Yale Reliant, a lift truck operator assistance system, was crowned a 2021 Product of the Year by readers of Material Handling Product Newsand MaterialHandling247.com. The innovative technology suite beat out three other competitors in the ergonomics and safety category.

Yale Reliant is an industry-first package of technologies for supporting lift truck operator awareness and adherence to best practices. The solution monitors the operating environment and equipment information in real-time to trigger dynamic alerts and automatic performance adjustments.

Performance adjustments include a broad range of functionality on the warehouse floor, such as automatic speed reduction for stability when cornering and preventing trucks from moving overweight loads. The tool can also be used to reinforce site-specific traffic rules such as proper following distance, reduced speed around pedestrians, and restricted lift height in specific areas.

“With warehouse labor in short supply and pressure to fulfill greater order volumes at an increasingly fast pace, maintaining a strict focus on lift truck operating best practices can be a challenge,” says Brad Long, Brand Manager, Yale Materials Handling Corporation. “Yale Reliant is the latest example of how our lift truck technologies give warehouses the modern solutions they deserve – no need to settle for the same old, tired options.”

While the system automatically limits truck performance, the operator always remains in ultimate control of the lift truck. For instance, the system activates automatic speed reduction to reinforce adherence to location-specific rules, but the operator maintains control of steering and braking to steer away from a hazard or bring the truck to a complete stop.

In addition to the change in truck performance, the display monitor issues a visual alert to inform the operator of the reason for intervention. This information provides an additional layer of feedback that can be helpful for reinforcing the proper operating technique established during training.