Image Sensors in Era of Smart Factories

Sasken: The Image processing, which is done on top of an image, makes a lot of difference in the outcome of a picture. This is key in making user experience better. The analytics on image, specific to use case/application adds lot of value to customer. Sasken’s ability to build re-usable blocks and quickly adapt to new requirement/use case/application is a key differentiator. Another unique value is the ability to build real-time image processing algorithm, which could be adapted quickly in Automotive and retail segments.

The amount of time required in verifying image processing algorithms without automation would be significantly higher. It requires execution of lot of repeated test cases and labour intensive job which might lead to poor quality products. Sasken’s test automation services enable customers to build quality products and take them to the market faster.

R&D  In Era of Industry 4.0

Infineon: Accurate 3D depth data can be beneficial for numerous Industry 4.0 applications such as people or object movement counting in the area of security and surveillance. Another major application field is industrial automation and robotics. Due to high diversity of system requirements, these applications require solutions developed in partnership with customer and camera design-house.

Texas Instruments: Right now, a lot more applications are being explored in Factory Automation by utilizing the advantages of this imaging technology, which were a challenge to implement till date with existing solutions. 3D-TOF sensors can detect objects’ shapes and dimensions to help robot understand how to position the grippers, making the whole operation lot less time consuming and efficient. Also, one key R&D effort underway is to come out with relatively lower cost lower pixel array 3D ToF Sensing devices, to enable usage of this technology in cost sensitive applications.

ON Semiconductor: The imaging needs of Industry 4.0 start first with the imaging needs of the application – the resolution, light sensitivity requirements, shutter performance, etc., required for the job in question.  Industry 4.0 may impose additional requirements – such as small physical size, low power footprint, or system-on-chip processing – that add to these base product needs.  We address these additional requirements through the development of small-pixel architectures, advanced digital processing blocks, and product options that reduce the power footprint required for operation.

Sasken: We are in the process of adapting existing sensors and algorithms/capability in the Industrial domain which would enable us to quickly address use cases in same. Some of the use cases include factory process operation inspection, output quality inspection, equipment health, asset tracking, etc. There is also emphasis on capturing good picture/vision in all environment conditions. Here, real-time action is needed in case of quality inspection and rejection of output products. The algorithm must be tuned to specific needs to address real problems. Image sensors and analytics would help to speed up the manufacturing time and make process more efficient and robust.

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