Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden Doors
To improve the production system for customized wooden doors and to gain research and development efficiency, this paper proposed the feasibility of using hierarchical clustering algorithms to cluster a company's customized wooden door products and its application to rational product family arc...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
North Carolina State University
2023-10-01
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| Series: | BioResources |
| Subjects: | |
| Online Access: | https://ojs.cnr.ncsu.edu/index.php/BRJ/article/view/22918 |
| _version_ | 1797660834257698816 |
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| author | Na Zhang Wei Xu Yong Tan |
| author_facet | Na Zhang Wei Xu Yong Tan |
| author_sort | Na Zhang |
| collection | DOAJ |
| description | To improve the production system for customized wooden doors and to gain research and development efficiency, this paper proposed the feasibility of using hierarchical clustering algorithms to cluster a company's customized wooden door products and its application to rational product family architecture. The particular use of multi-attribute feature data to locate products and the integration of image data into the database can make the original hierarchical clustering more compatible and adaptable for application to customized wooden doors. The preprocessed data was analyzed by clustering to obtain the clustering results and similarity relationships. Hierarchical clustering results were uneven and not entirely interpreted. However, the internal order structure of clusters and the clustering process could be clearly observed, and the distance hierarchical relationship between the products could be obtained, which was beneficial to the division of the product architecture. The results illustrated that processing using hierarchical clustering of multi-attribute data is feasible for optimizing customized wooden door product systems. In addition, the product architecture, product coding rules, and front-end development process were established to improve standardization and research and development efficiency. There is still great potential for developing the custom wooden door category in custom furniture companies. |
| first_indexed | 2024-03-11T18:36:36Z |
| format | Article |
| id | doaj.art-2341440cb4e34944ad732a7f4fa495a8 |
| institution | Directory Open Access Journal |
| issn | 1930-2126 |
| language | English |
| last_indexed | 2024-03-11T18:36:36Z |
| publishDate | 2023-10-01 |
| publisher | North Carolina State University |
| record_format | Article |
| series | BioResources |
| spelling | doaj.art-2341440cb4e34944ad732a7f4fa495a82023-10-12T19:28:33ZengNorth Carolina State UniversityBioResources1930-21262023-10-01184788979041001Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden DoorsNa Zhang0Wei Xu1Yong Tan2College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, ChinaDepartment of Product Research and Development, ZBOM Home Collection Co., Ltd., Hefei 230001, ChinaTo improve the production system for customized wooden doors and to gain research and development efficiency, this paper proposed the feasibility of using hierarchical clustering algorithms to cluster a company's customized wooden door products and its application to rational product family architecture. The particular use of multi-attribute feature data to locate products and the integration of image data into the database can make the original hierarchical clustering more compatible and adaptable for application to customized wooden doors. The preprocessed data was analyzed by clustering to obtain the clustering results and similarity relationships. Hierarchical clustering results were uneven and not entirely interpreted. However, the internal order structure of clusters and the clustering process could be clearly observed, and the distance hierarchical relationship between the products could be obtained, which was beneficial to the division of the product architecture. The results illustrated that processing using hierarchical clustering of multi-attribute data is feasible for optimizing customized wooden door product systems. In addition, the product architecture, product coding rules, and front-end development process were established to improve standardization and research and development efficiency. There is still great potential for developing the custom wooden door category in custom furniture companies.https://ojs.cnr.ncsu.edu/index.php/BRJ/article/view/22918customized furnitureproduct system optimizationmachine learningresearch and development |
| spellingShingle | Na Zhang Wei Xu Yong Tan Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden Doors BioResources customized furniture product system optimization machine learning research and development |
| title | Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden Doors |
| title_full | Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden Doors |
| title_fullStr | Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden Doors |
| title_full_unstemmed | Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden Doors |
| title_short | Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden Doors |
| title_sort | multi attribute hierarchical clustering for product family division of customized wooden doors |
| topic | customized furniture product system optimization machine learning research and development |
| url | https://ojs.cnr.ncsu.edu/index.php/BRJ/article/view/22918 |
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