Quality & Quantity

, 42:795

Measuring the readability performance (RP) of aircraft maintenance technical orders by fuzzy MCDM method and RP index


DOI: 10.1007/s11135-006-9068-9

Cite this article as:
Hsia, TC., Chen, HT. & Chen, WH. Qual Quant (2008) 42: 795. doi:10.1007/s11135-006-9068-9


With the development of the global economy and the ease of air transportation, extra emphasis has been placed on flight safety. There are precise specifications and procedures in the operation and maintenance of aircraft. Human errors and mechanical disorders are two key factors of flight safety. The maintenance personnel need to follow an outlined procedure to avoid human errors and ensure flight safety. Readability of aircraft maintenance technical orders can affect the quality and reliability of aircraft maintenance. To ensure the editing quality of technical orders, controlling/monitoring the number of unreadable sentences is important and necessary. In this study, the number of unreadable sentences found in a technical order was used as the measure of readability performance (RP) as well as a readability performance index was provided to evaluate whether the RP of individual readability characteristics of technical orders was adequate. Different readability characteristics make different grade of RP loss. Based on fuzzy multiple criteria decision-making (Fuzzy MCDM) approaches, we investigated the expert opinions to rank and calculate the weights of all readability characteristics. At the same time, we proposed the upper limits of unreadable sentences according the weights of individual readability characteristics. In this paper, the technical orders issued by Taiwan Aerospace Industrial Development Corporation was used as an example to evaluate the readability of the technical orders and total RP losses for individual readability characteristics. Finally, an improved way of editing quality for technical orders was recommended.


Technical order Readability performance index Readability characteristics Fuzzy multiple criteria decision-making (Fuzzy MCDM) 

Copyright information

© Springer Science + Business Media B.V. 2008

Authors and Affiliations

  1. 1.Department of Industrial Engineering and ManagementChienkuo Technology UniversityChanghuaTaiwan, ROC
  2. 2.Department of Leisure Industry ManagementNational Chin-Yi University of TechnologyTaichungTaiwan, ROC
  3. 3.National Palace MuseumTaipeiTaiwan, ROC

Personalised recommendations