It sounds futuristic, but you can’t imagine the number of use cases applied to this technology.
In this blog I will address three of them: safety, warehouse management and quality inspection.
By: Jair Pérez, CEO of Gesta Labs, Industry 4.0 innovation study
Computer Vision (CV) is one of the most exciting and defining technologies today. It is very popular. To give you an idea, just type “Computer Vision Covid 19” in the Google search engine and you will have about 734,000,000 results.
It plays a crucial role in the pandemic that we are facing today. Perhaps is the technology that is gaining the most confidence from companies as the solution that supports the return to activities safely, for example, to measure the social distancing of workers without the need for physical contact and prevent accumulations of people, as a preventive measure to avoid coronavirus outbreaks. And this is exciting because there’s a lot of research at stake, in which entrepreneurs and companies try to develop the most disruptive use case.
According to Markets and Markets, CV will reach a value of 25.3 billion dollars by 2025, with an annual growth rate of 47.5%, thanks to its adoption in industries such as healthcare, security, robotics, sports, mobility and , of course, the automotive value chain, a segment where, in addition, this technology will have the highest growth rate (56.3%) and will reach 2.6 billion dollars in market value.
For this reason I will address 3 use cases that automotive and auto parts companies can adopt to solve, on the one hand, some of the problems that have historically been a headache for them and, on the other, the new complications that have arisen in the context of this pandemic.
Not sure how to build a use case for yourself? With our Discovery workshop, which is completely free, we help you focus Computer Vision on a practical and profitable solution.
Case 1. Personal safety measures and social distancing
Covid-19 created the need to enable safe environments in those areas of companies that cannot operate remotely, such as some operations on the production floor.
Since the start of the pandemic, about 20% of plants have registered absenteeism as a result of panic among employees. A useful solution is the installation of checkpoints with Computer Vision models to assess that employees entering the factory are wearing face masks, masks, gloves and other protective equipment, and to send alerts on those who are not using them properly. Not only this, the solution can be combined with another vision model focused on measuring the distance between people, marking a perimeter around each person and sending alerts when 2 or more people are violating the healthy distance. In this way, the Human Capital and plant surveillance teams can be receiving alerts and monitoring the plant to avoid coronavirus outbreaks among its operators.
Case 2. Warehouse Management
In the supply chain segment, one of the areas where this technology is having great utility is in inventory management, from the counting of parts and items in a warehouse to the automatic issuance of replenishment orders. CV has many applications in this regard, from integrating models into cameras that monitor inventory levels in real time and automatically send replenishment orders, to artificial intelligence models integrated into mobile phone apps that allow inventory counts to be made by taking photos that tell the operator the number of pieces. The benefits are countless: reduction of execution times, reduction of the number of personnel assigned to the count, or elimination of the same, improvement in the precision of the count, reduction of stockouts, among others.
Case 3. Quality inspection
Estimates vary, but the cost of quality can represent between 15 and 20% of the income of industrial companies (source: ASQ), making it one of the most critical aspects of their operation. There is a use case that exemplifies what can be done by applying this technology in quality inspection processes. At its Regensburg, Germany plant, BMW developed a pilot to inspect a very specific process on its assembly line: the sealing of a screw that goes inside the headlights. The model is capable of detecting if the process was done correctly and alerting when there are anomalies. It’s such a critical process that if you get it wrong, the firm could violate some safety rules on the cars it sells. So it will undoubtedly save you several headaches and several thousand dollars and rework for operating personnel.
As you can see, it is a technology whose adoption is starting to manifest.
What can you do to start adopting this technology? The first thing is to define the business case and get to work.
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