Fuzzy cluster analysis of solid wood parts of children's furniture

Yuechun Yang; Yi Ren; Zhongfeng Zhang

doi:10.1117/12.2640696

24 October 2022 Fuzzy cluster analysis of solid wood parts of children's furniture

Yuechun Yang, Yi Ren, Zhongfeng Zhang

Proceedings Volume 12289, International Conference on Intelligent Manufacturing and Industrial Automation (CIMIA 2022); 1228908 (2022) https://doi.org/10.1117/12.2640696
Event: International Conference on Intelligent Manufacturing and Industrial Automation (CIMIA 2022), 2022, Kunming, China

Abstract

To improve the production efficiency of children's furniture enterprises, the fuzzy cluster analysis method is used to classify the solid wood parts into groups according to the similarity of processing technology in children's furniture, thereby shortening the production cycle. This paper takes solid wood children's furniture as the research object, selects 3 pieces of solid wood children's furniture with different functions as samples, and divides them into 113 pieces and 50 kinds of solid wood parts. According to the processing technology of the parts, the part-process binary association matrix of solid wood parts is constructed. By establishing the fuzzy similarity matrix and the fuzzy equivalent matrix and solving them, the threshold λ and the corresponding number of parts groups are obtained. Children's furniture enterprises can select different thresholds λ based on the results of fuzzy cluster analysis, combined with actual production conditions and needs, and obtain suitable parts grouping production methods. On the basis of this, it can establish a corresponding production unit, reduce the ineffective transportation of parts between processing machines, grow large quantities of production and improve production efficiency.

Citation Download Citation

Yuechun Yang, Yi Ren, and Zhongfeng Zhang "Fuzzy cluster analysis of solid wood parts of children's furniture", Proc. SPIE 12289, International Conference on Intelligent Manufacturing and Industrial Automation (CIMIA 2022), 1228908 (24 October 2022); https://doi.org/10.1117/12.2640696

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KEYWORDS

Solids

Fuzzy logic

Analytical research

Binary data

Manufacturing

Statistical analysis

Sustainable technology

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