A Mathematical Model-Based Optimization Method for Direct Metal Deposition of Multimaterials

2017 ◽  
Vol 139 (8) ◽  
Author(s):  
Jingyuan Yan ◽  
Ilenia Battiato ◽  
Georges M. Fadel
Keyword(s):  
Inconel 718 ◽  
Laser Power ◽  
Laser Energy ◽  
Scanning Speed ◽  
Metal Deposition ◽  
Direct Metal Deposition ◽  
Fabrication Process ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Multi Objective

During the past few years, metal-based additive manufacturing technologies have evolved and may enable the direct fabrication of heterogeneous objects with full spatial material variations. A heterogeneous object has potentially many advantages, and in many cases can realize the appearance and/or functionality that homogeneous objects cannot achieve. In this work, we employ a preprocess computing combined with a multi-objective optimization algorithm based on the modeling of the direct metal deposition (DMD) of dissimilar materials to optimize the fabrication process. The optimization methodology is applied to the deposition of Inconel 718 and Ti–6Al–4V powders with prescribed powder feed rates. Eight design variables are accounted in the example, including the injection angles, injection velocities, and injection nozzle diameters for the two materials, as well as the laser power and scanning speed. The multi-objective optimization considers that the laser energy consumption and the powder waste during the fabrication process should be minimized. The optimization software modeFRONTIER® is used to drive the computation procedure with a matlab code. The results show the design and objective spaces of the Pareto optimal solutions and enable the users to select preferred setting configurations from the set of optimal solutions. A feasible design is selected which corresponds to a relatively low material cost, with laser power 370 W, scanning speed 55 mm/s, injection angles 15 deg, injection velocities 45 m/s for Inconel 718, 30 m/s for Ti–6Al–4V, and nozzle widths 0.5 mm under the given condition.

Optimization of Process Parameters in Laser Engineered Net Shaping (LENS) Deposition of Multi-Materials

2015 ◽  
Author(s):  
Jingyuan Yan ◽  
Nafiseh Masoudi ◽  
Ilenia Battiato ◽  
Georges Fadel
Keyword(s):  
Fabrication Process ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Feeding Rates ◽  
Multi Objective ◽  
Heterogeneous Objects ◽  
Multiple Materials ◽  
Optimization Methodology ◽  
Manufacturing Technologies ◽  
Net Shaping

During the past few years, metal based additive manufacturing technologies have evolved and may enable the direct fabrication of heterogeneous objects with full spatial material variations. A heterogeneous object has potentially many advantages and in many cases can realize appearance and/or functionality that homogeneous objects cannot achieve. In this work we employ a preprocess computing combined with a multi-objective optimization algorithm based on the modeling of the LENS deposition of multiple materials to optimize the fabrication process. The optimization methodology is applied to the fabrication of cermet composite (using Inconel 718 and ceramic powders) with prescribed material feeding rates. The multi-objective optimization considers that the energy consumption and the material waste during the fabrication process should be minimized, while the probability of the melting of the powders should be maximized. The optimization software modeFRONTIER® is used to drive the computation procedure with a MATLAB code. The results show the design and objective spaces of the Pareto optimal solutions, and enable the users to select preferred setting configurations from the set of optimal solutions.

Research on Technics of Laser Direct Metal Deposition Forming Technology

2009 ◽  
Vol 69-70 ◽  
pp. 54-58
Author(s):  
Wei Zhang ◽  
Jian Hua Yao
Keyword(s):  
Laser Power ◽  
Scanning Speed ◽  
Metal Deposition ◽  
Direct Metal Deposition ◽  
Solidification Velocity ◽  
Technological Parameters ◽  
Technical Parameters ◽  
Forming Technology ◽  
Average Hardness ◽  
Feeding Speed

The technological parameters of laser direct metal deposition (DMD) were researched by DMD forming experiments using 2Cr13 powder. Fixing other parameters, the lower of laser power, the smaller the characteristic sizes of cladding layer are. Increasing of laser power, cladding height would firstly increase and then decrease, cladding width would firstly increase and then almost maintain constant, while cladding depth would gradually increase. When other parameters are invariable, with increasing of powder feeding speed, cladding height would increase, cladding width and cladding depth would decrease. When other parameters are invariable, cladding width, cladding height and cladding depth would decrease with the adding of scanning speed. The microstructure of single track cladding had three typical patterns, cellular dendritic, column dendritic and equiaxed crystal. The patterns depended on the temperature gradient and the solidification velocity. Under different technical parameters, the average hardness of specimens would change from 300HV0.2 to 550HV0.2.

scholarly journals A Comparative Analysis of Laser Additive Manufacturing of High Layer Thickness Pure Ti and Inconel 718 Alloy Materials Using Finite Element Method

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 876 ◽  
Author(s):  
Sapam Ningthemba Singh ◽  
Sohini Chowdhury ◽  
Yadaiah Nirsanametla ◽  
Anil Kumar Deepati ◽  
Chander Prakash ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Layer Thickness ◽  
Inconel 718 ◽  
Laser Power ◽  
Scanning Speed ◽  
Laser Additive Manufacturing ◽  
Inconel 718 Alloy ◽  
Melt Pool ◽  
High Layer

Investigation of the selective laser melting (SLM) process, using finite element method, to understand the influences of laser power and scanning speed on the heat flow and melt-pool dimensions is a challenging task. Most of the existing studies are focused on the study of thin layer thickness and comparative study of same materials under different manufacturing conditions. The present work is focused on comparative analysis of thermal cycles and complex melt-pool behavior of a high layer thickness multi-layer laser additive manufacturing (LAM) of pure Titanium (Ti) and Inconel 718. A transient 3D finite-element model is developed to perform a quantitative comparative study on two materials to examine the temperature distribution and disparities in melt-pool behaviours under similar processing conditions. It is observed that the layers are properly melted and sintered for the considered process parameters. The temperature and melt-pool increases as laser power move in the same layer and when new layers are added. The same is observed when the laser power increases, and opposite is observed for increasing scanning speed while keeping other parameters constant. It is also found that Inconel 718 alloy has a higher maximum temperature than Ti material for the same process parameter and hence higher melt-pool dimensions.

scholarly journals Single- and Multi-Objective Optimization of a Dual-Chamber Microbial Fuel Cell Operating in Continuous-Flow Mode at Steady State

Processes ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 839
Author(s):  
Ibrahim M. Abu-Reesh
Keyword(s):  
Flow Rate ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Dual Chamber ◽  
Worst Case ◽  
Multi Objective ◽  
Model Based ◽  
Conflicting Objectives

Microbial fuel cells (MFCs) are a promising technology for bioenergy generation and wastewater treatment. Various parameters affect the performance of dual-chamber MFCs, such as substrate flow rate and concentration. Performance can be assessed by power density ( PD ), current density ( CD ) production, or substrate removal efficiency ( SRE ). In this study, a mathematical model-based optimization was used to optimize the performance of an MFC using single- and multi-objective optimization (MOO) methods. Matlab’s fmincon and fminimax functions were used to solve the nonlinear constrained equations for the single- and multi-objective optimization, respectively. The fminimax method minimizes the worst-case of the two conflicting objective functions. The single-objective optimization revealed that the maximum PD ,   CD , and SRE were 2.04 W/m2, 11.08 A/m2, and 73.6%, respectively. The substrate concentration and flow rate significantly impacted the performance of the MFC. Pareto-optimal solutions were generated using the weighted sum method for maximizing the two conflicting objectives of PD and CD in addition to PD and SRE   simultaneously. The fminimax method for maximizing PD and CD showed that the compromise solution was to operate the MFC at maximum PD conditions. The model-based optimization proved to be a fast and low-cost optimization method for MFCs and it provided a better understanding of the factors affecting an MFC’s performance. The MOO provided Pareto-optimal solutions with multiple choices for practical applications depending on the purpose of using the MFCs.

scholarly journals A New Method for Dynamic Multi-Objective Optimization Based on Segment and Cloud Prediction

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 465 ◽  
Author(s):  
Peng Ni ◽  
Jiale Gao ◽  
Yafei Song ◽  
Wen Quan ◽  
Qinghua Xing
Keyword(s):  
Optimization Problems ◽  
Pareto Set ◽  
Benchmark Problems ◽  
Small Range ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Good Convergence ◽  
Multi Objective ◽  
The Law ◽  
Cloud Theory

In the real world, multi-objective optimization problems always change over time in most projects. Once the environment changes, the distribution of the optimal solutions would also be changed in decision space. Sometimes, such change may obey the law of symmetry, i.e., the minimum of the objective function in such environment is its maximum in another environment. In such cases, the optimal solutions keep unchanged or vibrate in a small range. However, in most cases, they do not obey the law of symmetry. In order to continue the search that maintains previous search advantages in the changed environment, some prediction strategy would be used to predict the operation position of the Pareto set. Because of this, the segment and multi-directional prediction is proposed in this paper, which consists of three mechanisms. First, by segmenting the optimal solutions set, the prediction about the changes in the distribution of the Pareto front can be ensured. Second, by introducing the cloud theory, the distance error of direction prediction can be offset effectively. Third, by using extra angle search, the angle error of prediction caused by the Pareto set nonlinear variation can also be offset effectively. Finally, eight benchmark problems were used to verify the performance of the proposed algorithm and compared algorithms. The results indicate that the algorithm proposed in this paper has good convergence and distribution, as well as a quick response ability to the changed environment.

Hybrid QPSO-NNIA2 Algorithm for Multi-Objective Optimization Problem

2019 ◽  
Vol 33 (08) ◽  
pp. 1959025
Author(s):  
Lan Zhang
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problem ◽  
Nearest Neighbor ◽  
Superior Performance ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Evolution Algebra ◽  
Neighbor List

To improve the convergence and distribution of a multi-objective optimization algorithm, a hybrid multi-objective optimization algorithm, based on the quantum particle swarm optimization (QPSO) algorithm and adaptive ranks clone and neighbor list-based immune algorithm (NNIA2), is proposed. The contribution of this work is threefold. First, the vicinity distance was used instead of the crowding distance to update the archived optimal solutions in the QPSO algorithm. The archived optimal solutions are updated and maintained by using the dynamic vicinity distance based m-nearest neighbor list in the QPSO algorithm. Secondly, an adaptive dynamic threshold of unfitness function for constraint handling is introduced in the process. It is related to the evolution algebra and the feasible solution. Thirdly, a new metric called the distribution metric is proposed to depict the diversity and distribution of the Pareto optimal. In order to verify the validity and feasibility of the QPSO-NNIA2 algorithm, we compare it with the QPSO, NNIA2, NSGA-II, MOEA/D, and SPEA2 algorithms in solving unconstrained and constrained multi-objective problems. The simulation results show that the QPSO-NNIA2 algorithm achieves superior convergence and superior performance by three metrics compared to other algorithms.

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