Depalletizing is the process of unloading boxes or bags from pallets. This process traditionally involves people doing strenuous physical activities like bending, stretching, and heavy lifting.
This is dangerous to people depalletizing, especially when the load is over 25 kilos, and it also slows down the process. The objects also come in different shapes, sizes, and loads, making it more difficult for manual pickers.
Recently the manual labor requirement in warehouses around the United States increased to 1.2 million. In addition, the quarantine and social distancing requirements since the pandemic made it worse because only a few manual pickers were working.
This slowed down warehouse operations, and comparing the increased costs, automating the depalletizing process was the best alternative.
Traditional Depalletizing Methods Limitations
Robotic technology was previously limited to dealing with objects with the same characteristics. This made it hard to use in different warehouse jobs because of the numerous Stock Keeping Unit variations.
One key benefit of working with manual pickers is that they can identify SKU variations and handle them accordingly, making it easier to work with mixed-SKU pallets. Humans have the intelligence to identify objects, differentiate them, pick them up at good speed, and place it in the right place.
Before working in a warehouse, workers must undergo safety and job training to ensure accurate performance. Despite the training, however, humans are still vulnerable to injuries due to heavy lifting.
The University of North Carolina came up with a report indicating that 36% of manual warehouse workers suffer from shoulder and back injuries, resulting in missed work days.
Such incidences cost the company injury claim expenses, legal compliance costs, and safety training, increasing the turnover rate. This is something that all companies want to avoid, which increases the urgency of incorporating robotic depalletizer systems.
Companies must also balance employing new workers and delivering better or consistent throughput results.
Employers’ other common concerns with manual depalletization include lack of supervision, physical constraints, and poor ergonomics. This created the urgency to develop a reliable depalletizing system that does not involve human pickers.
These days, with the development in technology and artificial intelligence, automating a depalletizing system is not hard. Deep-learning algorithms have enabled warehouse owners to employ suitable robotic depalletizing systems.
These systems have appropriate grippers to lift even the heaviest objects and a cutting-edge vision system to avoid accidents.
Factors to Consider For an Automated Depalletizing Process
Usually, manual pickers don’t fully utilize the warehouse space. However, depalletizer cells will optimally use the floor and vertical warehouse space, improving overall performance. It also allows workers to focus on more important tasks.
Robotic depalletizers also come with a 3D vision system with several cameras, laser sensors, and vision software. This helps them capture their environment and determine the position of randomly placed objects.
That enables the robot to scan every object to determine whether it’s the right one, and the grippers allow them to pick the object and place it on the conveyor belt. This way, the robots can handle a long flow of mixed SKU pallets in different sequences.
The vision software also helps integrate the robot’s software and hardware components. It can improve the robot’s accuracy in segmenting objects and allows it to lift heavy objects from random stacks.
Most system integrators use Fizyr’s vision software to help them deal with overlapping and closely stacked boxes.
Whether dealing with the same or mixed-SKU pallets, automated robotic depalletizing help reduce operation costs, enhance productivity, and improve workplace safety.
