How to boost performance and productivity with AIoT
Scenario
In the Industry 5.0 landscape, where efficiency and accuracy are crucial, it is crucial to detect manufacturing defects in real time to speed up operations, optimize resources and cut costs.
Identify anomalies to increase productivity
Identifying anomalies during the production process ensures the quality of the final product and optimizes the production chain. This operation, however, requires considerable time and resources, resulting in an impact on productivity and operating costs.
The central role of GCP and AutoML Vision Object Detection.
The chosen development environment was an Industry 5.0 Factory Simulator, an innovative prototype supported by Google Cloud Platform. Central to the solution were the powerful capabilities offered by AutoML Vision Object Detection, which enabled the training of a custom model capable of accurately detecting and discriminating different types of objects in real time.
Object detection up to 10 times faster with Coral TPU
Coral TPU technology has enhanced the performance of the solution, making object detection up to ten times faster, with a minimum delay of about 10 milliseconds.
Compatibility and accessibility through TensorFlow Lite
The TensorFlow Lite (TF Lite) framework has made the solution compatible with mobile devices, so it is even more accessible and ready to use: thus, the system enables defect detection directly in the field, without the need for a continuous Internet connection.
A fast, flexible and 100% accurate model
The trained model has proven to be 100 percent accurate and 10 times faster in object detection, allowing it to cut down on uptime. In fact, the solution has greatly simplified production processes, improving product quality and inventory management. As a result, human resources are able to focus on strategic activities and see reduced operational costs and risks associated with production.
In conclusion, the project offers a wide range of possibilities and unprecedented flexibility, easily adapting to the specific needs of each customer and production environment.
