Integrated Component Reliability Modeling for Helicopter Service Industry
Garret S Lamson1, Shailendra K Gaikwad2 and Jim Lee2*
1Engineering Management Program, University of Louisiana at Lafayette, USA
2Systems Engineering Program, University of Louisiana at Lafayette, USA
- *Corresponding Author:
- Dr. Jim Lee
Systems Engineering Program
University of Louisiana at Lafayette, USA
E-mail: [email protected]
Received Date: June 20, 2016; Accepted Date: July 07, 2016; Published Date: July 14, 2016
Citation: Lamson GS, Gaikwad SK, Lee J (2016) Integrated Component Reliability Modeling for Helicopter Service Industry. Ind Eng Manage 5:196. doi: 10.4172/2169-0316.1000196
Copyright: © 2016 Lamson GS, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
A helicopter service industry is concerned with component reliability, as poor component reliability jeopardizes the safe operation of aircraft. Currently the maintenance process used for component overhauls and replacements is typically based on the maximum intervals called Hard Time (HT) limits recommended by manufacturer without using the real-world reliability data. In this case study, an integrated component reliability modeling procedure using is proposed to identify proper component overhaul and replacement intervals for a leading helicopter service industry. This procedure considers analysis methods including removal rate analysis, mean time between failure (MTBF) analysis, average life analysis, data distribution analysis, and total quality management (TQM) shop survey which can be used as a framework to support reliability programs in the helicopter industry, working as a decision-support tool for the modification of manufacturer’s recommended intervals. An illustrative example is provided to show the use of this modeling procedure. Future work could be done to correlate inventory analysis using component reliability modeling leading to total productive maintenance.