Deep-learning algorithms are enabling powerful video analytics. A practical use in manufacturing is monitoring human actions in manual operations. Some assemblies require specific torquing sequences, which can't always be tracked with traditional methods. AI-based Computer Vision advances quality management.
Verification of assembly processes is common practice across manufacturing to help guarantee quality. The current methodology is to inspect after something is applied or assembled. This practice works well for many inspection applications, for example, if the process is automated with motion control and applicators.
Quality & Manual Operations
Manual operations have benefits, which is why many factories are not highly automated. One reason is manual operations are less costly due to the flexibility in dynamic environments, especially compared to adding automation. Even though manual operations tend to be more dynamic and less expensive, they have their own breadth of challenges. If an assembly operation is not fully automated there are some challenges from a quality perspective to overcome.
AI-based Computer Vision Advances Quality Management
Quality management is essential for all assembly operations, but especially in manual assembly. In some applications, timing or a specific sequence of actions matter. Many processes struggle with implementing quality assurance protocols because traditional methods reduce throughput by requiring people to modify the operations to compliment the inspection solution, rather than complimenting the operation.