Investigation of the workability and surface roughness of thin brass wires in various dieless drawing technologies

Possibilities of improving the workability of the CuZn37 brass thin wire in a diameter of 0.14–0.18 mm produced by the dieless drawing processes were explored. The workability was defined as the maximum final longitudinal strain of the wire up to its fracture, achievable in the dieless drawing process. Two technologies of dieless drawing were developed and their workability was compared. The first one is the classical one-pass process; the second, a multi-pass one. For both developed technologies, it was possible to obtain a good-quality product but more than two times higher workability has been demonstrated for the multi-pass technology. No evident effect of the deformation temperature from the window of technologically accepted parameters on the workability was found but an increase in the temperature significantly increased the roughness of the product surface. For the same deformation temperature, the roughness of the wire obtained from the multi-pass process appeared to be significantly lower than for the one of the classical one-pass technologies.

Research of the Processes of Eliminating Warpage of Aviation Products Made of Polymer-Composite Materials Obtained by High-Temperature Molding

The article considers issues of identifying the causes and factors that have a significant impact on the occurring and development of the warping process in monolithic products made of polymer — composite materials (PCM) obtained by the method of multidirectional layering of uncured PCM — semi-finished product (prepreg) and subsequent high-temperature molding in an autoclave. Warping is understood as a defect of a PCM product in the form of distortion of its configuration (deformation) under stresses arising during the polymerization of the binder prepreg at a high temperature (1800C) and cooling the product to room temperature. Flat samples made of glass-based prepregs have been researched. The selecting schemes of equilibrium stacking of samples of monolithic panels has been carried out. The influence of the binder content in the prepreg on the deformations in non-equilibrium layouts of the panel samples has been evaluated. It is shown that the most significant factors influencing the occurrence of warpage of monolithic PCM panels are: the weaving pattern of the prepreg reinforcing base, the amount of binder deposited in the prepreg, the direction of stacking monolayers in the panel, the edge effect and the shape of the product surface. It was found that the warpage of the sample occurs along the direction of unbalanced shrinkage of the binder. For balanced stacking, compensation in the direction of binder shrinkage and symmetry with respect to the central layer are necessary; more binder in the prepreg reduces the amount of warpage, but only slightly. The development of constructive and technological recommendations based on the results obtained will lead to a reduction in the terms of development of PCM products.

Sustainability-Based Analysis of Conventional to High-Speed Machining of Al 6061-T6 Alloy

High-speed machining is considered to be a promising machining technique due to its advantages, such as high productivity and better product quality. With a paradigm shift towards sustainable machining practices, the energy consumption analysis of high-speed machining is also gaining ever-increasing importance. The current article addresses this issue and presents a detailed analysis of specific cutting energy (SCE) consumption and product surface finish (Ra) during conventional to high-speed machining of Al 6061-T6. A Taguchi-based L16 orthogonal array experimental design was developed for the conventional to high-speed machining range of an Al 6061-T6 alloy. The analysis of the results revealed that SCE consumption and Ra improve when the cutting speed is increased from conventional to high-speed machining. In particular, SCE was observed to reduce linearly in conventional and transitional speed machining, whereas it followed a parabolic trend in high-speed machining. This parabolic trend indicates the existence of an optimal cutting speed that may lead to minimum SCE consumption. Chip morphology was performed to further investigate the parabolic trend of SCE in high-speed machining. Chip morphology revealed that the serration of chips initiates when the cutting speed is increased beyond 1750 m/min at a feed rate of 0.4 mm/rev.

An Implementation of Yolo-family Algorithms in Classifying the Product Quality for the ABS Metallization

In the traditional electroplating industry of Acrylonitrile Butadiene Styrene (ABS), quality control inspection of the product surface is usually performed with the naked eye. However, these defects on the surface of electroplated products are minor and easily ignored under reflective conditions. If the number of defectiveness and samples is too large, manual inspection will be challenging and time-consuming. We innovatively applied Additive Manufacturing (AM) to design and assemble an automatic optical inspection (AOI) system. The system can identify defects on the reflective surface of the plated product. Based on the deep learning framework from YOLO, we successfully started the neural network model on GPU using the family of YOLO algorithms: from v2 to v5. Finally, our efforts showed an accuracy rate over an average of 70 percentage for detecting real-time video data in production lines. We also compare the classification performance among various YOLO algorithms. Our efforts of visual inspection significantly reduce the labor cost of visual inspection in the electroplating industry.

A predictive model for galling phenomenon and its applicability for deep drawing processes

Galling is a recurring phenomenon in deep drawing processes which requires frequent maintenance of tools to improve the product surface quality. Adhesive transfer of softer material on the hard tool surface results in sharp features which causes surface roughening of the dies and deterioration of deep drawn products. In this article, an adhesive wear model based on deterministic approach is developed to predict the galling behavior in a deep drawing process. The model uses the surface topography, material properties and contact conditions to predict the surface roughening of tool surfaces under perfectly plastic conditions. The adhesive transfer of material is considered by the growth of the asperities based on its geometry for the increase in height and radial direction by preserving the original shape and volume consistency. The results of the multi-asperity models shows the growth of transfer layer and its effects due to load, sliding cycle, sliding distance and affinity of the materials. The results shows the influence of the above-said parameters and its applicability for deep drawing process conditions. The simulated results shows an 85% level of confidence in comparison with the experiments from literature for the prediction of the surface evolution due to galling mechanism.

Evaluation of Ball End Micromilling for Ti6Al4V ELI Microneedles Using a Nanoadditive Under MQL Condition

The use of nanoadditives in lubricants has gained much attention to the research community due to the enhancement of tribological properties and cooling capabilities. This paper studies the advantages of using a MQL (Minimum Quantity of Lubrication) system and nanoadditive in the manufacture of microneedle arrays in Ti6Al4V ELI alloy. Tungsten carbide ball nose tools with a cutting diameter of 200 µm were used in experimental tests. Surface and dimensional characterization was performed to evaluate the impact of a nanoadditive to a vegetable-based oil. Additionally, cutting forces and cutting edge radius (CER) were measured while needles were machined. Experimental tests confirmed that micro end milling with nanoadditives provide slightly better dimensional features and low cutting forces compared to oil. The performance of nanoadditives resulted in a reduction of surface roughness (~ 0.3 μm). Qualitative study of microneedles illustrated burr formation on needle surface manufactured without a nanoadditive solution. Results reveal an increment of CER using low feed rate values (2.0 µm/flute) while a reduction of CER was observed with feed rates up to 2.5 µm/flute. Our results indicated that the addition of nanoadditives to vegetable oil promotes a better product surface topography and cutting tool performance.

Surface Defect Detection Methods for Industrial Products: A Review

The comprehensive intelligent development of the manufacturing industry puts forward new requirements for the quality inspection of industrial products. This paper summarizes the current research status of machine learning methods in surface defect detection, a key part in the quality inspection of industrial products. First, according to the use of surface features, the application of traditional machine vision surface defect detection methods in industrial product surface defect detection is summarized from three aspects: texture features, color features, and shape features. Secondly, the research status of industrial product surface defect detection based on deep learning technology in recent years is discussed from three aspects: supervised method, unsupervised method, and weak supervised method. Then, the common key problems and their solutions in industrial surface defect detection are systematically summarized; the key problems include real-time problem, small sample problem, small target problem, unbalanced sample problem. Lastly, the commonly used datasets of industrial surface defects in recent years are more comprehensively summarized, and the latest research methods on the MVTec AD dataset are compared, so as to provide some reference for the further research and development of industrial surface defect detection technology.

Automatic Generation of Seamless Mosaics Using Invariant Features

The acquisition of satellite images over a wide area is often carried out across seasons because of satellite orbits and atmospheric conditions (e.g., cloud cover, dust, etc.). This results in spectral mismatch between adjacent scenes as the sun angle and the atmospheric conditions will be different for different acquisitions. In this work, we developed an approach to generate seamless mosaics using Scale-Invariant Features Transformation (SIFT). In this process, we make use of the overlapping areas between two adjacent scenes and then map spectral values of one imagery scene to another based on the filtered points detected by SIFT features to create a seamless mosaic. We make use of the Random Sample Consensus (RANSAC) method successively to filter out obtained SIFT points across adjacent tiles and to remove spectral outliers across each band of an image. Several high resolution satellite images acquired with WorldView-2 and Dubaisat-2 satellites, and medium resolution Sentinel-2 satellite imagery are used for experimentation. The experimental results show that the proposed approach can generate good seamless mosaics. Furthermore, Sentinel-2’s level 2A (L2A) product surface reflectance data is used to adjust the spectral values for color consistency.