Research on assist design strategy of electric garden tools driven by data and intelligence

Abstract

This study proposes an artificial intelligence (AI) assited design strategy for electric gardening tools, focusing on direct interaction between workers and tools. Using electric pruning shears as a case study, the research first identifies the actual needs of gardening workers through on-site interviews. By applying the KANO model and Fuzzy Analytic Hierarchy Process (FAHP), the critical requirements of gardening workers are precisely determined. Subsequently, generative AI is utilized to generate design solutions based on these identified needs. Designers draw inspiration from AI-generated solutions and assess and score them separately, comparing trained and untrained ones based on the KANO-FAHP model. Significantly improved evaluation scores are observed for the trained solutions. The KANO-FAHP-AI design approach proposed in this study presents a novel pathway for designing electric gardening tools.