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Why use Machine Vision?

The case for Machine Vision

In the early days of machine vision, the choice to implement or not to implement a machine vision system required a lengthy process of cost-benefit analysis and making tough decisions around the restructuring of the workforce. As the machine vision systems became cheaper over time and companies realized the benefits that a machine vision system can bring, the gates for adoption in both manufacturing and non-manufacturing industries were wide open.

Semiconductor manufacturers were the early adopters and they currently account for about half of the machine vision systems deployed in the factories. Acceptance grew quickly soon after throughout the manufacturing sector with machine vision systems getting deployed in food processing, pharmaceuticals, wood and paper, plastics, metal fabrication and other industries.

Today, machine vision systems have become an integral part of the manufacturing process. Moreover, numerous non-manufacturing applications are being discovered for example volumetric capture and sports live-streaming. Let’s have a look at the benefits that a machine vision system can bring to both manufacturing and non-manufacturing industries:

Manufacturing

  • Significant Cost Savings Detection of small defects at an early stage of manufacturing stops defective products from preceding to the later stages. Early removal of defective products not only saves material costs but also saves time that is spent on repair and reworks.

  • Less Scrap & Waste – Higher accuracy of measurement allows efficient use of raw materials thus reducing scrap and waste during the manufacturing process.

  • Higher Quality Products – Tracking and analysis of defects not only make it possible to iterate product designs faster, but the self-learning nature of AI-based systems helps them to predict recurring defects in advance. The result is a very high-quality product.
  • Increased Productivity – The ability to inspect products of all sizes at very high-speed without any supervision drastically increase overall productivity.

  • Better Inventory Control – Scanning and logging information about products increases traceability and results in better inventory control.

  • Safe Work Environment – Machine vision systems reduce human involvement in the manufacturing process. Thus, they prevent the contamination of clean rooms and protect human workers from hazardous environments.

Non-Manufacturing

  • Split-Second Moments – The advent of extremely high-speed cameras with frame rates going up to [email protected] has made it possible to capture split-second moments with great details.

  • Low-Latency Streaming – In addition to extremely high speeds, today’s machine vision systems can stream images at 100Gbps with less than 1us latency. This results in negligible lag for video streams and has enabled many new applications including live-streaming 3D events in virtual reality.

  • High-Resolution Mapping – For applications where the camera is mounted on a moving platform for example a satellite or an unmanned aerial vehicle, packing as much detail as possible in one image is very important. Today’s machine vision cameras can capture a whooping 152MP image at 16FPS making far-distance imaging a reality.

  • Long-Distance Data Delivery – For environments that require delivery of images over long distances for example undersea inspection, SFP+/SFP28 single-mode cabling can enable the delivery of images at maximum frame rate for up to 10 kilometers.
  • Event-based Monitoring – AI-based machine vision systems can be programmed to respond to events. For example, unlocking a door upon recognizing a face or raising an alarm upon detecting an intruder.

  • High Dynamic Range – Machine vision cameras can be programmed using sequencer feature to automatically capture images at various exposure times and gains. This is particularly useful when a camera is mounted on a vehicle and is being used both during the day and at night.