Laser-Based Repair of Damaged Dies, Molds, and Gears

Nikam, Sagar H.; Jain, Neelesh Kumar

doi:10.1007/978-3-319-56099-1_6

Cited by 9 publications

(6 citation statements)

References 33 publications

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“…The mechanical characterization of the samples showed that in the deposited layer, compressive residual stresses were generated. Leunda et al [84] varying the process parameters repaired heat cracks, caused by repetitive heating and cooling cycles [85], on Vanadis 4 die using Vanadis 4 and CPM 10 powder. Results showed that a good metallurgical bonding was obtained without defect, and this suggests that LP-DED can be successfully used to repair heat cracks.…”

Section: Lp-ded Repair Of Tools and Mouldsmentioning

confidence: 99%

Current research and industrial application of laser powder directed energy deposition

Piscopo

Iuliano

2022

Int J Adv Manuf Technol

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Additive Manufacturing (AM) technologies are recognized as the future of the manufacturing industry thanks to their possibilities in terms of shape design, part functionality, and material efficiency. The use of AM technologies in many industrial sectors is growing, also due to the increasing knowledge regarding the AM processes and the characteristics of the final part. One of the most promising AM techniques is the Directed Energy Deposition (DED) that uses a thermal source to generate a melt pool on a substrate into which metal powder is injected. The potentialities of DED technology are the ability to process large build volumes (> 1000 mm in size), the ability to deliver the material directly into the melt pool, the possibility to repair existing parts, and the opportunity to change the material during the building process, thus creating functionally graded material. In this paper, a review of the industrial applications of Laser Powder Directed Energy Deposition (LP-DED) is presented. Three main applications are identified in repairing, designed material, and production. Despite the enormous advantages of LP-DED, from the literature, it emerges that the most relevant application refers to the repairing process of high-value components.

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Section: Lp-ded Repair Of Tools and Mouldsmentioning

confidence: 99%

Current research and industrial application of laser powder directed energy deposition

Piscopo

Iuliano

2022

Int J Adv Manuf Technol

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“…These defects are formed due to irregularities or contaminations during powder recoating, poor interaction between laser and material, and partial solidification [1]. These defects are of concern among researchers and manufacturers owing to their negative effects on the mechanical properties of manufactured parts [2][3][4]. However, the defects in the components manufactured by the DED process are flash formation, voids, cracks, porosity, surface lines, and high surface roughness.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Approach to Classify and Detect Defects in the Components Manufactured by Laser Directed Energy Deposition Process

Patil,

Nigam,

Mohapatra

et al. 2023

Machines

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This paper presents a deep learning approach to identify and classify various defects in the laser-directed energy manufactured components. It mainly focuses on the Convolutional Neural Network (CNN) architectures, such as VGG16, AlexNet, GoogLeNet and ResNet to perform the automated classification of defects. The main objectives of this research are to manufacture components using the laser-directed energy deposition process, prepare a dataset of horizontal wall structure, vertical wall structure and cuboid structure with three defective classes such as voids, flash formation, and rough textures, and one non-defective class, use this dataset with a deep learning algorithm to classify the defect and use the efficient algorithm to detect defects. The next objective is to compare the performance parameters of VGG16, AlexNet, GoogLeNet and ResNet used for classifying defects. It has been observed that the best results were obtained when the VGG16 architecture was applied to an augmented dataset. With augmentation, the VGG16 architecture gave a test accuracy of 94.7% and a precision of 80.0%. The recall value is 89.3% and an F1-Score is 89.5%. The VGG16 architecture with augmentation is highly reliable for automating the defect detection process and classifying defects in the laser additive manufactured components.

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“…To date, Research in the field of LSM in steels has focused more on the stainless steels and corrosion resistance of resulted structures [28], while LSM in tool steels can be considered as a solution to heal cracks developed during their use [29,30], eliminate cracks and voids in repaired tools and also as a substitution of required heat treatment after repair welding which can contribute to serious heat treatment cracks in large expensive dies and molds [31][32][33]. And this will be possible only if the laser surface melted steel exhibits wear properties at least equal to the heat-treated steel.…”

Section: Introductionmentioning

confidence: 99%

The effect of laser surface melting on the retained austenite and wear properties of AISI D2 tool steel

Moradiani

Beiranvand

Ratnayake

et al. 2022

Optik

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Laser-Based Repair of Damaged Dies, Molds, and Gears

Cited by 9 publications

References 33 publications

Current research and industrial application of laser powder directed energy deposition

Current research and industrial application of laser powder directed energy deposition

A Deep Learning Approach to Classify and Detect Defects in the Components Manufactured by Laser Directed Energy Deposition Process

The effect of laser surface melting on the retained austenite and wear properties of AISI D2 tool steel

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