Predictive technology cuts warehouse accidents and breakdowns

Warehouse safety technology is moving beyond the traditional reactive model towards predictive analytics. To improve safety, extend the lifespan of equipment and make better use of it, predictive technology is increasingly becoming part of standard warehouse management systems.

Warehouse safety policies usually follow a reactive model. Equipment is repaired after it malfunctions. Operators receive safety training in response to an accident or near-miss incident.

Advances in sensors fitted to connected material-handling equipment provide predictive analytics that identify and give warning of impending equipment failures or emerging safety risks.

Unexpected breakdowns of equipment such as fabrication tables, packing stations and aisle-picking trolleys can disrupt warehouse operations. Sensors that detect component wear allow equipment to be maintained before it fails and has to be taken out of service.

Early intervention improves equipment availability and reduces repair costs and disruption.

Telematics technology monitors operator behaviour, including excessive speed and repeated impacts. A single instance of poor operator behaviour may not be a problem, but recurring incidents indicate a safety risk that needs to be addressed.

Gathering data on how equipment is handled informs the content of operator coaching and highlights where extra training is required.

Utilisation data helps management understand how often equipment is used and informs decisions about when to order new equipment.

For electric vehicles, charging cycles can be monitored by AI systems. Charging data, combined with vehicle utilisation information, identifies excessive energy consumption. This helps create a plan to use vehicles more efficiently by reducing unnecessary journeys.

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