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Optimisation of a component replacement policy at KLM E&M using Predictive Maintenance

Hof, Irene van den (2019) Optimisation of a component replacement policy at KLM E&M using Predictive Maintenance.

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Abstract:This study is an attempt to support KLM Engineering & Maintenance with the construction of a business case for a new data-driven maintenance application called 'Prognos'. Prognos is developed to improve MRO operations with Predictive Maintenance. Predictive component replacement policies, designed to reduce repair and spare part cost, were tested in a discrete-event simulation model. A case study for a particular system showed that inventory levels could be reduced with 20% and the average total cost with 30%.
Item Type:Essay (Master)
Clients:
KLM, Amsterdam, Nederland
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:50 technical science in general
Programme:Industrial Engineering and Management MSc (60029)
Link to this item:http://purl.utwente.nl/essays/77909
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