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The feasibility-of-objectives (FOO) technique has become the current standard for assessing reliability designs for military mechanical\u2013electrical systems. However, the FOO method has several drawbacks: For instance, it requires that the value of reliability allocation factors is single linguistic variables, and it does not consider the ordered weight of reliability allocation factors, but simply multiplies the ISPE (Complexity (I), State of Art (S), Performance Time (P), and Environment (E)) values one by one. This can lead to erroneous results. To address these issues, this paper combines the fuzzy allocation method with the maximum entropy ordered weighted averaging method (ME-OWA) to achieve a flexible allocation of system reliability. To verify the effectiveness of the proposed method, the CNC machine tool is taken as an example. The FOO method and the fuzzy allocation method and the proposed method were used to assign reliability to the eight subsystems of a CNC machine tool, and the results were compared to draw conclusions: The proposed method is more flexible and accurate for reliability allocation.<\/jats:p>","DOI":"10.3233\/jifs-190376","type":"journal-article","created":{"date-parts":[[2019,8,20]],"date-time":"2019-08-20T10:53:43Z","timestamp":1566298423000},"page":"7991-8004","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":11,"title":["Reliability allocation method based on maximum entropy ordered weighted average and hesitant fuzzy Linguistic term set"],"prefix":"10.1177","volume":"37","author":[{"given":"Qiang","family":"Cheng","sequence":"first","affiliation":[{"name":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"},{"name":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, China"}]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"},{"name":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, China"}]},{"given":"Zhifeng","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"},{"name":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, China"}]},{"given":"Caixia","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"},{"name":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, China"}]},{"given":"Dongyang","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"},{"name":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, China"}]},{"given":"Baobao","family":"Qi","sequence":"additional","affiliation":[{"name":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"},{"name":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, China"}]}],"member":"179","published-online":{"date-parts":[[2019,8,17]]},"reference":[{"key":"e_1_3_2_2_2","volume-title":"Office of the Assistant Secretary of Defense Research and Engineering","author":"Advisory. 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