How will AI ensure you don’t get a dented can of baked beans? Or that you don’t get green crisps in your packet of cheese & onion? In this video Andrew and Danny chat about quality control in manufacturing and how AI is improving this all the time.
In a nutshell:
We talk about some of the ways that AI is being used for quality control in manufacturing:
- Control of raw materials: Quality is like links in a chain. Make sure that any defective raw materials are prevented from entering your processes by scanning them on the way in. We use an example of picking out green potatoes on a production line for this.
- Catch defective product at the end of a production stage: Use photo and video as forms of automated non-destructive testing to assess products based on their appearance. We talk abut two great examples here: dents in cans of baked beans and using penetrating dye to check for cracks in castings.
- Check your processes in real time: You can monitor the sound of your machines operating to know whether they are working within bounds, and even use this to feed back into your control systems. An example here is a microphone listing to robotic soldering on a circuit board can alert you to quality issues.
These are just a few of the possibilities for improving manufacturing quality, we’d love t hear about some of your examples!
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AI and Machine Learning Strategy
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How will AI ensure you don’t get a dented can of baked beans? Or that you don’t get green crisps in your packet of cheese
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