Residual stresses evaluation in precision milling of hardened steel based on the deflection-electrochemical etching technique

Vilček, Igor; Řehoř, Jan; Carou, Diego; Zeman, Pavel

doi:10.1016/j.rcim.2016.10.001

Cited by 18 publications

(3 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hot rolled strip steel is widely used in various industries such as automobile manufacturing, shipbuilding industry, and pipeline transportation. Due to various technical factors, various defects often appear on the surface of hot-rolled strip steel, which can lead to production accidents and seriously affect production enterprises [1] . Moreover, customers have increasingly strict requirements for the quality of hot-rolled strip steel products.…”

Section: Introductionmentioning

confidence: 99%

Research on surface defect classification method of hot rolled strip steel based on comparative learning

Zang,

Zhang,

2024

International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023)

View full text Add to dashboard Cite

In response to the thin nature of hot rolled steel plates and strips, the vast majority of which are surface defects that can easily lead to production accidents, and limited by the challenges of insufficient datasets and a large amount of unlabeled data, this paper proposes a comparative learning method to solve the above problems. In terms of methods, a dual data augmentation strategy is adopted. Firstly, the original image is data enhanced through manual processing, and CycleGAN is introduced for style transfer to enrich the dataset. Then, ResNet152 network is used for feature extraction, and several comparative learning methods are applied to observe the accuracy of hot rolled strip defect detection. In the end, the improved comparative learning method in this article successfully improved the accuracy of surface defect classification for hot rolled strip steel. Through this research, we are committed to providing more reliable quality control methods for industrial production and reducing the risk of production accidents.

show abstract

Section: Introductionmentioning

confidence: 99%

Research on surface defect classification method of hot rolled strip steel based on comparative learning

Zang,

Zhang,

2024

International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023)

View full text Add to dashboard Cite

show abstract

“…Indeed, mathematical optimization has become an important tool in a variety of areas. The list of applications is still steadily expanding [24][25][26][27][28][29][30][31][32]. Solving real problems is the main motivation for the development, so engineering optimization attract attention considerably of many scientists, research teams, and engineers; it is a part of today's current mathematical modelling and control of processes and systems.…”

Section: Introductionmentioning

confidence: 99%

Selected Mathematical Optimization Methods for Solving Problems of Engineering Practice

2022

View full text Add to dashboard Cite

Engineering optimization is the subject of interest for many scientific research teams on a global scale; it is a part of today’s mathematical modelling and control of processes and systems. The attention in this article is focused on optimization modelling of technological processes of surface treatment. To date, a multitude of articles are devoted to the applications of mathematical optimization methods to control technological processes, but the situation is different for surface treatment processes, especially for anodizing. We perceive their lack more, so this state has stimulated our interest, and the article contributes to filling the gap in scientific research in this area. The article deals with the application of non-linear programming (NLP) methods to optimise the process of anodic oxidation of aluminium using MATLAB toolboxes. The implementation of optimization methods is illustrated by solving a specific problem from engineering practice. The novelty of this article lies in the selection of effective approaches to the statement of optimal process conditions for anodizing. To solve this complex problem, a solving strategy based on the design of experiments approach (for five factors), exploratory data analysis, confirmatory analysis, and optimization modelling is proposed. The original results have been obtained through the experiment (performed by using the DOE approach), statistical analysis, and optimization procedure. The main contribution of this study is the developed mathematical-statistical computational (MSC) model predicting the thickness of the resulting aluminium anodic oxide layer (AOL). Based on the MSC model, the main goal has been achieved—the statement of optimal values of factors acting during the anodizing process to achieve the thickness of the protective layer required by clients, namely, for 5, 7, 10, and 15 [μm].

show abstract

“…However, most of the works are focused on the accuracy of the programmed tool path, especially on obtaining high accuracy in the corner cut [21][22][23]. The quality of the surface after the WEDM process does not always meet expectations therefore additional technological operations are used [24][25][26][27] to improve surface quality. However, the use of additional treatments significantly increases the production costs.…”

Section: Introductionmentioning

confidence: 99%

Archives of Metallurgy and Materials

Świercz

Oniszczuk-Świercz

Zawora

et al. 2019

View full text Add to dashboard Cite

New materials require the use of advanced technology in manufacturing parts of complex shape. One of the modern nonconventional technology of manufacturing difficult to cut materials is the wire electrical discharge machining (WEDM). The article presents the results of theoretical and experimental research in the influence of the WEDM conditions and parameters on the shape deviation during a rough cut. A numerical model of the dielectric flow in the gap (ANSYS) was developed. The influence of the dielectric velocity field in the gap on the debris evacuation and stability of WEDM process was discussed. Furthermore, response surface methodology (RSM) was used to build empirical models for influence of the wire speed V d , wire tension force F n , the volume flow rate of the dielectric Q v on the flatness deviation after the WEDM.

show abstract

Residual stresses evaluation in precision milling of hardened steel based on the deflection-electrochemical etching technique

Cited by 18 publications

References 21 publications

Research on surface defect classification method of hot rolled strip steel based on comparative learning

Research on surface defect classification method of hot rolled strip steel based on comparative learning

Selected Mathematical Optimization Methods for Solving Problems of Engineering Practice

Archives of Metallurgy and Materials

Contact Info

Product

Resources

About