Abstract
Among textile manufacturing industries, garment manufacturing produces products with the highest added value. Because certain standards and specifications must be followed in large-scale production, each country must have its own standard-sizing systems for manufacturers to follow. Data mining is used in many fields but there is a lack of research on sizing systems in garment manufacturing. This study aims to establish such sizing systems using a decision tree-based data mining approach. When sizing systems are established using the innovative technology, three advantages can be seen: resulting in fewer size groups with high coverage; generating regular patterns and rules; providing manufacturers with reference points to facilitate manufacturing. As a result, production planning can be made more realistic and inventory costs due to mismatches can be minimised. The innovative technology is found to be effective in processing classification problems for promoting production planning and management.
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