Machine Vision: How Can It Benefit Your Manufacturing Process [A LIVE WEBINAR]
Machine vision is a combination of seeing and understanding. It mimics the human eyes and brain. It makes machine vision applications more sophisticated. Such systems provide sophisticated analysis like image recognition. It works using various data science methods like deep learning and advanced big data analytics. Machine vision in manufacturing increases efficiency and reduces costs.
With rapid developments in many different areas including imaging techniques, embedded vision, machine, and deep learning, robot interfaces, data transmission standards, and image processing capabilities, vision technology can benefit the manufacturing industry at many different levels.
Different pain areas addressed by leveraging machine vision:
Predictive Maintenance
Predictive maintenance forecasts failure and helps to take corrective actions or replace the system. This can lead to major cost savings. Machine vision in manufacturing performs predictive analytics based on data provided by sensors to take maintenance measures on time.
Barcodes scanning and Reading
The role of a barcode scanner is significant in the manufacturing industry. Manufacturers are provided with several barcode scanning benefits like reduced time and cost, minimized errors, and decreased stress levels.
Inspecting goods
Quality control and product inspection are two main activities of the industry that cannot be ignored. Manufacturers can detect flaws, or cracks in a physical product, with machine vision systems. These systems can also check accurate and precise measurements of components, which, sometimes, can be faulty when done manually. All these issues can be eliminated easily with machine vision that can also optimize the process in less time.
Goals to deploy machine vision in manufacturing:
- Faster production
Being able to produce more in the same timeframe is a major plus for any manufacturer. Machine vision powers precise robots and automates small and repetitive tasks. Robots don’t need breaks, they don’t get tired, and they work in sync.
- Precision
Machines are still not smarter, but they are more precise with delicate tasks. Many items are ruined because of human errors, which increases product rejection and write-offs. Machines can achieve high precision, especially when they use image recognition.
- AI and Automation
Automation of any kind leads to increased efficiency, lower costs and better profits at the end of the day. Primitive automation can use simple controllers to automate the plant and shut it down in case something goes wrong. Smart automation with image recognition can recognize various scenarios and react appropriately.
Incorporating machine vision in manufacturing will benefit manufacturers by helping them predict production flaws in manufacturing lines, improving the quality, cutting down unnecessary costs, and achieving high productivity with automation.
Etag conducts informative webinars every week. We choose topics that will help manufacturers in understanding new trends in the market that will help increase production efficiency.
In this webinar, we will explore how manufacturers can incorporate machine vision in their factory and Identify possible pain areas that can be addressed by leveraging machine vision.
Webinar Agenda
- Topic-related informative session.
- The technical walkthrough of what to expect for a machine vision implementation.
- Industry-based use case documents discussion.
- Question & Answer session.
Key takeaways from the Webinar
- Introduction to Machine Vision in Manufacturing
- How Machine Vision can aid Predictive Maintenance
- How Machine Vision improves product quality and helps in quality control
- How it can enable faster Product and Components Assembly
- Improved Safety & Reduced Defects
- How Machine Vision helps in Package Inspection
- 3D Vision Inspection
- How AI & Deep Learning is utilized in Machine Vision
- Case Studies
Webinar Details
- Speaker: Mr Prashant, Senior IoT Consultant at Etag
- Date: 18th March 2021
- Time : 2 PM EST – 3 PM EST
