چکیده مقاله
The automotive sector is progressively adopting error proofing techniques to uphold stringent production standards, particularly in the fabrication of LED boards utilized in automotive lighting systems This study explores the application of Artificial Intelligence AI to refine the Poka Yoke mistake proofing methodology in the manufacturing process of LED boards By integrating MATLAB and Python, we present an advanced framework that leverages AI for defect detection during both the production and testing stages This innovative system enhances the accuracy of error detection, significantly elevates product quality, and minimizes costs related to manufacturing defects The research demonstrates that the proposed AI driven approach can effectively ensure the consistent delivery of high quality LED boards, thus reinforcing the safety and reliability of automotive lighting systems Additionally, the incorporation of AI in error proofing processes offers the potential for scaling production while maintaining high standards, ultimately fostering greater efficiency and reducing the likelihood of defects in automotive lighting components
کلیدواژهها
نویسندگان
Ayddin Doroudi
PhD Candidate, Polymer and Color Engineering Department, Amirkabir University of Technology
Ebrahim Abbasi Karandagh
Expert in Car Light System Engineering, Ext & Int Trimming parts Localization & Eng Design Affairs, Supplying Automotive Parts Co SAPCO
Malek Alizadeh Bakdilo
Engineering Design Manager, Ext & Int Trimming parts Localization & Eng Design Affairs, Supplying Automotive Parts Co SAPCO
شیوه ارجاع
Doroudi, Ayddin and Abbasi Karandagh, Ebrahim and Alizadeh Bakdilo, Malek,1403,Application of Artificial Intelligence for Poka-Yoke in the Process and Manufacturing of LED Boards in Car Lights: A MATLAB and Python Integration Approach,The10th International and 21th National Conference on Manufacturing Engineering,Tehran
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