Material-handling activities can be dangerous because they require repetitive tasks that may cause strain or injuries. Additionally, employees must learn specifics such as proper lifting techniques and ergonomic posture principles to increase their chances of staying safe on the job.
Understandably, many executives wonder if there is an easier, more effective way. Some have begun investigating automated material handling technologies that work with artificial intelligence. They believe AI could create safer workplaces by assisting with tasks or wholly handling them so employees can transition into less strenuous, more rewarding work. What are some examples of the emerging possibilities?
Handling Dangerous or Dirty Tasks
“AI could be a game-changer for especially dangerous or dirty tasks that involve handling heavy or cumbersome things in industrial environments.”
For example, some mining leaders have applied artificial intelligence to ore sorting. The technology identifies and separates the valuable materials from waste, improving an activity that formerly required significant manual labor.
Conveyors are also staples of mining and other industries that require moving goods consistently and quickly. One practical way to combine conveyor belts with AI is to install cameras that use machine learning and computer vision to verify whether materials are defective or meet quality standards.
Meeting Industry-Specific Needs With Versatility
Another benefit of using AI-powered material-handling systems is that many vendors offer options made with particular industry needs in mind. Relatedly, AI technology for material handling often includes sensors, advanced cameras and other integrated features that allow the equipment to recognize and react to many environmental obstacles.
For example, food and pharmaceutical companies choose plastic pallets because they are nonporous, making them more sanitary than wood options. Additionally, the smoothness makes it an ideal material for pairing with automated systems, whether cobots, guided robots or lifts. Artificial intelligence can boost productivity and reduce errors, keeping injury rates low while allowing companies to meet goals.
Improving Human Workflows
AI material-handling investments aim to reduce or eliminate activities that often cause accidents and other safety-related issues. Even though the associated technologies are still in the early stages, a few current examples show there is plenty to feel excited about when industrial leaders ponder the possibilities.
In one case, a technology for autonomous forklifts and reach trucks generates more than 16.5 million data points per second with each of its cameras. This allows the material-handling equipment to recognize obstacles and respond to them swiftly. This particular system requires human oversight, illustrating how workers’ jobs may change soon when they can minimize or eliminate time spent on potentially dangerous activities at work.
Combining AI With Accountability
These are some of the compelling reasons why many of today’s leaders want to optimize material handling tasks with artificial intelligence. However, even if they invest in the most advanced systems available, they must still devote sufficient time and other resources to training workers, keeping their skills sharp as their roles change, and creating a work environment where everyone understands and upholds their role in maintaining safety.
Once people understand the value of personal accountability, they can apply that commitment to every material-handling task, regardless of whether AI helps them do it.
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