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Book synopsis

Aircraft structural maintenance is one of the critical operational tasks to sustain continued airworthiness. It also contributes a significant proportion of the total life-cycle cost. Reliability Based Aircraft Maintenance Optimization and Applications presents flexible and cost-effective maintenance schedule for aircraft structures particular in composite airframes. By applying an intelligent rating system, the back-propagation network (BPN) method, and FTA technique, a new approach was created with a powerful learning ability and a flexible data fusion capability, to assist in determining inspection intervals for new aircraft structures, especially in composite structure. This book also discusses the influence of Structure Health Monitoring (SHM) on scheduled maintenance. An integrated logic diagram was established incorporating SHM into the current MSG-3 structural analysis, based on which four maintenance scenarios with gradual increasing maturity levels of SHM were analyzed. The inspection intervals and the repair thresholds are adjusted according to different combinations of SHM tasks and scheduled maintenance. This book provides a practical means for aircraft manufacturers and operators to consider the feasibility of SHM by examining labor work reduction, structural reliability variation as well as maintenance cost savings. The first book available on airframe maintenance optimization Presents the most advanced methods and technologies of maintenance engineering analysis, including first application of composite structure maintenance engineering analysis integrated with SHM Provides the latest research results of composite structure maintenance and health monitoring system

Book details

Book category Books in English Economics, finance, business & management Industry & industrial studies Manufacturing industries

• Full title: Reliability Based Aircraft Maintenance Optimization and Applications
• Author: He Ren, Xi Chen
• Language: English
• Binding: Paperback
• Number of pages: 260
• EAN: 9780128126684
• ISBN: 012812668X
• ID: 14564695
• Publisher: Elsevier Science Publishing Co Inc
• Weight: 412 g
• Dimensions: 154 × 228 × 15 mm
• Date of publishing: 24. March 2017

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