Machine vision is used in a wide variety of methods in life sciences applications, each with their own unique needs that are much different than those in the industrial sector.

While you may know exactly what you want your camera to do for your life science application, you may not know which machine vision system would be best for that application.

There are thousands of configurations to choose from, which can make the decision difficult.

Here are 5 things to consider when selecting a camera for life science applications:

  1. Business needs: What business obstacles will the camera help you overcome? Will it be used for increased throughput or to achieve higher yields? Knowing this will help you narrow down your options.
  2. Camera size: Will your camera need to fit in a compact space? Will it need to be integrated into existing systems? Your options will already be limited based on where the camera must be positioned.
  3. Inspection environment: Will the camera be subjected to high heat, vibration or variations in lighting? You may need to purchase a camera that can handle some of the environmental influences your application will present.
  4. Longevity: How long is the lifecycle of your project? This is particularly important for life science applications, especially for products that require FDA approval. You’ll want cameras to last the entire lifecycle of the project to ensure the consistency of results.
  5. Supplier: Who is your supplier? Who you purchase a camera from is important as they should be able to provide customization when needed. They should also provide regular service and maintenance to improve the lifetime of the camera. Most importantly, the supplier needs to be financially stable, otherwise you could lose access to maintenance and equipment replacement.

Choosing a camera for life science applications can be daunting task. There are many options out there and it can be difficult to determine the best one. Take these 5 considerations into account to help you make the best decision.

>> Read more at Vision Online, April 4, 2017

Top 5 Camera Considerations for Machine Vision in Life Sciences