Maintenance Analytics: A Solution to Parts Shortages and Supply Chain Delays?

“Decimating,” “hobbled,” “headache,” and “constant pressure.”

This is how fleet executives described the impact of supply chain delays on truck maintenance.

Parking trucks for lack of drivers is nothing new to the industry. Parking trucks for lack of parts is.

The topic has made its way from shop floors to driver forums, boardrooms, and investor calls as a headwind. With companies waiting up to three months longer for even basic parts, just keeping enough trucks on the road represents a real challenge.

Luckily, fleets are not powerless in the industry’s maintenance melee. Predictive analytics using truck data and telematics devices hold the key to fighting back against today’s supply chain struggles.

Out-of-Service Setbacks

Many U.S. trucking companies report having up to 10% of their fleet out-of-service due to maintenance delays. Intensifying the problem is a long-term truck shortage since the pandemic’s start. OEMs are falling behind on new truck orders—or canceling them altogether—often because of their own parts shortages. That has fleets extending the life of existing trucks.

Older equipment requires more repairs, and the pandemic-related trend of fleet running used equipment longer is a contributor to the 20.4% jump in truck repair costs between 2020 and 2022.

Downtime averaging two to four days now is taking between seven and 10. In many cases, shops don’t know when a part will come in. Technicians are getting creative in sourcing. Partnering with rural shops, scouring eBay, and using existing equipment as parts donors is quickly becoming a norm rather than the exception.

Even the threat of a recession offers little hope for relief. FTR Transportation Intelligence predicts 96% truck utilization in 2023 indicating a strong demand for capacity.

Out of service is simply not an option.

Predictive Analytics for Parts Inventory Management

Predictive analytics is a proven tool for improving equipment uptime. Catching real-time truck issues and better managing preventative maintenance avoids costly roadside breakdowns and extends the life of equipment.

The data science behind predictive maintenance offers a unique way to navigate supply chain slowdowns. Understanding when a truck will require a repair, and why, lets maintenance shop inventory managers get ahead of the parts delays keeping thousands of trucks off the road every day.

With predictive analytics, the SKU ordered today isn’t for the truck sitting in the shop right now. The part is for the problem technology anticipates will happen in the near future. It is as close to a crystal ball as any maintenance operation could hope for and creates three unique opportunities.

1. Ordering the Right Parts at the Right Time

Predictive analytics technology aggregates data across every piece of equipment down to the part. The model forecasts with a high level of accuracy when a part will fail or require intervention. Ordering in advance minimizes the impact of supply chain delays. Rather than waiting for days or weeks for a shipment to arrive, the part is ready in stock before the problem occurs.

Capital tied up in inventory represents a key driver of maintenance costs. Managing inventory with a “just in case” methodology is expensive. Predictive analytics collected through telematics devices lets inventory managers order more intelligently to have the right parts at the right time. No guesswork. No extended downtime.

Plus, the technology shows the right inventory location. Rather than centralized storage, fleets can distribute the needed parts to the locations where repairs will happen. This minimizes unnecessary mileage and time lost to repair routings.

2. Finding Alternative Options

The price of brake drums is up year-over-year around 47%. The part requires pig iron, a large export of Ukraine. Now brake drums, rotors, and kits are in short supply with the country engaged in war. Finding other suppliers takes time—something a shop doesn’t have with a truck already sitting over the maintenance pit. Rush orders command premium prices.

With predictive analytics anticipating repair needs, maintenance operations have time to source parts from other suppliers while better controlling for costs. The move supports a company’s overall continuity plan as shortages among parts constantly change.

3. Using Labor More Efficiently

Currently 80,000 open positions for diesel mechanics exist in the U.S. Wasting these skilled mechanics’ time diagnosing problems, waiting on inventory, and sourcing parts worsens the out-of-service problem.

Maintenance analytics reduces diagnostic time by spotting the likely problem before the truck pulls into the shop door. Mechanics can train on an impending problem in advance. This also minimizes the time to make the repair.

The analytics benefit drivers as well. Breakdowns and equipment downtime impact pay, the number one cause of driver turnover industry wide. Scheduling proactive and routine maintenance together minimizes the time a driver’s wheels aren’t turning. Plus, the technology lessens the burden on the driver to alert the shop of repair needs. The maintenance team can anticipate the issue and prepare accordingly.

Update Your Inventory Management with Uptake

Uptake Fleet delivers real analysis that keeps trucks on the road. The technology pairs with Geotab to analyze vehicle data to find problems before they occur. The insights help fleets prioritize maintenance decisions, effectively manage inventory, and prolong the life of the equipment.

By pairing current sensor feeds with historical equipment data, companies using Uptake Fleet show a 15% improvement in equipment availability, a 4% maintenance cost reduction, and a 37% decrease in technician time. In an industry where time is money, Uptake Fleet pays off.

Want to learn more about how Uptake Fleet can transform your maintenance operation? Download “The Ultimate Guide for Maximizing Vehicle Uptime.”

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