Design Method of Public Agricultural Residue Cleaning Machine Driven by Multi-factor Analysis and SOR Model Combination

GUO Zhiqiang, LIU Zengyu

Packaging Engineering ›› 2025, Vol. 46 ›› Issue (16) : 146-156.

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Packaging Engineering ›› 2025, Vol. 46 ›› Issue (16) : 146-156. DOI: 10.19554/j.cnki.1001-3563.2025.16.013
Industrial Design

Design Method of Public Agricultural Residue Cleaning Machine Driven by Multi-factor Analysis and SOR Model Combination

  • GUO Zhiqiang, LIU Zengyu*
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Abstract

In response to the call for building green rural areas, the work aims to design a public pesticide residue cleaning machine to protect agricultural workers from secondary pesticide exposure and ensure the sanitary safety of rural land. The research involved literature review and semi-structured offline interviews to identify the pain points of the product. The SETH-SOR model was used to summarize the requirements. The fuzzy Delphi method was employed to further refine the requirements. The effectiveness of the constructed theoretical model was validated using the Partial Least Square Structural Equation Model (PLS-SEM), and the priority of product requirements was ranked through path analysis and weight score calculation. Finally, the TRIZ theory was utilized to transform the requirements into actual structural functionalities, leading to an ideal solution. Innovative design of the public pesticide residue cleaning machine was based on the summarized invention principles. Building upon the SETH-SOR theory, the performance of the model is evaluated through PLS-SEM, and the TRIZ theory is applied to design and test the feasibility of the pesticide residue cleaning machine.

Key words

industrial design / SETH-SOR / partial least squares regression / structural equation modeling / pesticide residue cleaning machine / TRIZ / fuzzy Delphi method

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GUO Zhiqiang, LIU Zengyu. Design Method of Public Agricultural Residue Cleaning Machine Driven by Multi-factor Analysis and SOR Model Combination[J]. Packaging Engineering. 2025, 46(16): 146-156 https://doi.org/10.19554/j.cnki.1001-3563.2025.16.013

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