What is Defect Detection with Computer Vision?

What is defect detection with computer vision ? To answer that question I will continue with the same methodology as our other blogs. To understand this concept, we must divide the terms and understand them individually, then after looking at the bigger Picture. So, what is computer vision?

Computer vision is an area of artificial intelligence known as computer vision that enables computers and systems to extract useful information from digital photos, videos, and other visual inputs and to conduct actions or offer suggestions in response to that information. Now let's explain the defect detection process. As the name evokes, defect detection is a process of detecting the flows of the manufactured final product. Defect detection was a labor-intensive, manual operation before computer vision became widely used. This led to a number of issues, including the possibility of human mistake and the inability for employees to be available around-the-clock. The task of defect detection in computer vision aims to identify probable flaws, mistakes, anomalies, and problems with equipment or products.

The Costs of Defects and Anomalies for Businesses 

The word ‘Defect’ might sound non-fatal sometimes, however let's deep dive into that topic and see what statistics have to say. We should define defect cost first, the value of resource consumption for rework as a result of a defect is defined as the defect cost. To fix the flaw, labor, supplies, and equipment must be used. A fault results in waiting time being lost. Whoever pays is not a factor in determining the price. One of the greatest risks firms face today is risk related to products. In addition to seriously endangering the public's safety, defective products can seriously harm the reputation and bottom line of the companies involved. According to AGCS, accidents involving defective products have resulted in insured losses above 2 billion dollars over the previous five years, making them the main source of liability losses.

Losses from product recalls are a significant factor. Although the frequency of recalls can vary from year to year and by industrial sector, activity has been steadily increasing over time. Recall exposures are rising significantly due to a number of factors, including an increased focus on safety and regulation by authorities, the emergence of intricate global supply chains, the knock-on effects of the current economic climate, growing consumer awareness, and the growing influence of social media. A growing threat also comes from malicious product tampering and even extortion situations.

Benefits of Defect Detection

We went through what defects mean for businesses and what can be the costs for them. So let's continue with the benefits of defect detection. As mentioned above with quite strict product quality measurements and with the amazing influence and spreading power of social media, the customers are way more alert and cautious with their purchased products. Even small defects that might have missed due to human flaws, can cause billions of dollars to huge businesses and with the same amount of scale hundreds of thousands dollars for the small businesses, the loss of reputation is even worse that it consolidates the fact of customers will going to stop being customers due to thinking of if something happened once, it can happen again.

Defect detection is sitting at a corner where the own costs of using those Technologies are basically a solid insurance of the damage that could be done.  Manufacturers, as well as businesses, gain greatly from computer vision. On the one hand, it expedites defect identification, decreases prices, shortens wait times, and uses up less waste. On the other hand, it clearly improves the workflow and increases model correctness, employee happiness, and defect detection accuracy. If we had to summarize, the benefit is twofold: it increases the profitability of your production processes while also making the detecting work easier and, as a result, increasing staff satisfaction.

Why Do Businesses Need Defect Detection?

Businesses need defect detection for several reasons, utilizing computer vision for defect detection enhances manufacturing operations and reduces costs. It reduces the manufacturer's expenses via quicker and earlier detection of defects. Additionally, it raises staff productivity and lowers scrap. The following things can be avoided by improving defect detection accuracy and decreasing defect-related expenses like recalls; reputational damage; decreasing sales; product scraps; product liability; replacement and transportation costs; extra marketing expenses, etc.

So main two reasons can be told as, reduced costs and stronger reputation;  companies may find and solve flaws, mistakes, and abnormalities before goods leave the production line, saving them money on corrective actions like refunds or recalls. Defect identification not only helps firms save on immediate costs but also prevents long-term harm to their reputations in the form of lowered consumer confidence and potentially product liability lawsuits.

Conclusion

Computer Vision in defect detection brings a range of benefits to manufacturing businesses. The technology aids in the quick discovery of defects and the removal of defective components before they are used in manufacturing. Manufacturers can eliminate manual operations by utilizing computer vision's unrivaled automation capabilities. They are able to avoid production mistakes, damage to their reputation, and income losses. Those Technologies might require significant investments due to high software costs and even higher additional hardware costs. However, companies like Cameralyze have found a revolutionary solution for that, with quite low subscription based systems and solutions that can be integrated to every camera and hardware, saving businesses from a lot of big costs and benefits them with increasing the production qualities. Using the no-code structure also does not require high technical knowledge. You can sign up here and try a free demo version just in seconds.