Kenworth Case Study

Challenge

For fleet operators, unplanned downtime is expensive, disruptive, and potentially tarnishes service reputations. These expenses cut directly into revenue mile profits. With an eye towards reducing unplanned downtime to zero, Kenworth sought the best way to improve the uptime and reliability of their vehicles, starting with their MX-13 engines.

For decades, engines have displayed warning lights for a variety of conditions but these failed to provide drivers with sufficient information to determine whether the issue was an imminent failure that would disable the truck or a minor condition. Service centers used equipment connected directly to the truck that could help diagnose a single condition, but didn’t take into consideration related events or conditions that might accelerate meantime-to-repair (MTTR) and get the truck back on the road more quickly. This manual approach ate into uptime as technicians spent hours troubleshooting and fixing problems. Finally, lengthy and imprecise warranty processing resulted in high warranty costs for Kenworth and lengthy reimbursement periods for its third-party service centers.

Solution

To create a holistic system designed to continually improve truck uptime, Bsquare worked collaboratively with Kenworth over a period of months to fully understand their goals and explore what was possible with Bsquare’s DataV IoT software stack. Several requirements emerged from this collaboration:

• Scalable – the solution needed to scale across upwards of 300,000 trucks with a large number of different engine configurations
• User friendly – all human interaction with the system had to be simple and easy to understand for non-technical users
• Business friendly – the system couldn’t be dependent on the IT department or other technologists to program, report, or administer on a daily basis
• Cost effective – measurable business results had to be clearly achievable to justify the technology investment

Tying in to the existing telematics system that collected and transmitted engine data to an Amazon Web Services (AWS) cloud instance, Bsquare used its DataV software stack to implement predictive failure capabilities and data-driven diagnostics.

Results

Kenworth has been able to become proactive rather than reactive, and tie multiple relevant data sources together with business logic to create a user-friendly, holistic IoT system that scales to hundreds of thousands of trucks. Fleet operators and drivers can now schedule truck service at times and locations that minimize disruption thanks to the insight provided by predictive failure analytics. Revenue miles increase, providing faster ROI on truck investment. Service centers experience multiple benefits:

• The optimal repair plans created from data-driven diagnostics speed repairs, improve efficiency and accurately track parts use. Mechanics can fix the problem right the first time, reducing mean-time-to repair (MTTR).
• Accurate problem identification virtually eliminates false positives, or “no problem found” scenarios.
• The learning loop of the truck-side application makes repairs more efficient as the system eliminates unnecessary diagnostic or repair steps for subsequent repairs.
• More efficient repairs enable faster bay turnover, allowing shops to service more trucks and increase billable dollars per event for increased revenue streams.
• Warranty reimbursement can be accelerated as Kenworth receives faster and more accurate notification of repairs completed.