Accuracy in production is crucial for gear manufacturers. Faulty production can end up causing them severe financial damage. However, no production process is error-proof. Because of this, checking for errors becomes critical as it also helps in improving the production process. Visual inspection by people is the primary way manufacturers check for errors. Experienced individuals in this area can be a great asset to gear manufacturers. But even then, fatigue and boredom lead to miss outs.
To alleviate this problem, several manufacturers employ machines for this critical task. Technology-oriented systems have led to better control of both manufacturing and error checking processes. This comes with its caveats, though. Machine-based visual inspection is quite efficient when it comes to gears with minimal variations compared to the standard. However, gears with significant variations cause machines to struggling with finding errors. Many such machines are based on either hard-coded rules or a golden image, which depends on comparing a product’s image with that of an error-free standard image. Because of this, machines may classify the right gear as defective in a false positive and vice-versa.
The answer to the problem lies in deploying artificial intelligence (AI)-based visual detection systems. The following are the most significant benefits of using these systems in the visual gear inspection process:
- Removes subjectivity: With a rule-based machine, there has to be an overlay of manual inspection, which defeats the purpose of using a machine in the first place. An AI-based system eliminates this subjectivity in gear inspection because of adaptive learning, which helps increase its accuracy with time.
- Increased efficiency in production: With errors being removed because of superior visual inspection, the production process is improved because of identifying areas that were causing the errors, to begin with.
- Scalability: Rule-based machines can work well for simple products and a limited number of units being produced. But for more complex gears that need to be produced in large numbers, such machines become a liability. On the other hand, an AI-based system is highly scalable as it learns from itself, making it adaptive to changing production needs.
- Customizability: The number of variables required for visual inspection can be changed according to changing production environments. Their adaptability makes them highly customizable.
Gear manufacturers have such AI-powered systems available to them. Griffyn Robotech offers Optivity – an industry 4.0 – ready vision-based inspection system which can be deployed for gear inspection. It is quick and precise while inspecting gears and its advanced machine learning algorithm allows it to locate the exact error. It can be operated by unskilled labor, thus eliminating the need for hiring technical personnel. Optivity can provide the edge that your gear manufacturing business needs to gain an advantage over your competition.
Griffyn Robotech is a company focused on leveraging technology to create smart solutions for manufacturing industries. We can present a solution to all the challenges related to machine learning and quality control.
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