| This paper studies the multi-attribute evaluation of surface defects during the transportation of panels,which is helpful for enterprises to classify their surface quality accurately and determine the main defects,so as to optimize the logistics service process,and help to improve the logistics service quality continuously.It has important practical significance.In this paper,covering parts are taken as evaluation objects,and multiple surface defects generated during transportation are taken as evaluation attributes.Decision makers give hesitant fuzzy numbers to realize the transformation from qualitative evaluation to quantitative evaluation.Based on the hesitant fuzzy theory and the hesitant fuzzy multiattribute evaluation method,a multi-attribute fuzzy evaluation model for surface defects of panel is established by taking the comprehensive score of surface defects of single panel as the objective function and combining with the surface quality grading function.On the basis of the subjective weighting method of eigenvector,the optimal subjective weight is determined by genetic algorithm;on the basis of the traditional deviation maximization method,a new hesitant fuzzy deviation maximization method is proposed to determine the objective weight;on the basis of the two methods,the overall algorithm of surface defect fuzzy evaluation is designed and solved by using MATLAB mathematical analysis software,and each of them is obtained.The comprehensive score value and surface quality grade of the evaluation object.The validity,adaptability and superiority of the model and its algorithm are verified by the calculation and analysis of a practical case.The multi-attribute evaluation model and algorithm for surface defects of automobile panels for transportation cargo damage analysis are proposed in this paper,which can provide a model and algorithm reference for automobile enterprises to evaluate the quality grade of surface defects of automobile panels and screen the main defects.At the same time,it has a certain reference significance for multi-attribute evaluation of surface quality of similar products. |
