
南京航空航天大学 机电学院,江苏,南京,210016
Online First:10 March 2021,
Published:2021
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王体春, 华洋, 秦家祺. 基于可拓本体蕴含系的产品方案可拓设计模型[J]. 广东工业大学学报, 2021, 38(2): 1-9.
Wang Ti-chun, Hua Yang, Qin Jia-qi. An Extension Scheme Design Model of Complex Product Based on Extension Ontology Implication System[J]. 2021, 38(2): 1-9.
王体春, 华洋, 秦家祺. 基于可拓本体蕴含系的产品方案可拓设计模型[J]. 广东工业大学学报, 2021, 38(2): 1-9. DOI: 10.12052/gdutxb.200086.
Wang Ti-chun, Hua Yang, Qin Jia-qi. An Extension Scheme Design Model of Complex Product Based on Extension Ontology Implication System[J]. 2021, 38(2): 1-9. DOI: 10.12052/gdutxb.200086.
蕴含关系是影响复杂产品方案快速配置设计的重要因素。为了有效提升复杂产品方案可拓配置设计的能力
针对复杂产品方案设计过程中蕴含信息的有效表达、挖掘、推理和重用等进行了研究。对大型复杂产品方案可拓设计过程中的可拓本体概念模型、可拓本体蕴含系的信息量计算模型、基于可拓本体蕴含系的设计蕴含关系挖掘模型、基于可拓本体蕴含系的可拓重用度计算模型等进行了分析
提出了一种基于可拓本体蕴含系的复杂产品可拓设计模式
并给出了相应模型与算法的实现步骤和框架。通过具体的设计实例对文中的模型和算法进行了说明和验证分析
结果验证了模型和算法的有效性和可行性
从而为复杂产品方案可拓设计的顺利实施提供理论和工程应用支持。
Implication relationships are important factors affecting the rapid configuration design of complex product schemes. Aiming at improving the ability of extension configuration design of complex product schemes
the effective expression
mining
reasoning and reuse of information contained in the process of complex product scheme design were researched. The concept model of extension ontology
the information calculation model of implication system
the implication relationship mining model and the extension reuse calculation model based on extension ontology implication system in the process of extension design of large complex product schemes were analyzed. A complex product extension design model based on extension ontology implication system was proposed
and the implementation steps and framework of the corresponding model and algorithm were put forward. The model and algorithm were illustrated and validated by a specific design example. The results indicate that the model and algorithm are effective and feasible
which provides a theoretical and engineering support for the smooth implementation of extension design of complex product schemes.
ZHANG S Y, XU J H, GOU H W, et al . A research review on the key technologies of intelligent design for customized products [J ] . Engineering, 2017(5): 631-640.
YANG D, CHAI H M. Research on green product design selection based on QFD and case based reasoning [J]. Science and Technology Management Research, 2018, 38(16): 251-259.
MA H Z, CHU X N, XUE D Y, et al . A systematic decision making approach for product conceptual design based on fuzzy morphological matrix [J ] . Expert Systems with Applications, 2017, 81: 444-456.
YANG T, YANG Y, ZHANG D D. Generation of product innovation conceptual design schemes for considering the demand preferences of customers [J]. Computer Integrated Manufacturing Systems, 2015, 21(4): 875-884.
JIANG J, DING G F, ZHANG J, et al . A systematic optimization design method for complex mechatronic products design and development [J ] . Mathematical Problems in Engineering, 2018(2): 1-14.
ZHANG L, ZHANG S Y, LIU X J, et al . Reconstruction technology of configuration design for complex product based on expanded GRA and weighted sequence cross [J ] . Computer Integrated Manufacturing Systems, 2015, 21(10): 2564-2576.
NI J T, WANG Z G, LIAN X Z, et al . Optimization method of product design schemes based on preference information [J ] . Computer Integrated Manufacturing Systems, 2019, 25(5): 1238-1247.
GRUH IER E, DEMOLY F, DUTARTRE O, et al . A formal ontology-based spatiotemporal mereotopology for integrated product design and assembly sequence planning [J ] . Advanced Engineering Informatics, 2015, 29(3): 495-512.
WEN J F, GUO W, SHAO H Y. Case retrieve methodology based on domain ontology and case-based reasoning [J]. Computer Integrated Manufacturing Systems, 2017, 23(7): 1377-1385.
EMILIO M S, FAROUK B, ALAIN B. Ontology-based knowledge representation for additive manufacturing [J]. Computers in Industry, 2019, 109: 182-194.
CHEN Y, ZHAO M, XIE Y B, et al . A new model of conceptual design based on Scientific Ontology and intentionality theory-Part I [J ] . The Conceptual Foundation Design Studies, 2015, 37: 12-36.
CHEN Y, ZHAO M, XIE Y B, et al . A new model of conceptual design based on scientific ontology and intentionality theory—art II: the process model [J ] . Design Studies, 2015, 38: 139-160.
CHANG D N, CHEN C H. Product concept evaluation and selection using data mining and domain ontology in a crowdsourcing environment [J]. Advanced Engineering Informatics, 2015, 29(4): 759-774.
ZHAO Y W, ZHOU J Q, HONG H H, et al . Overview and prospects of extension design methodology [J ] . Computer Integrated Manufacturing Systems, 2015, 21(5): 1158-1167.
CAI W, YANG C Y. Basic theory and methodology on Extenics [J]. Chin Sci Bull, 2013, 58(13): 1190-1199.
REN J Z. Technology selection for ballast water treatment by multi-stakeholders: a multi-attribute decision analysis approach based on the combined weights and extension theory [J]. Chemosphere, 2018, 191: 747-760.
YANG G W, ZHU R C, ZHANG X F, et al . Definition of extension ontology and its properties [J ] . Mathematics in Practice and Theory, 2015, 45(13): 215-225.
WEN S Y, LI W H. Application of in the ontology knowledge expansion analysis tree extension strategy generation system [J]. CAAI Transactions on Intelligent Systems, 2014, 9(1): 1158-1167.
杨春燕. 可拓创新方法[M]. 北京: 科学出版社, 2017.
YANG C Y. Extension Innovation Method[M]. New York: CRC Press, 2019.
LI Z H, YANG C Y, LI W J. An application of extension innovation method in generator innovation design [J]. Journal of Guangdong University of Technology, 2020, 37(1): 1-6.
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