Connectivity brings clarity to forklift service requirements
With the rise and evolution of telematics and data analytics, companies are uncovering and utilising data points that are helping them realise significant productivity and efficiency gains across the supply chain.
For instance, says Collin Rush, director of InfoLink customer support, Crown Equipment, a wealth of data can be gathered from forklifts, acting as a sort of information hub for the warehouse.
“Companies are using telematic systems, such as Crown’s InfoLink operator and fleet management system, to capture such data. They then use the insight provided to better understand how forklifts are utilised and make informed decisions that help them achieve operational objectives,” says Rush.
“Since the introduction of telematics to the warehouse, some have anticipated that predictive maintenance will eventually completely transform forklift service, though the industry hasn’t yet reached this point. The good news is that the technology has advanced to a state where combined with data analytics, there are opportunities to be more proactive and take some of the mystery out of forklift service.”
Proactive, connected maintenance increases uptime
Rush says that fleet managers struggle with the unpredictable nature of service and maintenance costs. It can be challenging for them to predict, prepare for and budget unforeseen maintenance issues. Fortunately, telematics systems and monitoring devices are available today that can help enable a more proactive approach that brings a level of predictability to service timing and requirements.
“Telematics users can do this by collecting a wealth of data on the health, performance and status of connected forklifts and batteries. Data analytics are then used to unlock the potential of all this information, which includes everything from lift truck event codes and impact alerts to planned maintenance and unexpected disruptions, providing a holistic insight into the vehicle’s overall health. The goal is to better understand truck health and proactively schedule service support to maintain equipment uptime.
“Lift truck health can be defined by the time a vehicle’s electronics function optimally without generating a significant event code. It considers the elapsed time between the initial detection of a significant event code and the point at which the event code is resolved. While event codes do not always equate to equipment downtime, the less healthy a lift truck may be, the more likely downtime will occur. Lift truck health also considers the time the truck is unavailable to be used and/or not communicating with the telematics system.”
Rush adds that shorter time durations between each event and its resolution equates to a higher health rate and a healthier truck. He says that a healthier truck usually means less downtime and lower service and maintenance costs. Another significant determinant of truck health can be how long the service issue goes unnoticed or unreported, delaying the service call and its ultimate fix.
“For example, with a traditional reactive service approach, a forklift could develop a maintenance issue at 8am. It may not be documented, and service requested until the end of the nine-hour shift. If the tech arrives onsite that evening and is able to resolve the issue by midnight, the forklift was reported as unhealthy for 16 hours. This means the forklift was not performing at optimal levels.
“With connected maintenance, through remote monitoring and proactive dispatch, the service request for a connected lift truck is no longer dependent on when the lift truck operator or warehouse manager identifies and reports the issue. This time, when the maintenance issue appears at 8am, the forklift sends a request, enabling the service provider to alert the customer’s fleet manager so the dispatch of a service tech can be approved. The tech can arrive onsite and potentially resolve the issue that afternoon, reducing unhealthy hours by 50% or more.”
Five years of data makes the case
While the example above illustrates the potential benefit, a growing amount of data proves the return on investment of the approach.
“In many cases, customers with five years of connected maintenance data have compared lift truck health before and after connected maintenance was initiated and documented significant results. On average, results have revealed more than a 20% improvement in lift truck health and with it, an increase in the amount of time the forklift operates without generating an alert.
“Data has also indicated a significant reduction in event alerts when they are actively monitored. This is typically because alerts from monitored forklifts are reported more quickly and the corresponding issues are addressed. Users who monitor mean time to repair (MTTR) have also confirmed this improvement in response and resolution,” says Rush.
He says these results will only increase as connected maintenance continues to mature and machine learning and predictive maintenance are integrated into service and maintenance programs.
“In the meantime, telematics systems and data analytics enable fleet managers to bring greater predictability to forklift maintenance and enhance the performance and uptime of the fleet.”