scholarly journals Effect of Printing Parameters on Dimensional Error, Surface Roughness and Porosity of FFF Printed Parts with Grid Structure

Polymers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1213
Author(s):  
Irene Buj-Corral ◽  
Ali Bagheri ◽  
Maurici Sivatte-Adroer
Keyword(s):  
Flow Rate ◽  
Desirability Function ◽  
Low Cost ◽  
Multi Objective Optimization ◽  
Grid Structure ◽  
Fused Filament Fabrication ◽  
Dimensional Error ◽  
Layer Height ◽  
Multi Objective ◽  
Printing Parameters

Extrusion printing processes allow for manufacturing complex shapes in a relatively cheap way with low-cost machines. The present study analyzes the effect of printing parameters on dimensional error, roughness, and porosity of printed PLA parts obtained with grid structure. Parts are obtained by means of the fused filament fabrication (FFF) process. Four variables are chosen: Layer height, temperature, speed, and flow rate. A two-level full factorial design with a central point is used to define the experimental tests. Dimensional error and porosity are measured with a profile projector, while roughness is measured with a contact roughness meter. Mathematical regression models are found for each response, and multi-objective optimization is carried out by means of the desirability function. Dimensional error and roughness depend mainly on layer height and flow rate, while porosity depends on layer height and printing speed. Multi-objective optimization shows that recommended values for the variables are layer height 0.05 mm, temperature 195 ºC, speed 50 mm/min, and flow rate 0.93, when dimensional error and roughness are to be minimized, and porosity requires a target value of 60%. The present study will help to select appropriate printing parameters for printing porous structures such as those found in prostheses, by means of extrusion processes.

scholarly journals Modeling of the Influence of Input AM Parameters on Dimensional Error and Form Errors in PLA Parts Printed with FFF Technology

Polymers ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 4152
Author(s):  
Carmelo J. Luis-Pérez ◽  
Irene Buj-Corral ◽  
Xavier Sánchez-Casas
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Desirability Function ◽  
Nozzle Diameter ◽  
Simultaneous Optimization ◽  
Acetabular Cup ◽  
Fused Filament Fabrication ◽  
Dimensional Error ◽  
Layer Height ◽  
Form Errors

As is widely known, additive manufacturing (AM) allows very complex parts to be manufactured with porous structures at a relatively low cost and in relatively low manufacturing times. However, it is necessary to determine in a precise way the input values that allow better results to be obtained in terms of microgeometry, form errors, and dimensional error. In an earlier work, the influence of the process parameters on surface roughness obtained in fused filament fabrication (FFF) processes was analyzed. This present study focuses on form errors as well as on dimensional error of hemispherical cups, with a similar shape to that of the acetabular cup of hip prostheses. The specimens were 3D printed in polylactic acid (PLA). Process variables are nozzle diameter, temperature, layer height, print speed, and extrusion multiplier. Their influence on roundness, concentricity, and dimensional error is considered. To do this, adaptive neuro-fuzzy inference systems (ANFIS) models were used. It was observed that dimensional error, roundness, and concentricity depend mainly on the nozzle diameter and on layer height. Moreover, high nozzle diameter of 0.6 mm and high layer height of 0.3 mm are not recommended. A desirability function was employed along with the ANFIS models in order to determine the optimal manufacturing conditions. The main aim of the multi-objective optimization study was to minimize average surface roughness (Ra) and roundness, while dimensional error was kept within the interval Dimensional Error≤0.01. When the simultaneous optimization of both the internal and the external surface of the parts is performed, it is recommended that a nozzle diameter of 0.4 mm be used, to have a temperature of 197 °C, a layer height of 0.1 mm, a print speed of 42 mm/s, and extrusion multiplier of 94.8%. This study will help to determine the influence of the process parameters on the quality of the manufactured parts.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

Multi-objective optimization of squirrel cage fan for range hood based on Kriging model

2021 ◽  
pp. 095440622199586
Author(s):  
Qianhao Xiao ◽  
Jun Wang ◽  
Boyan Jiang ◽  
Weigang Yang ◽  
Xiaopei Yang
Keyword(s):  
Flow Rate ◽  
Optimization Design ◽  
Volume Flow Rate ◽  
Kriging Model ◽  
Volume Flow ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

scholarly journals Suitability of Recycled PLA Filament Application in Fused Filament Fabrication Process

2021 ◽  
Vol 15 (4) ◽  
pp. 491-497
Author(s):  
Tomislav Breški ◽  
Lukas Hentschel ◽  
Damir Godec ◽  
Ivica Đuretek
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Polylactic Acid ◽  
Design Of Experiment ◽  
Experimental Approach ◽  
Manufacturing Processes ◽  
Support Structures ◽  
Fused Filament Fabrication ◽  
Layer Height ◽  
Printing Parameters

Fused filament fabrication (FFF) is currently one of the most popular additive manufacturing processes due to its simplicity and low running and material costs. Support structures, which are necessary for overhanging surfaces during production, in most cases need to be manually removed and as such, they become waste material. In this paper, experimental approach is utilised in order to assess suitability of recycling support structures into recycled filament for FFF process. Mechanical properties of standardized specimens made from recycled polylactic acid (PLA) filament as well as influence of layer height and infill density on those properties were investigated. Optimal printing parameters for recycled PLA filaments are determined with Design of Experiment methods (DOE).

scholarly journals Optimization of the 3D Printing Parameters for Tensile Properties of Specimens Produced by Fused Filament Fabrication of 17-4PH Stainless Steel

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 774 ◽  
Author(s):  
Damir Godec ◽  
Santiago Cano ◽  
Clemens Holzer ◽  
Joamin Gonzalez-Gutierrez
Keyword(s):  
Stainless Steel ◽  
3D Printing ◽  
Tensile Properties ◽  
Layer Thickness ◽  
Flow Rate ◽  
Three Dimensional ◽  
Steel Powder ◽  
Extrusion Temperature ◽  
Fused Filament Fabrication ◽  
Printing Parameters

Fused filament fabrication (FFF) combined with debinding and sintering could be an economical process for three-dimensional (3D) printing of metal parts. In this paper, compounding, filament making, and FFF processing of feedstock material with 55% vol. of 17-4PH stainless steel powder in a multicomponent binder system are presented. The experimental part of the paper encompasses central composite design for optimization of the most significant 3D printing parameters (extrusion temperature, flow rate multiplier, and layer thickness) to obtain maximum tensile strength of the 3D-printed specimens. Here, only green specimens were examined in order to be able to determine the optimal parameters for 3D printing. The results show that the factor with the biggest influence on the tensile properties was flow rate multiplier, followed by the layer thickness and finally the extrusion temperature. Maximizing all three parameters led to the highest tensile properties of the green parts.

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.

Investigation on the modeling and dynamic characteristics of a fast-response and large-flow water hydraulic proportional cartridge valve

2020 ◽  
Vol 234 (22) ◽  
pp. 4415-4432
Author(s):  
Mingxing Han ◽  
Yinshui Liu ◽  
Kan Zheng ◽  
Youchun Ding ◽  
Defa Wu
Keyword(s):  
Genetic Algorithm ◽  
Flow Rate ◽  
Dynamic Characteristics ◽  
Fast Response ◽  
Dynamics Simulation ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Flow Capacity ◽  
Water Hydraulic ◽  
Large Flow

In large-power and high-pressure hydraulic systems, the maximum instantaneous flow rate is often several thousand liters per minute. Normal proportional valves are often difficult to meet their requirements for large flow rate and fast response at the same time. And the leakage of hydraulic oil will seriously pollute the environment. Therefore, a novel water hydraulic proportional valve with fast response and high flow capacity is presented for the large transient power hydraulic system in this paper. The valve utilizes a two-stage structure with two 2/2-way water hydraulic proportional valves as the pilot stage and a cartridge poppet valve as the main stage to achieve fast-response and large-flow capacity simultaneously. A detailed and precise nonlinear mathematical model of the valve considering both structural parameters and flow force is developed. A comprehensive performance optimization has been carried out, which can be mainly divided into computational fluid dynamics simulation optimization based on reducing flow force and multi-objective optimization based on genetic algorithm. The effects of double U-grooves' parameters on the flow force (flow-induced loads) have been studied in detail by numerical simulation. Through the grooves geometry optimization, the maximum flow force can be reduced by 10%. Then, the influences of structure parameters on the performance of step response have been studied, and the optimal parameters of the valve have been obtained by multi-objective optimization based on genetic algorithm. The maximum overshoot has been reduced from 15% to 6% (about 60%) and the adjusting time has been reduced from 58 ms to 48 ms. The dynamic characteristics of the valve have been improved effectively. Finally, a test apparatus which has the ability to provide transient large flow is built. The accuracy of simulation model and optimization design method is verified by test results.

scholarly journals Energy Saving and Low-Cost-Oriented Design Processes of Blank’s Dimensions Based on Multi-Objective Optimization Model

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 811 ◽  
Author(s):  
Yongmao Xiao ◽  
Qingshan Gong ◽  
Xiaowu Chen
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Optimization Model ◽  
Low Cost ◽  
Minimum Cost ◽  
Processing Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Set Up

The blank’s dimensions are an important focus of blank design as they largely determine the energy consumption and cost of manufacturing and further processing the blank. To achieve energy saving and low cost during the optimization of blank dimensions design, we established energy consumption and cost objectives in the manufacturing and further processing of blanks by optimizing the parameters. As objectives, we selected the blank’s production and further processing parameters as optimization variables to minimize energy consumption and cost, then set up a multi-objective optimization model. The optimal blank dimension was back calculated using the parameters of the minimum processing energy consumption and minimum cost state, and the model was optimized using the non-dominated genetic algorithm-II (NSGA-II). The effect of designing blank dimension in saving energy and costs is obvious compared with the existing methods.

Flow Resistance Coefficient Identification of Chilled Water System Based on Multi-Objective Optimization and Experiment Validation

2014 ◽  
Vol 651-653 ◽  
pp. 742-746
Author(s):  
Zhi Jian Hou ◽  
Ming Qu ◽  
Zhi Rui Wang
Keyword(s):  
Flow Rate ◽  
Air Conditioning ◽  
Optimization Problems ◽  
Water Flow Rate ◽  
Resistance Coefficient ◽  
Fundamental Parameter ◽  
Multi Objective Optimization ◽  
Air Conditioning System ◽  
Multi Objective ◽  
Terminal Unit

Hydraulic resistance coefficient (HRC) is a fundamental parameter that characterizes the hydraulic state of a water pipeline and significantly determines the efficiency of the water-transport process. To estimate HRC and diagnose hydraulic process fault in building air conditioning system, a novel method called multi-objective optimization (MBO) strategy was developed in the research effort. MBO is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. In this paper, first, the basic principle of the approach is presented. Then several experiments are conducted to identify the HRC in a real air conditioning system. And the water flow rate of each air handling terminal unit is estimated by the flow rate of primary pipe and identified HRC. The experiment results show that the model can accurately estimate HRCs. The HRCs of each pipe and terminal unit were obtained by the flow rate and the pressure difference of primary pipe without requiring geometric specifications, which is very convenient in real engineering application.

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