Laser Alloying Monel 400 with Amorphous Boron to Obtain Hard Coatings

Kukliński, Mateusz; Bartkowska, Aneta; Przestacki, Damian

doi:10.3390/ma12213494

Cited by 17 publications

(8 citation statements)

References 43 publications

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“…Laser head was integrated with robot arm KUKA KR16-2 (KUKA, Augsburg, Germany) to manipulate location of the beam. To provide constant laser beam velocity on whole length of laser track, the laser beam was started above and turned off behind the specimen just like in papers [ 6 , 31 ]. The scheme of the laser alloying process is presented in Figure 1 .…”

Section: Methodsmentioning

confidence: 99%

Influence of Microstructure and Chemical Composition on Microhardness and Wear Properties of Laser Borided Monel 400

et al. 2020

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In this study, wear properties of Monel 400 after laser alloying with boron are described. Surfaces were prepared by covering them with boron paste layers of two different thicknesses (100 µm and 200 μm) and re-melting using diode laser. Laser beam power density was equal to 178.3 kW/cm2. Two laser beam scanning velocities were chosen for the process: 5 m/min and 50 m/min. Surfaces alloyed with boron were investigated in terms of wear resistance, and the surface of untreated Monel 400 was examined for comparison. Wear tests were performed using counterspecimen made from steel 100Cr6 and water as a lubricant. Both quantitative and qualitative analysis of surfaces after wear test are described in this paper. Additionally, microstructures and properties of obtained laser alloyed surfaces are presented. It was found that the wear resistance increased from four to tens of times, depending on parameters of the laser boriding process. The wear mechanism was mainly adhesive for surfaces alloyed with initial boron layer 100 µm thick and evolves to abrasive with increasing boron content and laser beam scanning velocity. Iron particles detached from counterspecimens were detected on each borided surface after the wear test, and it was found that the harder the surface the less built-ups are present. Moreover, adhered iron particles oxidized during the wear test.

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Section: Methodsmentioning

confidence: 99%

Influence of Microstructure and Chemical Composition on Microhardness and Wear Properties of Laser Borided Monel 400

et al. 2020

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“…In the publications that are available, the authors managed to find a single publication discussing diffusion boriding of Ni-Cu alloys [21]. Publications typically focus on the use of boron as a component of the additive material (powder) used in the laser cladding process (laser alloying [22][23][24][25], laser cladding [26,27]). In [27], a NiCrSiB coating was produced on Monel 400 using a laser cladding method, which was to improve resistance to cavitation erosion and corrosion.…”

Section: Introductionmentioning

confidence: 99%

“…They also found that resistance to cavitation erosion and corrosion was significantly improved. In [22][23][24][25], the influence of boron introduced into the Ni-Cu alloy by means of a laser beam was studied; cracks at the border of laser tracks were found to be a certain drawback when creating a layer on Monel in laser boriding.…”

Section: Introductionmentioning

confidence: 99%

Laser Processing of Diffusion Boronized Layer Produced on Monel® Alloy 400—Microstructure, Microhardness, Corrosion and Wear Resistance Tests

et al. 2021

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The paper presents the results of studies of microstructure, mechanical and physicochemical properties of surface layers produced by laser modification of the diffusion boron layer on Monel® Alloy 400. The diffusion boron layers were produced at 950 °C for 6 h. The gas-contact method was used in an open retort furnace. The process was carried out in a powder mixture containing B4C carbide as a boron source. The next stage was the modification of the boron layer with a diode laser beam of a nominal power of 3 kW. A constant power of 1400 W of the laser beam was used. The scanning speed was variable (successively 5 m/min, 25 m/min, 50 m/min). In order to determine the best parameters, single tracks were created, after which multiple tracks were prepared using previously selected parameters. It was found that both the diffusion borided layer and the laser modified layer had better properties than the substrate material. Both these processes contributed to an increase in corrosion resistance, hardness and wear resistance. It was also found that laser modification caused a slight deterioration of the properties in comparison with the diffusion borided layer. However, the laser modification process resulted in the production of a much thicker layer.

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“…In addition to the right selection of tool material, unconventional machining improved cutting performance is common. One of the used methods is the electrical discharge machining (EDM), laser machining (LAM), electrochemical machining, ultrasonic machining (USM), and high-speed machining [ 27 , 28 , 29 ]. According to [ 30 ], Chwalczuk et al shows the optimization of heating and cutting parameters during turning of Inconel 718 under laser-assisted machining (LAM) conditions.…”

Section: Introductionmentioning

confidence: 99%

Tool Wear Prediction Based on Artificial Neural Network during Aluminum Matrix Composite Milling

Wiciak-Pikuła

Felusiak-Czyryca

Twardowski

2020

Sensors

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This article deals with the phenomenon of tool wear prediction in face milling of aluminum matrix composite materials (AMC), class as hard-to-cut materials. Artificial neural networks (ANN) are one of the tools used to predict tool wear or surface roughness in machining. Model development is applicable when regression models do not give satisfactory results. Because of their mechanical properties based on SiC or Al2O3 reinforcement, AMCs are applied in the automotive and aerospace industry. Due to these materials’ abrasive nature, a three-edged end mill with diamond coating was selected to carry out milling tests. In this work, multilayer perceptron (MLP) models were used to predict the tool flank wear VBB and tool corner wear VBC during milling of AMC with 10% SiC content. The signals of vibration acceleration and cutting forces were selected as input to the network, and the tests were carried out with three cutting speeds. Based on the analysis of the developed models, the models with the best efficiency were selected, and the quality of wear prediction was assessed. The main criterion for evaluating the quality of the developed models was the mean square error (MSE) in order to compare measured and predicted value of tool wear.

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Laser Alloying Monel 400 with Amorphous Boron to Obtain Hard Coatings

Cited by 17 publications

References 43 publications

Influence of Microstructure and Chemical Composition on Microhardness and Wear Properties of Laser Borided Monel 400

Influence of Microstructure and Chemical Composition on Microhardness and Wear Properties of Laser Borided Monel 400

Laser Processing of Diffusion Boronized Layer Produced on Monel® Alloy 400—Microstructure, Microhardness, Corrosion and Wear Resistance Tests

Tool Wear Prediction Based on Artificial Neural Network during Aluminum Matrix Composite Milling

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