Industrial vision systems have been supporting businesses for many years in various applications, like scanning barcodes and OCRs. The technology has enabled businesses to run more efficiently and accurately, and to rely less on human intervention for repetitive or mundane tasks and thereby reducing labour costs.
The system consists of a camera to capture images or videos. The visual data is then analysed using a computer and software to instruct and return the appropriate response. The software could be programmed to identify a particular item, as with barcodes, or it may contain certain height and weight restrictions for items on a conveyor belt as part of a production line or to guide a robot. Consistent environmental conditions are required to ensure data is recorded accurately, such as good lighting.
The use of artificial intelligence has taken this technology to another level by implementing self learning algorithms that move away from the rigid ‘rule-based’ pre-programmed software. Let’s further examine the benefits of AI-controlled Industrial Vision Systems in more detail compared to conventional systems.
Subtle Defect Detection: AI excels in detecting unexpected anomalies, such as small cracks, scratches, or surface discolourations that do not conform to predefined standards. These systems learn by example rather than requiring regular manual reprogramming for new product variants or changes in lighting and texture.
Lower Error Rates: AI-integrated systems can reduce error rates to below 1%, compared to nearly 10% for some non-AI-managed systems.
Faster Processing: Modern AI models can process images in milliseconds, allowing real-time inspection for greater efficiency.
Reduced Costs: By identifying defects early, AI prevents faulty materials from advancing, which reduces waste and material costs. Live video feeds analysed by AI can spot early warning signs of equipment failure, reducing downtime by 30–50%. Automated AI inspection can reduce quality assurance labour costs by approximately 50% and potentially save businesses millions annually. Early adoption of AI-controlled vision systems acts to future-proof businesses and provides a competitive advantage over rivals.
Safer Working Conditions: Manual checks often have risk implications. Automated vision in hazardous environments can reduce unsafe incidents by 40–60% leading to fewer injuries and working days lost while recovering. This also reduces the risk of compensation claims and litigation. AI vision systems can also monitor other processes within your business to trace potential problems before they manifest and cause disruption.
Greater Scalability: AI vision solutions scale easily from small business environments to larger operations because they utilise self-learning algorithms that adjust to different applications with minimal intervention and downtime.
Increased application usage: Greater adaptability, efficiency, and accuracy enable its use for more applications across a wider range of industries.
For example, robots can be guided for increasingly complex tasks at greater speed and accuracy on a car production line. Ford has greatly benefited from the use of its own Mobile Artificial Intelligence Vision System (MAIVS), which it installed globally in its factories to do multiple tasks.
In agriculture, it can monitor the quality and yield of crops. Fruit can be sorted by type, quality or ripeness. It can reject those that don’t meet the quality threshold and remove foreign objects. Automated weed detection is also possible with the use of this technology.
In the pharmaceutical industry, it can be used to inspect drugs, check vials and ensure equipment is sterile before use.
There are many more applications in numerous industries that AI-controlled Vision Systems serve, and they are increasingly being utilised as their full potential is being recognised with its associated benefits.
Artificial Intelligence is still in its infancy, so it’s reasonable to expect these systems to continue to develop and become further integrated not just into industry but also into more aspects of our daily lives.