The future of uptime: Why the load handling industry must move from preventive to predictive maintenance
In the on-road load handling industry, a machine is only as valuable as its availability. For decades, the primary strategy for keeping fleets running has been strict, calendar-driven servicing. But as the industry moves faster and margins grow tighter, the traditional approach to equipment care is no longer enough.
At Hiab, we believe the future of safer, more sustainable lifecycle services relies on a fundamental industry shift: moving away from reactive and preventive schedules, and stepping fully into the era of predictive maintenance, powered by AI.
Understanding the shift: preventive vs. predictive maintenance
To understand where the industry is heading, we must clearly distinguish between how maintenance has historically been managed and how connected data is rewriting the rules.
Preventive maintenance relies on predefined intervals, such as replacing wear parts after a set number of operating hours or conducting structural inspections annually. While this interval-based approach is highly effective at minimizing emergency breakdowns, it operates without knowing the actual condition of the machine. It can lead to over-servicing, where perfectly functional components are replaced prematurely, yet it still leaves fleets vulnerable to sudden, unforeseen failures between scheduled visits.
Predictive maintenance, on the other hand, is condition-based. It utilizes real-time asset data, advanced sensors, and telemetry to continuously monitor the actual health of the equipment. Instead of servicing a machine on a fixed schedule, connected systems analyze sensor data, track fluctuations and anomalies, and monitor load cycles to anticipate component failure before it happens. Maintenance is scheduled based on fact-based insights, reducing the risk of unexpected downtime and unnecessary component waste.
Our vision: engineering maximum uptime
For predictive maintenance to become a reality, hardware, software, big data and human expertise must work together seamlessly.
Michael Bruninx, President of Services at Hiab, explains the strategic imperative: "Historically, the load handling industry has treated physical maintenance and connectivity as two completely separate investments. Our vision is to eliminate that divide. We are no longer just fixing equipment; we are utilizing connected data to actively engineer maximum uptime for our customers.”
This confidence is grounded in scale. Through a sustained investment over many years, Hiab has amassed data from more than 50,000 connected assets and over 1,000,000 completed service visits. Michael elaborates, “As the market leader in load handling equipment, we see this as more than an opportunity; it is our responsibility to set the industry standard. Our customers rely on us to support their productivity, enable safer operations, and reduce downtime.”
The path forward: collaboration is key
The true power of predictive maintenance is unlocked through deep collaboration with our customers and our authorized service partners globally.
When connected insights flag a predictive alert, the goal is to equip our local service teams and partners with exact diagnostic data before they even touch the machine. This transforms the entire workflow. Instead of reacting to an urgent phone call from a stranded driver, the service team can preemptively order the required parts, contact the fleet manager, and schedule a targeted repair during the truck’s planned idle time.
The transition from preventive schedules to predictive intelligence is an ongoing journey. As we continue to invest in connected solutions and integrated service models, we look forward to sharing more about the next evolution of our service offerings very soon.
Stay tuned as we build a smarter, more predictable future for load handling.
