Extending Fleet Life

Training technicians for predictive maintenance.


One of the biggest costs associated with fleet operations is aging and turnover of vehicles and equipment. It's a given that preventive maintenance can play a huge role in extending fleet life. But can training also have an impact?

If you read this issue's feature article on the City of Oconomowoc (page 6), you see how a robust preventive maintenance program can keep your aging fleet performing well beyond expectations. It's hard to believe, but a study as recent as 2000 (cited by the Federal Energy Management Program) showed that over 50 percent of businesses in the United States that use vehicles and/or equipment still employ a primarily "reactive" maintenance strategy. That is, there are no formal efforts taken to either prevent failures through regular maintenance or to maintain the equipment as the manufacturer recommends. They are using a simple "fix it if it breaks" approach.

While the reactive strategy is cheaper in terms of staffing, materials and up-front costs, the long-term costs related to down time, customer dissatisfaction and eventual equipment turnover are much worse. So, training on proven preventive maintenance strategies can be somewhat beneficial.

Moving beyond preventive maintenance and into the realm of predictive maintenance can provide even further long-term cost savings and extended fleet life. The same FEMP-cited study shows that, while about 45 percent of businesses surveyed employ at least a preventive maintenance strategy, only 12 percent carry that to the predictive maintenance level.

Predictive maintenance bases maintenance needs not only on scheduled intervals, but also on actual wear indicators exhibited by the vehicle or equipment. In this way, predictive maintenance is a better way to prevent more "catastrophic" failures down the road.

With the continuing improvements in scan tool technologies and expansion of their capabilities, the possibilities for predictive maintenance are greater than ever. Engines and automatic transmissions, for example, already have a number of operating parameter values (for control system inputs, outputs and operating characteristics) that can be accessed through diagnostic equipment. And control identifiers for anti-lock brakes and body systems are rapidly catching up to this level. Other diagnostic technologies like heat analysis are also making their way into the automotive and heavy duty world.

Certainly, training in an overall predictive maintenance strategy is a good start. But where training can really have an impact is in the use of the diagnostic software or equipment and, especially, analysis of the diagnostic data available.

The increased precision of vehicle control systems can be a double-edged sword. While providing more robust information to the diagnostic technician about operating conditions that can be used in predictive maintenance, the complexity can be overwhelming. For example, a 2006-level diesel engine control system for one of my OEM customers had about 100 parameter identifiers (PIDs) available through their scan tool. For their latest diesel engine meeting 2007-level EPA emissions requirements, the number of PIDs has increased to over 300!

Training that covers accessing, selecting and recording operating parameters via diagnostic software is essential. But it must be paired with follow-up training in data and graph analysis to be used for predictive maintenance.

The biggest drawback to predictive maintenance is initial cost—both in terms of the diagnostic equipment/software and technician training. Fleet managers may also have concerns about tying up resources too often on predictive tasks instead of the more routine—but essential—preventive maintenance and service tasks. A few fleets and plants in the U.S. have started to employ a cost-centered approach; that is, focusing predictive maintenance on vehicles and systems that are of higher importance or have a higher failure potential, and falling back on preventive maintenance or even some reactive maintenance for systems that are more reliable and/or inexpensive to repair.

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