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Mass customization is the direction of China's solid wood furniture companies in the future. Group technology can solve the problems of multiple categories and small batches brought about by mass customization. The rational part division is the prerequisite for the application of group technology. This paper is based on fuzzy cluster analysis and BP neural network technology to study the clustering of solid wood furniture parts into groups. The case analysis conducted experiments with 164 parts of solid wood furniture from a company, and the results showed that 2-8 part families are better GT solutions. After 8 iterations, the error of the BP neural network is reduced to less than 1*10-6, the parts participating in the test are accurately grouped, and the neural network meets the requirements of actual use. The case verifies the method proposed in this article, and the results show that this method is a method of grouping parts suitable for the production of solid wood furniture, which can help solid wood furniture companies cope with mass customization production.
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