In the wake of the COVID-19 pandemic, product development and manufacturing companies faced disruption across their supply chains and factory floors. In a bid to recover, many are using AI to refine their processes, speed up delivery times, and reduce human error.

Those that increase their adoption of transformative AI technologies are better able to navigate challenges — such as supply chain shortages — and demonstrate business value. One such technology leading the way is computer vision.

As its name suggests, computer vision interprets, recognizes, and reconstructs visual stimuli. It aims to replicate the mechanics of the human eye with greater accuracy and speed.

But how does it work? And can it be of use to your business?

How does computer vision work?

Computer vision uses algorithms and deep learning systems to recognize, process, and analyze visual inputs. The more data fed into these systems, the more sophisticated they become.

To put this into context, consider traffic monitoring — a use case that we’re all familiar with. Many traffic cameras capture and label visual stimuli, such as cars, bicycles and pedestrians, to better understand movement patterns, identify and report problematic driving, and ensure roads remain safe.

But computer vision use cases can stretch far beyond this, particularly in the product development and manufacturing space.

4 use cases for computer vision

It’s important to note that, like most AI systems, computer vision works in conjunction with humans. On busy factory floors, where parts move continuously and machinery must undergo rigorous checks, computer vision can help workers better prioritize their time and focus on more valuable tasks.

Let’s see how this can play out with some specific use cases.

1. Automated assembly

Computer vision can recognize and label product parts better than the human eye. When you couple this with advanced processing power, these AI systems can then enable factory machinery to assemble products with greater speed, consistency, and precision.

This reduces human error and results in higher-quality products with a quicker time to market.

2. Quality assurance

On the subject of quality, computer vision systems can also detect anomalies in the manufacturing process that the human eye might miss.

For example, they can record and monitor the average time for each stage in the assembly process. If one stage takes longer than anticipated, the AI will search for defects in product quality through pattern detection. From there, the system can automatically alert a human supervisor to investigate any signs of a problem.

3. Maintenance checks and alerts

Beyond product assembly, computer vision systems can also continually monitor production machinery to identify early signs of degradation, such as part corrosion or leakages. Upon detecting these signs, the systems can schedule maintenance checks with factory technicians.

This not only increases the safety of factory floors but reduces the need for continuous human checks. That way, technicians need only spend their time on more complex tasks, such as fixing problems or provisioning new parts.

4. Health and safety

Many factories deal with a multitude of health and safety risks, such as corrosive materials and heavy machinery. Naturally, these environments require stringent health and safety protocols — though it can be difficult to enforce these, particularly if your organization employs hundreds of workers.

Computer vision can help to make your environment safer for your employees. Similar to traffic cameras, video devices can monitor employee habits, detect any problems, and trigger follow-up actions. For instance, imagine a worker who has forgotten to wear a safety mask. A computer vision system will pick this up via a camera and route the issue to a supervisor, who can then escalate it.

Is computer vision right for you?

“Successfully scaling 4IR technology makes supply chains more efficient and working hours more productive, reduces factory waste, and has countless other benefits for employees, stakeholders, and consumers.” — McKinsey

We’re well into the fourth industrial revolution — also known as Industry 4.0 or 4IR. This entails a digital-driven change to the way we live, work, and interact with our environment. One key cornerstone of this new revolution is artificial intelligence and advanced analytics, such as computer vision.

Many organizations are already taking advantage of this technology, with the market set to expand by a compound annual growth rate of seven percent until 2030. And it’s no surprise. Computer vision has the power to boost efficiency, aid human-led processes, and shorten time to market.

That said, as an AI ecosystem in its early stages, it’s naturally a difficult area to break into. It also requires a varied set of skills to implement properly and securely, which is proving difficult to find in today’s competitive talent landscape. So, if you’re interested in embedding AI into your digital transformation initiatives but need some assistance, reach out to our team for support.