Reuse-oriented common structure discovery in assembly models

Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed t...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wang, Pan [verfasserIn] Zhang, Jie Li, Yuan Yu, Jianfeng

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Design reuse Common structure Assembly model Graph descriptor Frequent subgraph mining

Anmerkung:	© The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017

Übergeordnetes Werk:	Enthalten in: Journal of mechanical science and technology - Berlin : Springer, 2005, 31(2017), 1 vom: Jan., Seite 297-307
Übergeordnetes Werk:	volume:31 ; year:2017 ; number:1 ; month:01 ; pages:297-307

Links:	Volltext

DOI / URN:	10.1007/s12206-016-1232-0

Katalog-ID:	SPR025327488

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520			\|a Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach.
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912			\|a GBV_ILN_602
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matchkey_str	article:19763824:2017----::esoinecmosrcueicvri
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publishDate	2017
allfields	10.1007/s12206-016-1232-0 doi (DE-627)SPR025327488 (SPR)s12206-016-1232-0-e DE-627 ger DE-627 rakwb eng Wang, Pan verfasserin aut Reuse-oriented common structure discovery in assembly models 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach. Design reuse (dpeaa)DE-He213 Common structure (dpeaa)DE-He213 Assembly model (dpeaa)DE-He213 Graph descriptor (dpeaa)DE-He213 Frequent subgraph mining (dpeaa)DE-He213 Zhang, Jie aut Li, Yuan aut Yu, Jianfeng aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 31(2017), 1 vom: Jan., Seite 297-307 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:31 year:2017 number:1 month:01 pages:297-307 https://dx.doi.org/10.1007/s12206-016-1232-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2017 1 01 297-307
spelling	10.1007/s12206-016-1232-0 doi (DE-627)SPR025327488 (SPR)s12206-016-1232-0-e DE-627 ger DE-627 rakwb eng Wang, Pan verfasserin aut Reuse-oriented common structure discovery in assembly models 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach. Design reuse (dpeaa)DE-He213 Common structure (dpeaa)DE-He213 Assembly model (dpeaa)DE-He213 Graph descriptor (dpeaa)DE-He213 Frequent subgraph mining (dpeaa)DE-He213 Zhang, Jie aut Li, Yuan aut Yu, Jianfeng aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 31(2017), 1 vom: Jan., Seite 297-307 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:31 year:2017 number:1 month:01 pages:297-307 https://dx.doi.org/10.1007/s12206-016-1232-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2017 1 01 297-307
allfields_unstemmed	10.1007/s12206-016-1232-0 doi (DE-627)SPR025327488 (SPR)s12206-016-1232-0-e DE-627 ger DE-627 rakwb eng Wang, Pan verfasserin aut Reuse-oriented common structure discovery in assembly models 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach. Design reuse (dpeaa)DE-He213 Common structure (dpeaa)DE-He213 Assembly model (dpeaa)DE-He213 Graph descriptor (dpeaa)DE-He213 Frequent subgraph mining (dpeaa)DE-He213 Zhang, Jie aut Li, Yuan aut Yu, Jianfeng aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 31(2017), 1 vom: Jan., Seite 297-307 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:31 year:2017 number:1 month:01 pages:297-307 https://dx.doi.org/10.1007/s12206-016-1232-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2017 1 01 297-307
allfieldsGer	10.1007/s12206-016-1232-0 doi (DE-627)SPR025327488 (SPR)s12206-016-1232-0-e DE-627 ger DE-627 rakwb eng Wang, Pan verfasserin aut Reuse-oriented common structure discovery in assembly models 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach. Design reuse (dpeaa)DE-He213 Common structure (dpeaa)DE-He213 Assembly model (dpeaa)DE-He213 Graph descriptor (dpeaa)DE-He213 Frequent subgraph mining (dpeaa)DE-He213 Zhang, Jie aut Li, Yuan aut Yu, Jianfeng aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 31(2017), 1 vom: Jan., Seite 297-307 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:31 year:2017 number:1 month:01 pages:297-307 https://dx.doi.org/10.1007/s12206-016-1232-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2017 1 01 297-307
allfieldsSound	10.1007/s12206-016-1232-0 doi (DE-627)SPR025327488 (SPR)s12206-016-1232-0-e DE-627 ger DE-627 rakwb eng Wang, Pan verfasserin aut Reuse-oriented common structure discovery in assembly models 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach. Design reuse (dpeaa)DE-He213 Common structure (dpeaa)DE-He213 Assembly model (dpeaa)DE-He213 Graph descriptor (dpeaa)DE-He213 Frequent subgraph mining (dpeaa)DE-He213 Zhang, Jie aut Li, Yuan aut Yu, Jianfeng aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 31(2017), 1 vom: Jan., Seite 297-307 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:31 year:2017 number:1 month:01 pages:297-307 https://dx.doi.org/10.1007/s12206-016-1232-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2017 1 01 297-307
language	English
source	Enthalten in Journal of mechanical science and technology 31(2017), 1 vom: Jan., Seite 297-307 volume:31 year:2017 number:1 month:01 pages:297-307
sourceStr	Enthalten in Journal of mechanical science and technology 31(2017), 1 vom: Jan., Seite 297-307 volume:31 year:2017 number:1 month:01 pages:297-307
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Design reuse Common structure Assembly model Graph descriptor Frequent subgraph mining
isfreeaccess_bool	false
container_title	Journal of mechanical science and technology
authorswithroles_txt_mv	Wang, Pan @@aut@@ Zhang, Jie @@aut@@ Li, Yuan @@aut@@ Yu, Jianfeng @@aut@@
publishDateDaySort_date	2017-01-01T00:00:00Z
hierarchy_top_id	58714016X
id	SPR025327488
language_de	englisch
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author	Wang, Pan
spellingShingle	Wang, Pan misc Design reuse misc Common structure misc Assembly model misc Graph descriptor misc Frequent subgraph mining Reuse-oriented common structure discovery in assembly models
authorStr	Wang, Pan
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topic_title	Reuse-oriented common structure discovery in assembly models Design reuse (dpeaa)DE-He213 Common structure (dpeaa)DE-He213 Assembly model (dpeaa)DE-He213 Graph descriptor (dpeaa)DE-He213 Frequent subgraph mining (dpeaa)DE-He213
topic	misc Design reuse misc Common structure misc Assembly model misc Graph descriptor misc Frequent subgraph mining
topic_unstemmed	misc Design reuse misc Common structure misc Assembly model misc Graph descriptor misc Frequent subgraph mining
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title	Reuse-oriented common structure discovery in assembly models
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title_full	Reuse-oriented common structure discovery in assembly models
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author_browse	Wang, Pan Zhang, Jie Li, Yuan Yu, Jianfeng
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doi_str_mv	10.1007/s12206-016-1232-0
title_sort	reuse-oriented common structure discovery in assembly models
title_auth	Reuse-oriented common structure discovery in assembly models
abstract	Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach. © The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017
abstractGer	Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach. © The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017
abstract_unstemmed	Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach. © The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017
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title_short	Reuse-oriented common structure discovery in assembly models
url	https://dx.doi.org/10.1007/s12206-016-1232-0
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doi_str	10.1007/s12206-016-1232-0
up_date	2024-07-03T15:18:37.829Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR025327488</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230403065554.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2017 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12206-016-1232-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR025327488</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12206-016-1232-0-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wang, Pan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Reuse-oriented common structure discovery in assembly models</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Design reuse</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Common structure</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Assembly model</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Graph descriptor</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Frequent subgraph mining</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Jie</subfield><subfield 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