Machine vision uses the 3D modelling designs generated by design software to allow the system to assemble the product to the exact requirement speedily and at a high quality every time. This process is used by manufacturing giants across the world to be able to manufacture the high demand for their goods. The machine vision model coupled with machine learning helps to monitor the automatic machinery and human workers' interaction, to ensure that the most efficient assembly process is being used. This automated factory scenario can also help to avoid product recall situations, due to the strict assessment criteria put on each product as it moves through the factory.

Large scale manufacturing sites often struggle to achieve 100% accuracy in defect detection in their goods. With a camera and frame grabber based diagnostic system, they can collect the data in real-time and analyse the results required for the expected quality of a product and show where a defect has occurred and remove this item from the system before packaging. This is particularly good when identifying minute defects in a production line where the speed and size make identification far superior to that of the human eye.

Machine vision used in a packing scenario offers the user the ability to get their product packaged to their specification the first time. This may be in the number of items packaged into each product or the orientation of the labelling, through to barcodes and traceability. Machine vision is helping manufacturers to prevent mistakes being made during the packing process and ensuring the consumer has the same high-quality product they expect when they purchase an item.