MATERIALS HANDLING equipment can be working every day and still tell you remarkably little about how it is actually being used.

If a fault occurs, is it an isolated component failure, or part of a pattern? If one truck requires more maintenance than another, is that simply bad luck, or are the machines being operated differently? An impact is reported. How severe was it, when did it happen and what was the machine doing at the time?

Historically, answering questions like these has relied heavily on operators, service records and the experience of technicians. Increasingly, however, the machine already knows the answer.

The latest addition is impact detection, allowing significant events to be recorded alongside the growing range of operational information available from the machine.

Machine monitoring is hardly new. Hour meters and service reminders have existed for decades, while GPS tracking and basic fleet telematics are now commonplace. The interesting change is the depth of information becoming available.

Baumann Online can provide access to machine location and status, engine hours, active driving time, operator presence, hydraulic activity, fuel or energy consumption and operating behaviour. Machine condition information can include temperatures, pressures, warning signals, fault events and maintenance requirements.

On diesel machines, information can extend to emissions systems, including DPF condition and regeneration history. Taken individually, many of these data points are useful. Taken together, they begin to tell a story.

A recurring fault may correspond with a particular operating pattern. One machine may accumulate considerably more active hours than another supposedly performing the same role. Increasing fuel consumption could indicate a change in operation or condition.

The purpose is not simply to collect more data. It is to make previously invisible behaviour visible. Impact detection provides a particularly straightforward example.

Impacts happen in materials handling environments. Some are insignificant; others may result in damage that is not immediately obvious. Without an objective record, establishing exactly what happened can be difficult. Recording the event provides another piece of evidence.

As connected equipment becomes more sophisticated, that visibility also needs to be managed responsibly. The objective is to understand machine and fleet behaviour, not simply to monitor individuals, where data can be associated with individual operators, its use must therefore take account of applicable privacy and employment requirements.

More importantly, it can be considered alongside other machine information rather than viewed in isolation. Over time, repeated events may reveal patterns associated with particular locations or operating conditions and allow managers to investigate the underlying cause.

The same principle can potentially be applied to other aspects of machine behaviour.

Baumann’s system can accommodate additional sensors to record application-specific information. One example is measuring how long a sideloader is driven with its forks raised above deck level, turning something that would previously have depended upon observation into measurable information. For long-load handling operations, those details matter.

Looking inside the machine

The benefits extend beyond fleet management. Remote access to machine information changes the way technical problems can be investigated.

Instead of a technician arriving with little more than a reported symptom, service personnel can potentially examine operating conditions and fault information before attending the machine.

“It is much more than a telematics system,” says Baumann managing and technical director Riccardo Bove. “We are able to see what is happening inside the machine in real time, from operating conditions through to fault behaviour. That allows us to understand issues much more precisely and to respond in a structured way.”

Real-time information can include engine speed, coolant temperature, oil pressure and other operating measurements, together with active and stored faults.

For the customer, the practical objective is straightforward: quicker diagnosis, better prepared technicians and fewer unnecessary service visits.

From reactive to preventative

The larger opportunity comes from looking at information over time.

Maintenance has traditionally been based largely around operating hours and predetermined service intervals. Connected equipment provides another layer.

Historical information can reveal changes in performance and usage before they become obvious to the operator. Underutilised equipment becomes easier to identify. Service requirements can be related more closely to actual usage and early warning signs can be investigated before they develop into failures.

“We have developed Baumann Online to give customers a much clearer understanding of what is happening within their operation,” explains Baumann CEO Klaus Pirpamer. “It is not only about collecting data, but about making that data usable.”

That distinction is important, a dashboard containing hundreds of measurements is not necessarily useful. The objective is to identify the information that helps somebody make a better decision.

Changing the machine from a distance

Connected equipment can also change what happens after a problem or requirement has been identified.

One relatively simple example is travel speed. A customer may decide that a machine’s maximum speed should be reduced because its operating environment has changed. Traditionally, even a relatively minor parameter alteration could require somebody to visit the truck.

Baumann Online allows certain parameters to be adjusted remotely through a controlled procedure involving the operator.

It is a small example, but illustrates the wider potential of connected machinery. The relationship between manufacturer, service organisation and machine no longer necessarily ends when the truck leaves the factory or dealership.

None of this removes the importance of operators, technicians or good fleet management. Data without context can be every bit as misleading as having no data at all.

What it does provide is evidence, so instead of assuming why one machine performs differently from another, managers can investigate. Instead of waiting for an intermittent fault to become permanent, technicians can examine its history. Instead of relying entirely upon somebody noticing an operating behaviour, it can potentially be measured.

For specialist machines handling long, heavy and sometimes extremely valuable loads, that additional visibility has obvious attractions.

The next development in materials handling may therefore be less about what a machine can lift, and more about what it can tell us.

Because increasingly, the machine already knows.