection uses artificial intelligence (AI) to assess the similarity or coherence between all available hits, determining those with the higher consistency. Only the hits that pass both stages will be included in the final averaging, guaranteeing a reliable average. This leads to the similar notes (E) selected, and different ones (G,C,D) are rejected.
Test faster, smarter and more accurately
As such, the copilot allows the test engineer to perform the impact test faster, smarter, and more accurately—without the need to involve another peer to complete the task.
While you might think that the impact testing copilot operates solely based on a hard-coded mindset, in fact the test engineers will always remain the pilot-in-command of the impact testing session, meaning they can adjust the selection criteria in Simcenter Testlab Neo at any time during the test or afterwards, and can even veto the selection.
To wrap things up, we’ll give copilot the detailed introduction it deserves: copilot is an advanced “engineering assistant” integrated in Simcenter Testlab to enhance productivity and make the test workflows faster, smarter and more accurate. It delivers Engineering Intelligence that effectively leverages the combination of traditional data analysis methods with artificial intelligence (AI), acting as a companion to test engineers and assisting them with making smart decisions and achieving their best results.
Stay tuned for more updates on how our copilot will further improve your modal testing and analysis workflows in Simcenter Testlab Neo.
Meanwhile, happy Holidays! May your season be filled with lots of harmonious tones!
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