Cobot and AI Technology in Food and Beverage Processing
Collaborative Robots (Cobots):
Working in the same space as humans without a working cell or industrial fencing, a collaborative robot, or Cobot, is equipped with additional sensing that allows it to stop movement immediately when contacting foreign objects within the working envelope.
In the last five years, Cobots have become a significant addition to the industrial robot portfolio, and have been introduced by both existing suppliers as well as many new vendors.
Because Cobots – unlike traditional industrial robots – can operate without additional equipment such as caging, light curtains, etc. the footprint of the robot is minimized and costs associated with ancillary equipment are reduced.
The majority of Cobots support a payload below 10kg, which still enables a wide range of applications - such as pick and place - in the food and beverage industry. Their easy programming requires an operator only to move the Cobot to the desired fixed points, which are memorized and then automatically repeated. Cobots can be quickly introduced to the manufacturing line with “out-of-the-box” setup and easy programming, coupled with the fact that they don’t require additional safety equipment or fencing. The ease of moving a Cobot to other parts of the production line without disassembly also enables the support of multiple tasks and the production of various SKU’s.
The development of robotics and artificial intelligence is becoming more intertwined as robot vendors look to supply solutions that can support and enhance decision making processes while also replacing some repetitive human tasks.
Artificial intelligence (AI) capabilities will soon be providing an advanced level of analytics to the manufacturing sector, and robot vendors have been actively ensuring that they have the capabilities to support this trend through investments in artificial intelligence - through small acquisitions, joint ventures or partnerships.
Potential applications for AI are extensive:
- Minimizing downtime by pre-scheduling maintenance and ordering spare parts in robots with a high risk of breakdown.
- Optimizing robot movements by analyzing vision system and sensor data to reduce the time taken to complete a task.
- Reducing the time taken to learn new tasks with network-connected robots learning together.
In addition, combining artificial intelligence with machine vision systems is supporting significant developments in quality control, by enabling the robot to identify faulty products and remove them from the production process.
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Source: PMMI Business Intelligence “Industrial Robot Opportunities in Food and Beverage Processing”