scholarly journals Study on Hesitant Fuzzy Multiattribute Quality Evaluation Based on Surface Defect Information of Autobody Panels

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Jia Mao ◽  
Qi Sun ◽  
Kun Gui

Surface defects of autobody panels have the greatest impact on the surface quality of the automobile body, but many enterprises lack a scientific and reasonable evaluation method of surface quality, relying solely on the subjective judgment of decision makers which will lead to an increase in the probability of misjudgment. In this paper, the subjective weight is determined by the genetic algorithm based on optimization, and the objective weight is determined by the improved deviation maximization method. Combining the hesitant fuzzy set theory, the hesitant fuzzy mixed weighted arithmetic average operator (HFHWA), and the score function, the surface defect information of the panel is quantified. On this basis, a complete set of hesitant fuzzy multiattribute evaluation model of surface defect information is proposed. Taking a batch of inner panels of the automobile door produced by A automobile enterprise as an example, five common defects including hidden pit, bump and scratch, rust, indentation pockmark, and ripple are selected as evaluation attributes to evaluate their surface quality, which verifies the validity and practicability of the model.

Algorithms ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 135 ◽  
Author(s):  
Jun Ye ◽  
Wenhua Cui

Linguistic decision making (DM) is an important research topic in DM theory and methods since using linguistic terms for the assessment of the objective world is very fitting for human thinking and expressing habits. However, there is both uncertainty and hesitancy in linguistic arguments in human thinking and judgments of an evaluated object. Nonetheless, the hybrid information regarding both uncertain linguistic arguments and hesitant linguistic arguments cannot be expressed through the various existing linguistic concepts. To reasonably express it, this study presents a linguistic cubic hesitant variable (LCHV) based on the concepts of a linguistic cubic variable and a hesitant fuzzy set, its operational relations, and its linguistic score function for ranking LCHVs. Then, the objective extension method based on the least common multiple number/cardinality for LCHVs and the weighted aggregation operators of LCHVs are proposed to reasonably aggregate LCHV information because existing aggregation operators cannot aggregate LCHVs in which the number of their hesitant components may imply difference. Next, a multi-attribute decision-making (MADM) approach is proposed based on the weighted arithmetic averaging (WAA) and weighted geometric averaging (WGA) operators of LCHVs. Lastly, an illustrative example is provided to indicate the applicability of the proposed approaches.


Materials ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 6768
Author(s):  
Namsu Park ◽  
Yeonghwan Song ◽  
Seon-Ho Jung ◽  
Junghan Song ◽  
Jongsup Lee ◽  
...  

The surface quality control of extruded products is a critical concern in the home appliance manufacturing industry owing to the increasing need for products with a high surface quality, in addition to the essential mechanical properties of the final product. The underlying issue with achieving high-quality extrusion products is that surface defects, especially those resulting in surface gloss differences, called white line defects, are only observed after surface treatment. In this study, we aim to investigate the cause of white line defect generation on the surface of an extruded product. Accordingly, an experimental extrusion program is established using an L-shaped die that has a noticeable change in its bearing length along the inner corner of its cross-sectional profile. Laboratory-scale experiments were performed for the L-shaped extrusion of homogenized Al 6063 alloy at various ram speeds, in order to induce surface defects, considering the production yield rate required for mass production. Subsequently, the microstructural changes near the surface failure region were investigated using an arbitrary Lagrangian–Eulerian (ALE) technique-based thermomechanical finite element (FE) analysis. To scale-up the defect observation method from laboratory-scale to production-scale manufacturing and confirm the reproducibility of the surface defect, scaled-up L-shaped extrusions were performed in an actual industrial production line. Finally, the potential cause of white line defect generation is discussed by comparing the numerical and metallurgical analyses, including the scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) observations.


Author(s):  
Shunuan Liu ◽  
Ning Wang ◽  
Kaifu Zhang ◽  
Bin Luo

Hole surface quality in drilling carbon fiber-reinforced plastics and titanium alloy (CFRP-Ti) stacks is a key factor affecting high-quality assembly and reliable usage of the structure so it need be reasonably evaluated. However, there is no standardized evaluation system of hole surface quality in drilling CFRP-Ti stacks. The existing evaluation indexes cannot meet the evaluation requirements on the surface quality of the hole. This paper proposes a subjective-objective evaluation method to evaluate the surface quality of the hole in drilling CFRP-Ti stacks. Firstly, the evaluation factors are determined by experiments, including CFRP delamination, CFRP hole entrance tears, surface roughness of CFRP and Ti, and the evaluation system is established according to defect characteristics and industry standards. Secondly, the subjective evaluation model is established based on the improved analytic hierarchy process, the objective evaluation model is established based on the entropy weight method and the subjective and objective combination weight calculation method is obtained based on the principle of minimum discriminant information. Finally, the surface quality of the hole is evaluated by subjective, objective, subjective-objective evaluation methods respectively. The result shows that subjective-objective evaluation method is more reasonable and effective.


2020 ◽  
Vol 64 (1-4) ◽  
pp. 1365-1372
Author(s):  
Xiaohui Mao ◽  
Liping Fei ◽  
Xianping Shang ◽  
Jie Chen ◽  
Zhihao Zhao

The measurement performance of road vehicle automatic weighing instrument installed on highways is directly related to the safety of roads and bridges. The fuzzy number indicates that the uncertain quantization problem has obvious advantages. By analyzing the factors affecting the metrological performance of the road vehicle automatic weighing instrument, combined with the fuzzy mathematics theory, the weight evaluation model of the dynamic performance evaluation of the road vehicle automatic weighing instrument is proposed. The factors of measurement performance are summarized and calculated, and the comprehensive evaluation standard of the metering performance of the weighing equipment is obtained, so as to realize the quantifiable analysis and evaluation of the metering performance of the dynamic road vehicle automatic weighing instrument in use, and provide data reference for adopting a more scientific measurement supervision method.


Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 706
Author(s):  
Xinglong Feng ◽  
Xianwen Gao ◽  
Ling Luo

It is important to accurately classify the defects in hot rolled steel strip since the detection of defects in hot rolled steel strip is closely related to the quality of the final product. The lack of actual hot-rolled strip defect data sets currently limits further research on the classification of hot-rolled strip defects to some extent. In real production, the convolutional neural network (CNN)-based algorithm has some difficulties, for example, the algorithm is not particularly accurate in classifying some uncommon defects. Therefore, further research is needed on how to apply deep learning to the actual detection of defects on the surface of hot rolled steel strip. In this paper, we proposed a hot rolled steel strip defect dataset called Xsteel surface defect dataset (X-SDD) which contains seven typical types of hot rolled strip defects with a total of 1360 defect images. Compared with the six defect types of the commonly used NEU surface defect database (NEU-CLS), our proposed X-SDD contains more types. Then, we adopt the newly proposed RepVGG algorithm and combine it with the spatial attention (SA) mechanism to verify the effect on the X-SDD. Finally, we apply multiple algorithms to test on our proposed X-SDD to provide the corresponding benchmarks. The test results show that our algorithm achieves an accuracy of 95.10% on the testset, which exceeds other comparable algorithms by a large margin. Meanwhile, our algorithm achieves the best results in Macro-Precision, Macro-Recall and Macro-F1-score metrics.


2021 ◽  
pp. 1-18
Author(s):  
Hui Liu ◽  
Boxia He ◽  
Yong He ◽  
Xiaotian Tao

The existing seal ring surface defect detection methods for aerospace applications have the problems of low detection efficiency, strong specificity, large fine-grained classification errors, and unstable detection results. Considering these problems, a fine-grained seal ring surface defect detection algorithm for aerospace applications is proposed. Based on analysis of the stacking process of standard convolution, heat maps of original pixels in the receptive field participating in the convolution operation are quantified and generated. According to the generated heat map, the feature extraction optimization method of convolution combinations with different dilation rates is proposed, and an efficient convolution feature extraction network containing three kinds of dilated convolutions is designed. Combined with the O-ring surface defect features, a multiscale defect detection network is designed. Before the head of multiscale classification and position regression, feature fusion tree modules are added to ensure the reuse and compression of the responsive features of different receptive fields on the same scale feature maps. Experimental results show that on the O-rings-3000 testing dataset, the mean condition accuracy of the proposed algorithm reaches 95.10% for 5 types of surface defects of aerospace O-rings. Compared with RefineDet, the mean condition accuracy of the proposed algorithm is only reduced by 1.79%, while the parameters and FLOPs are reduced by 35.29% and 64.90%, respectively. Moreover, the proposed algorithm has good adaptability to image blur and light changes caused by the cutting of imaging hardware, thus saving the cost.


Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 393
Author(s):  
Jiantao Zhou ◽  
Xu Han ◽  
Hui Li ◽  
Sheng Liu ◽  
Shengnan Shen ◽  
...  

Laser polishing is a widely used technology to improve the surface quality of the products. However, the investigation on the physical mechanism is still lacking. In this paper, the established numerical transient model reveals the rough surface evolution mechanism during laser polishing. Mass transfer driven by Marangoni force, surface tension and gravity appears in the laser-induced molten pool so that the polished surface topography tends to be smoother. The AlSi10Mg samples fabricated by laser-based powder bed fusion were polished at different laser hatching spaces, passes and directions to gain insight into the variation of the surface morphologies, roughness and microhardness in this paper. The experimental results show that after laser polishing, the surface roughness of Ra and Sa of the upper surface can be reduced from 12.5 μm to 3.7 μm and from to 29.3 μm to 8.4 μm, respectively, due to sufficient wetting in the molten pool. The microhardness of the upper surface can be elevated from 112.3 HV to 176.9 HV under the combined influence of the grain refinement, elements distribution change and surface defects elimination. Better surface quality can be gained by decreasing the hatching space, increasing polishing pass or choosing apposite laser direction.


Sign in / Sign up

Export Citation Format

Share Document