Martin Engineering data tracking

Martin Engineering has introduced data tracking with QR codes on its conveyor belt cleaners and other components. The company says that customers benefit from regularly-scheduled inspections, providing operators with easy access to a wealth of data on the application, operating environment, service life and condition of conveyor components, updated on every belt cleaner maintenance visit. A Martin Engineering proprietary smart phone app gives technicians and customers a tool that helps maximise performance
Loading, Hauling & Excavation / February 5, 2018

636 Martin Engineering has introduced data tracking with QR codes on its conveyor belt cleaners and other components.

The company says that customers benefit from regularly-scheduled inspections, providing operators with easy access to a wealth of data on the application, operating environment, service life and condition of conveyor components, updated on every belt cleaner maintenance visit.

A Martin Engineering proprietary smart phone app gives technicians and customers a tool that helps maximise performance and service life, while minimising carryback and spillage, to improve safety and reduce unscheduled downtime. 

The system is currently being implemented in select markets around the world, with date codes imprinted on the blades during manufacture, while technicians also fix tags on existing equipment to begin monitoring condition and recording observations. Conceived as part of Martin Engineering’s factory-direct Mr Blade programme, technicians perform regularly scheduled inspections and adjustments, with an 18-point operational assessment from head pulley to tail pulley and a report for each visit. 

“Periodic reviews often reveal developing problems before they become a failure, such as worn idlers, leaking seals or excessive spillage,” says Chris Schmelzer, director of the Wear Components Business Group for Martin Engineering. 

“The data tracking programme will help us work with our customers to make better informed decisions about what equipment to use in specific applications, more accurately predicting the expected wear life.”

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