Manufacturers big and small have been faced with unprecedented challenges to keep production running – supply chain disruption, fluctuating demand and workforce scarcity. Some are still trying to ramp production back up to pre-pandemic levels. Through all of this, the motivation to look for ways to innovate has never been greater. In December, The Wall Street Journal predicted that “as we look out to 2021 and beyond, there is more reason for hope in manufacturing than at any time since the 1990s…. Automation and other technologies play a big role here, and advancements are accelerating”. Achieving your desired production or product quality goals through innovation can be challenging, but vision AI is already providing great value to manufacturers of all sizes around the world.
Vision AI powered inspections may be helping some manufacturers meet their quality inspection goals, however, up-front costs can be prohibitive. Therefore, it is important to differentiate between software and “all inclusive” solutions. An “all inclusive” solution might sound great, but when calculating the true cost for a quality control inspection point, the price quickly adds up. Software solutions can be more appealing to manufacturers because they are a more budget friendly route to AI implementation, work well with existing hardware already on the production line, while achieving the same performance as the more expensive all-inclusive solution. A vision AI software solution that has a lower upfront investment and is faster to train does not just pay for itself faster, it can also be applied to a much wider set of use cases; from the raw materials coming in, to the palletizing of products shipping out. Additionally, vision AI software can be deployed quickly without AI expertise, with minimal or no upfront investment results in a shortened ROI timeframe of months rather than years.
Taking the above points into consideration will help manufacturers big and small select the right vision AI software to improve their quality inspection process. Even business cases that could not support a more expensive solution, due to shorter production runs, lower volume, or very low failure rates, are easy to justify when implementing the right vision AI software.
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