Reachstacker reliability from sensor, event and service data
In 14 days on ten machines: reachstackers with service windows over about 350 hours were 2–5× more likely to have an oil leak per 1,000 hours, and high transmission-oil temperature traced to debris on the radiator.
Challenge
A port-equipment maker wanted to improve the reliability of a fleet of 10,000 reachstackers worldwide through proactive maintenance. The question was whether sensor and usage data together with design specifications could show when a machine is being operated at higher risk of unavailability.
Solution
In a 14-day project on ten machines across UK customers, Arundo reviewed 25 million lines of event, machine and service-order data, used keyword grouping of service orders to find the frequent events worth analysing, related leak-related service calls to the interval between planned services, and built a KPI on time spent at high transmission-oil temperature.
Impact
Reachstackers with service windows longer than about 350 engine hours were on average 2–5× more likely to have an oil-leak event per 1,000 hours; the longer a transmission runs hot, the more error codes it throws; the cause of hot running was identified as debris clogging the transmission radiator. Recommended next step: KPI-based fleet monitoring with debris-cleaning recommendations before the error codes occur.