Processing Produce With Artificial Intelligence
Combining custom hardware with vision and AI
CLIENT
Motivo’s solution needed to accommodate different types of produce with a wide variety of shapes, sizes, and imperfections. It needed to be robust and food safe with high cycle times and intense usage. Performance was also key; high precision and accuracy was needed to reduce the need for post-process labor.
OEM automated solutions existed but were limited to “perfectly shaped” fruits and vegetables and yet still yielded about 30% incorrect alignment. These solutions required downstream labor for rework. This labor-intensive rework is highly repetitive and hazardous due to close proximity to the industrial cutters.
CHALLENGE
Motivo’s solution needed to accommodate different types of produce with a wide variety of shapes, sizes, and imperfections. It needed to be robust and food safe with high cycle times and intense usage. Performance was also key; high precision and accuracy was needed to reduce the need for post-process labor.
OEM automated solutions existed but were limited to “perfectly shaped” fruits and vegetables and yet still yielded about 30% incorrect alignment. These solutions required downstream labor for rework. This labor-intensive rework is highly repetitive and hazardous due to close proximity to the industrial cutters.
MOTIVO’S SOLUTION
Motivo began the project by looking at the existing process as-installed, and evaluating different opportunities up front and in coordination with the client. Motivo then proposed a solution that directly integrated with most existing industrial food slicers and cutters to minimize cost and space requirements.
Motivo’s sensing system uses artificial intelligence to visually determine the yaw orientation of a fruit or vegetable as well as its geometric center height, size, and other key parameters. A manipulation stage then gently grasps, lifts, and rotates the fruit until correct alignment is achieved.
OUTCOME
The final solution was able to replace four humans working with/around razor sharp edges in an extremely loud environment (double hearing protection required). Not only was the solution successfully built and tested, but additional automation opportunities up and downstream were identified and are in the process of being implemented. This effort was intentionally designed to be modular in support of future expansion without impacting the flow of the production facility. This project went from initial ideation to a working proof of concept prototype with custom machine vision software in six months.