![]() By using a robot to move around a camera, the limitations of 2D inspection can be mitigated by taking images at multiple angles with multiple lighting applications. Assembly and Process Inspection – Using computer vision with a robot can provide inspection for robotic assembly or robotic process to ensure the value intended to be added by the robot has indeed been added.Processes in the electronic manufacturing industry such as bonding, fastening, welding, soldering, spraying and masking help to create repeatable actions, which are helpful in controlling key process or performance indicators. Production Processes – Leveraging robotics for a single process across multiple products is another great use for industrial robotics.Examples here would be Printed Circuit Board Assembly (PCBA) or higher level assemblies, such as enclosures or single-use medical devices. However, when paired with computer vision systems and products designed for automation, accurate distinctions can be made with greater consistency and efficiency. Robotic manipulation of components in this environment is difficult. ![]() Product Assembly – One of the most common applications of robotics in contract manufacturing is in the assembly of products.To identify opportunities, we can categorize the applications of robotics according to the following: In this context, automation and robotics set the precedent and groundwork for using AI in your broader smart factory initiatives. The role of artificial intelligence in roboticsĪs you consider how AI can improve automated processes, you’ll quickly realize that this largely translates into understanding where and how to implement artificial intelligence and machine learning in robotics. Why so few? Likely because it can be challenging to know where to focus and how to get started. However, only approximately 9% of manufacturing organizations are leveraging artificial intelligence today. This can also improve quality, reduce cost and accelerate time to market. By allowing machine learning algorithms to utilize Internet of Things (IoT), sensor data and images, configurations can be implemented in real-time to further optimize production facilities and reduce downtime to a minimum. According to a review by BCG and MIT Sloan Management, nearly 85% of executives expect AI to enable them to obtain or sustain a competitive advantage. Intelligent adoption of artificial intelligence (AI) and machine learning to improve automated processes can be hugely rewarding. Artificial intelligence in robotics brings huge potential for manufacturers ready to embrace it.Ĭompanies are in a race to embrace new technologies to drive digital transformation and enable Industry 4.0.
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