Optimization of parameters in laser powder deposition AlSi10Mg alloy using Taguchi method

Liu, Yang; Liu, Chao; Liu, Wensheng; Ma, Yunzhu; Tang, Shibo; Liang, Chaoping; Cai, Qingshan; Zhang, Cheng

doi:10.1016/j.optlastec.2018.10.030

Cited by 90 publications

(49 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A full factorial experiment would have required 4 4 = 256 different combinations since there were 4 levels for each factor. By using a Taguchi orthogonal L 16 (4 4 ) design, only 16 runs were needed, substantially reducing the number of runs over a full factorial experiment [13]. The Taguchi orthogonal array is a balanced design with each factor level weighted equally, so each factor can be evaluated independently.…”

Section: Methodsmentioning

confidence: 99%

“…where A clad is the cross-sectional area of clad on the substrate; W is the width of the total clad layer; H is the maximal height of the clad layer; B represents the scanning speed ( Figure 2). Calculating the signal-to-noise ratio (S/N) is a useful technique in data analysis for predicting optimized results [13,15,16]. S/N is a measure of the error between the actual response and the expected value [17,18].…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Optimizing Processing Parameters for Multi-Track Laser Cladding Utilizing Multi-Response Grey Relational Analysis

Lian

Zhang

et al. 2019

Coatings

View full text Add to dashboard Cite

Multi-track laser cladding is the primary technology used in industrial applications for surface reinforcement and remanufacturing of broken parts. In this study, the influence of processing parameters on multi-track laser cladding was investigated using a Taguchi orthogonal experimental design. A multi-response grey relational analysis (GRA) was employed to identify laser cladding processing parameters that simultaneously optimize the flatness ratio of the coating and the cladding efficiency. The optimal parameters setting found by GRA were validated experimentally. Results showed that the flatness ratio and cladding efficiency were closely correlated to the overlap rate and laser power, where the overlap rate shows the most significant impact on the flatness ratio and the laser power shows the most significant impact on cladding efficiency. Results from the validation experiment were within one percent (0.97% error) of the predicted value. This demonstrates the benefits of utilizing GRA in laser cladding process optimization. The methods presented in this paper can be used to identify ideal processing parameters for multi-response multi-track laser cladding processes or other industrial applications.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Optimizing Processing Parameters for Multi-Track Laser Cladding Utilizing Multi-Response Grey Relational Analysis

Lian

Zhang

et al. 2019

Coatings

View full text Add to dashboard Cite

show abstract

“…In signal processing, signal-to-noise ratio (SNR) is commonly used to understand the extent to which a desired property is affected by background noise. The higher the SNR, the better the product performance [22,23]. To obtain good quality multi-pass laser claddings, the SNRs of three responses were investigated to reveal the effects of the process parameters.…”

Section: Selection Of Signal-to-noise Ratiosmentioning

confidence: 99%

“…To obtain good quality multi-pass laser claddings, the SNRs of three responses were investigated to reveal the effects of the process parameters. The performance characteristics can be classified into three categories: the Larger the Better (LB), the Smaller the Better (SB), and the Nominal the Better (NB) [23,24]. Specifically, the clad width (W) and flatness (F) are considered as LB, whereas the non-fusion area (A nf ) is set to be SB, as calculated by…”

Section: Selection Of Signal-to-noise Ratiosmentioning

confidence: 99%

An Integrated Method for Multi-Objective Optimization of Multi-Pass Fe50/TiC Laser Cladding on AISI 1045 Steel based on Grey Relational Analysis and Principal Component Analysis

et al. 2020

View full text Add to dashboard Cite

As an essentially multi-input multi-output process, determination of optimal conditions for laser cladding normally requires multi-objective optimization. To understand multi-response coupling, the effects of processing parameters on the morphology quality of multi-pass laser claddings of Fe50/TiC on medium carbon steel AISI 1045 were investigated based on composite central design using response surface methodology. Multiple responses, including clad width, flatness, and non-fusion area, were transformed into a single objective through grey relational analysis, with weights objectively identified by principal component analysis. The correlation between grey relational grade (GRG) and process parameters was established by regression analysis. The results show that the GRG response model has excellent goodness of fit and predictive performance. A validation experiment was conducted at the process condition optimized for maximum GRG. The relative error of the predicted optimal GRG is 4.87% whereas those of interested individual objectives, i.e. clad width, flatness, and non-fusion area, are 5.73%, 2.97%, and 6.73%, respectively, which verifies the accuracy of the established model. The investigation of mechanical properties suggests the hardness of substrate can be improved from 20 HRC to 60 HRC and wear resistance to over 8.14 times better.Coatings 2020, 10, 151 2 of 22 independently when conducting optimization. The authors of [5][6][7] used regression analysis (RA) to develop empirical-statistical relationships between key parameters and geometrical characteristics of single-pass NiCrAlY, Ti-6Al-4V, and WC-12Co claddings (i.e., clad height, clad width, penetration depth, wetting angle, and dilution) as a combined parameter (P α V β F γ ). These empirical-statistical relationships were found to be in good agreement with measured values of single clad passes. Shi et al. [8] evaluated the effects of processing parameters (laser power, scanning velocity, and powder mass flow rate) on the geometric form of clad (clad height, width, and depth penetration into the substrate) using multiple regression analysis (MRA). With optimized process parameters, a 45-mm-high thin wall was formed with smooth side surfaces. By applying individual objectives, the laser cladding process can be easily optimized for each criterion. However, multiple optimizations of process conditions are hard to combine into a common goal.Many researchers have presented numerous methodologies to integrate multiple objectives for process optimization. Grey relational analysis (GRA), a process of quantifying the dynamic development of complex systems, has become an efficient method to reveal the correlation between influencing factors and multiple responses [9,10]. Mondal et al. [11] prepared Ni/Cr/Mo composite coatings on AISI 1040 steel with a L9 orthogonal array, using GRA (response target weight was one-third) to build the relationship between process parameters (laser power, scan speed, and powder feed rate) and clad quality characteristics (clad he...

show abstract

“…Liu et al [28] Optimization of the machining process for the roughness of the surface of materials. L 9 Kumar, Agarwal and Srivastava [29] Optimization of the penetration rate in rotary percussive drilling of machines.…”

mentioning

confidence: 99%

Design Optimization of the Aeronautical Sheet Hydroforming Process Using the Taguchi Method

et al. 2019

View full text Add to dashboard Cite

The aluminium alloy sheet forming processes forging in rubber pad and diaphragm presses (also known as hydroforming processes) are simple and economical processes adapted to aeronautical production. Typical defects of these processes are elastic recovery, necking, and wrinkling, and they present difficulties in control mainly due to property variations of the sheet material that take place during the process. In order to make these processes robust and unresponsive to material variations, a multiobjective optimization methodology based on the Taguchi method is proposed in the present study. The design of experiments and process simulation are combined in the methodology, using the nonlinear finite element method. The properties of sheet material are considered noise factors of the hydroforming process, the objective being to find a combination of the control factors that causes minimal defects to noise factors. The methodology was applied to an AA2024-T3 aluminium alloy sheet of 1 mm thickness stamping process in a diaphragm press. The results allowed us to establish the optimal pressure values, friction coefficient between sheet and block, and friction coefficient between sheet and rubber to reduce the elastic recovery variations and the minimal thickness before noise facts.

show abstract

Optimization of parameters in laser powder deposition AlSi10Mg alloy using Taguchi method

Cited by 90 publications

References 53 publications

Optimizing Processing Parameters for Multi-Track Laser Cladding Utilizing Multi-Response Grey Relational Analysis

Optimizing Processing Parameters for Multi-Track Laser Cladding Utilizing Multi-Response Grey Relational Analysis

An Integrated Method for Multi-Objective Optimization of Multi-Pass Fe50/TiC Laser Cladding on AISI 1045 Steel based on Grey Relational Analysis and Principal Component Analysis

Design Optimization of the Aeronautical Sheet Hydroforming Process Using the Taguchi Method

Contact Info

Product

Resources

About