REVIEW ARTICLE


Evaluation Method and Application of Machine Design Scheme Based on Information Content Measurement Model



Qin Yang*, 1, Yuanyuan Che2
1 School of Mechanical Engineering & Automation, University of Science and Technology Liaoning, Anshan, Liaoning 114051, China
2 Computering Center of Anshan Normal University Liaoning China, Anshan, Liaoning 114051, China


© 2015 Yang and Che

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the School of Mechanical Engineering & Automation, University of Science and Technology Liaoning, Anshan, Liaoning, 114051, Anshan, China; Tel/Fax: 15942252210; E-mail: id_yangqin@126.com


Abstract

While designing a machine, special design requirements are influenced by various restraint factors in practice. The evaluation of its scheme usually features multi-levels, multi-attributes and a mixed type of both qualitative and quantitative indices. Therefore, this paper focused on the evaluation of the machine design scheme and provided an evaluation method of the machine design scheme based on information content measurement model. This model firstly performed an analysis of all the factors that influence the design application and brought about an evaluation index system on the basis of information independence. Secondly, the model obtained the entire information content of the scheme by establishing information content calculating models of multi-level evaluation indices, and achieved the optimization analysis of machine design scheme on the basis of different amount of information content. Finally, the paper examined the effectiveness of the model with the application example.

Keywords: Design scheme, machine, information content, model, multiple attribute decision making.