When it comes to order processing for any ecommerce business, much credit is given to automated inventory management systems and organized warehouse personnel workflow. What is often overlooked, however, is the literal heavy lifting which drives any well-oiled logistics supply chain − specifically, the hard work done by forklifts and their operators to make sure the right payload arrives at the right order collection point.
The forklift itself is by no means at the forefront of tech innovation, nor does it appear to be the most obvious application for autonomous solutions. Yet, the potential growth of order processing efficiency that could be enabled by AI-augmented forklifts cannot be denied. This is particularly true for AI solutions which can decrease forklift operator accident rates and increase warehouse safety as a whole.
Warehouses, in order to keep up with pressing cargo deadlines and the ever-rising trend of single-day deliveries, are by no means calm and well-ordered environments. Rather, they are pushed to be fast moving, and oftentimes as an unfortunate side-effect, disorganized. In heavily-trafficked zones of warehouses, where numerous payloads are being transported at any given moment, forklift accidents are the most likely to happen and tend to incur the greatest human and economic cost.
In addition, a single forklift operating incident, be it overturned payloads or harmed employees, creates a domino effect which disrupts the entire supply chain system. Redirected transport routes for circumventing an accident site and the resulting bottleneck of forklift traffic within a busy warehouse translates into time lost in collecting and organizing product orders. The personnel required for dealing with an accident and the additional vehicles needed to put everything back into order means manpower and machinery transferred away from their original tasks of inventory preparation or transport. Time lost for cargo transfer and order preparation means delays in meeting delivery deadlines. The end result − a general postponing of order deliveries and an increased likelihood of customer dissatisfaction.
In the case of forklift driving incidents involving warehouse personnel, there is no doubt that human casualties should be minimized at all costs. As a more dangerous working environment populated by heavy machinery, it is essential that company warehouses’ strive to decrease personnel accident rates however possible.
The importance of minimizing safety hazards for forklift operators and surrounding warehouse personnel calls for an innovative tech solution. While AI-augmented forklifts might not appear to be the most obvious answer, they promise to be the most effective one. By shifting the focus from protection to prevention, solutions like our VIA Mobile360 AI Forklift Safety Kit can help companies to identify and tackle the root causes of accidents within warehouse working environments.
For example, the kit’s comprehensive AI-powered DMS (Driver Monitoring System), including Driver Facial Recognition and Driver Drowsiness Detection, prevents unauthorized vehicle use while promoting operator well-being. Rich visual intelligence features such as object detection and DMOD (Dynamic Moving Object Detection) cut down on reaction time to potential safety threats, one example being the unexpected arrival of another vehicle or person within close range. Finally, high performance hardware paired with a four-camera SVS (Surround View System) heightens operators’ situational awareness and execution efficiency.
Efficient warehouse order processing will only grow more important with the continued rise of ecommerce. As inventory management systems become smarter and personnel workflows become better coordinated, it is vital that the forklifts which execute all our heavy lifting and cargo transport within warehouses receive an upgrade as well with the integration of AI -powered features that enhance operator performance and safety.
Written by Josephine Cheng, a current intern at VIA and a Communications student at the University of Pennsylvania.