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

Abstract

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...

Finite Element Study on the Wear Performance of Movable Jaw Plates of Jaw Crushers after a Symmetrical Laser Cladding Path

“…It is mainly used in the product development fields of mechanical product modeling design, structural design, part assembly design, mold design, numerical control programming, design analysis, etc.) The radius difference between the two concentric circles is 230 mm [26][27][28][29][30], and it is added to the creator in FEPG in the form of x_t (Figure 4). The material of the setting ring in FEPG is 40Cr, the inner part of the cylinder is WDB620 (movable jaw plate material), and the outer part is laser cladding ceramic powder.…”

Grey Relational Analysis and Grey Prediction Model (1, 6) Approach for Analyzing the Electrode Distance and Mechanical Properties of Tandem MIG Welding Distortion

“…GRA is a method for calculating the degree of correlation within sequences and combining several output responses into a single output response by applying a GRG to each output response [ 38 , 39 ]. Researchers [ 40 , 41 , 42 , 43 , 44 ] used GRA to optimize grey-based Taguchi analysis (GTA) welding process variables for the multi-objective response by GRG. Taguchi’s GRA multi-objective optimization approach was used in this study to optimize gas tungsten arc welding (GTAW) characteristics of various AA6061 and AA2014 alloys.…”

Prediction and optimization of process parameters of electrospun polyacrylonitrile based on numerical simulation and response surface method

“…As an important part of the grey theory, the degree of grey correlation has been widely used in defining the similarity between dependent and independent variables. 40,41 Considering the use of the average diameter variation data of the fiber with voltage for GRA, the original data are expressed as follows: …”

“…As an important part of the grey theory, the degree of grey correlation has been widely used in defining the similarity between dependent and independent variables. 40,41 Considering the use of the average diameter variation data of the fiber with voltage for GRA, the original data are expressed as follows: Because the original data contain variations among the units and dimensions, the data points cannot be directly compared. To make the comparison possible, it is necessary to eliminate the differences according to the order of magnitude and utilize the following average conversion equation for processing:…”