FEATURE Packaging


EFFECTIVE DATA-DRIVEN MAINTENANCE


Data-driven insights can help optimise the performance, maintenance and sustainability of warehouse automation. Dan Migliozzi, Sales & Marketing Director, Invar Group, explains how to achieve the best results


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urrent materials handling and intralogistics equipment is amazingly reliable. Nonetheless, there is a lot to go wrong – all


those mechanical parts like rollers, bearings, motors, belts, plus switches, sensors and the rest of the electronics. For many businesses this equipment is fundamental – if it’s  Unexpected failures, and unplanned maintenance and repair, don’t just increase   and sustainability impacts. But by  strategies these cost, performance, and  reduced.


Some companies, particularly those with limited in-house capabilities, work on an  appear to reduce unnecessary downtime  a well-known law that states if something can fail, it will, and at the worst possible moment. A more sophisticated approach is that of planned, scheduled maintenance. Components subject to wear, or otherwise likely to fail, are replaced at  the equipment manufacturer, or based  





construct – some will fail early; others may be good for much longer. Maintenance  rather than the amount and nature of the usage the equipment has experienced –  will be replaced whether they need it or not. Perfectly good parts are sent for scrap. Meanwhile, the performance of other components may be degrading,   on the condition or life of other system components, while increasing the consumption of energy, lubricants and other consumables. None of this is good for sustainability.


 arbitrary. Most materials handling


18 December 2024/January 2025 | Automation


automation gathers a plethora of condition monitoring and other data that can be used  – key parameters, perhaps the energy consumption of motors, or the temperature of bearings, can be monitored, and generate alerts and warnings before the worst happens.





reacting to warnings that an element is, or is about to go, out of its performance    We can bring together both historical


and real-time data, from SCADA and other systems, to identify failure areas  regular wear-and-tear, mean times between failures, and downtimes required to take action. We can use data on actual loadings and usage, rather than elapsed times, to predict which components are likely to require replacement and when – and which identical components should still   software tools capable of analysing this data, to inform our decisions on the most appropriate, proportionate actions to take. Further, software empowers learning,   new equipment, or appropriate upgrades  operator training, may be needed.  equipment can operate longer at maximum capacity, and reduce those minor jams and other incidents, while necessary downtime can be optimised to suit patterns of work.  (internal or external), to anticipate the  necessary spare and replacement parts so that maintenance downtime is not wasted.  most critical resource – planning where and  their training needs are.





waste reduction goals by reducing the unnecessary use of costly (in economic 


 reconditioned rather than scrapped. 


 automation, thus reducing consumption of energy and consumables – a badly worn  much energy as one in good condition.  materials and their contents, damaged by underperforming or failed equipment, is reduced. Automation also reduces or eliminates the use of more polluting forms of equipment such as lift trucks. Automation can mitigate or eliminate many of the Health & Safety risks associated with warehouse operations, such as lifting. Equipment that is well maintained so as to stay within its designed   lifecycle impacts of parts and materials  sustainable procurement policies. And whilst the physical maintenance  machine monitoring means the need to stop the line for inspection and assessment is largely eliminated. Ironically, disassembly of equipment for inspection is itself a recognised cause of failure!


Invar Group www.invargroup.com


automationmagazine.co.uk


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