As digitization and automation become mainstream, materials handling vehicles (MHVs) are evolving from passive tools to intelligent, connected pieces of the supply chain. Navigant Research believes that advanced technology options for MHVs are nascent in the materials handling industry and offer significant improvements over traditional options. As the needs of these users grow more complex, it will be important that equipment evolves as seamlessly and efficiently as possible.
The application of Internet of Things (IoT) technology is not limited to automation; it also increasingly enables data integration and using materials handling equipment as data sources. Businesses are turning to data-driven intelligence to guide decisions that improve operational efficiency and protect the bottom line. For MHVs, connected fleets and data-driven operations produce a wealth of small floor-level insights that are transformed into actionable business intelligence. Several companies recognize this and are making steps to ensure predictive analytics play a role in day-to-day operations.
IoT’s Role in Equipment Maintenance
Besides operational efficiency, IoT technology is playing an increasing role in equipment maintenance. Autonomously monitoring the condition of MHV components and generating trouble codes for service technicians can be used to detect failures and/or equipment wear before they affect the vehicle’s performance. For example, forklift manufacturer Linde is working on automating the procedure of troubleshooting fleet issues, ordering spare vehicle parts, and scheduling service engineers while simultaneously informing the customer about the order status. In turn, this makes it easier to streamline orders, identify bottlenecks, and provides transparency to customers.
Advanced Automation – Playing a Role in the Integration of Emerging Electric Powertrain Options
Communication-enabled battery data and chargers allow warehouses to:
- Reduce or eliminate the battery room footprint by eliminating the need for bulky charging infrastructure
- Improve forklift uptime by way of opportunity charging
- Decrease the number of batteries and chargers onsite because of improved battery runtime
Navigant Research’s Advanced Electric Forklift Technologies in North America report states that advanced electric technologies for forklifts may have higher upfront prices. However, they can reduce operating costs with longer runtime and reduced fueling over the lifespan of the fleet.
Several battery manufacturers see increased interest in traction technologies nascent to the industry. One of the first companies to do so, Navitas Systems, recently announced it will deploy the Starlifter battery at a Defense Logistics Agency (DLA) in Pennsylvania. Navitas’ program objective is to evaluate the utility, feasibility, maintainability, and cost-effectiveness of replacing lead-acid batteries with fast-charging lithium ion (Li-ion) deep-cycle forklift batteries in DLA Distribution warehouses. The program also hopes to decrease total forklift battery costs of ownership and increase forklift operational readiness and productivity. Companies like Linde and Electrovaya also have recently announced new Li-ion options for forklift batteries as a result of the demands of current warehouse and logistics environments. Much different than the industry 20 years ago, modern warehouses have increased demand for operational efficiency, around-the-clock operations, and more advanced vehicles capable of working in cold storage climates.
Fleet managers look to operational data to improve efficiency and competitiveness. Real-time floor-level alerts are increasingly important so operators can address issues immediately. Customers also expect greater visibility into their lift truck fleet, support equipment, and ongoing asset health. In the future, vehicles will communicate with each other, decision-making will be at the user level, and batteries and charging infrastructure will combine with operator and truck data to inform fleet management across both forklift and powertrain platforms.