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2022 | Buch

Numerical Modelling and Optimization in Advanced Manufacturing Processes

herausgegeben von: Dr. Chander Prakash, Dr. Sunpreet Singh, Dr. Aminesh Basak, Prof. Dr. J. Paulo Davim

Verlag: Springer International Publishing

Buchreihe : Materials Forming, Machining and Tribology

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Über dieses Buch

This book presents different numerical modeling and nature-inspired optimization methods in advanced manufacturing processes for understanding the process characteristics. Particular emphasis is devoted to applications in non-conventional machining, nano-finishing, precision casting, porous biofabrication, three-dimensional printing, and micro-/nanoscale modeling. The book includes practical implications of empirical, analytical, and numerical models for predicting the vital output responses. Especial attention is given to finite element methods (FEMs) for understanding the design of novel highly complex engineering products, their performances, and behaviors under simulated processing conditions.

Inhaltsverzeichnis

Frontmatter
Parametric Appraisal of Plastic Injection Moulding for Low Density Polyethylene (LDPE): A Novel Taguchi Based Honey Badger Algorithm and Capuchin Search Algorithm
Abstract
In our quickly growing world, there is an increasing need for cheap, long-lasting, and less hazardous materials for medical purposes. To meet their needs, medical goods ranging from intravenous fluid containers to medical syringes are manufactured utilizing a variety of thermoplastics and Plastic Injection Moulding (PIM). Even sophisticated profile mouldings, however, may suffer from dimensional inaccuracy. The present research contributes to a better knowledge of thermoplastics, namely Low-Density Polyethylene (LDPE) material moulding for medical syringe plungers utilizing injection moulding equipment. Eight input injection moulding parameters were examined to reduce the depth sink marks along with weight produced during injection moulding of thermoplastic LDPE material. The 27 trials were piloted in accord with Taguchi's Design of Experiment, and the variables were optimized using the newly developed Honey Badger and Capuchin Search Algorithms, as well as analysis of variance, for determining the most dominating parameter. The cooling time and melt temperature of the plastic injection moulded part are the most significant factors influencing the sink-mark depth and weight of the part respectively, according to the Analysis of Variance (ANOVA) test.
Siddharth Jeet, Abhishek Barua, Dilip Kumar Bagal, Swastik Pradhan, Surya Narayan Panda, Siba Sankar Mahapatra
A Comparison of Ferrofluid Flow Models for a Curved Rough Porous Circular Squeeze Film Considering Slip Velocity and Various Shapes
Abstract
The aim of this investigation is to compare the magnetic fluid flow models for the ferrofluid lubrication of porous rough curved circular squeeze films incorporating slip velocity, wherein various film shapes are considered. The random irregularity of the bearing faces is characterized by a stochastic random variable with non-zero skewness, mean and variance. The concerned Reynolds type relation is averaged under Christensen and Tonder’s stochastic modeling. Using Reynolds boundary conditions, this expression is solved for the pressure distribution. Then the load bearing is determined. Magnetic fluid lubrication tends to overcome roughness’ adverse effect as much as possible. This result remains superior in Shliomis (SH) model for almost all film shapes. The novelty of this examination reveals that if designed properly Shliomis model based ferrofluid lubrication may be adopted from industry point of view even for some film shapes Neuringer-Rosensweig (NR)’s model can be a suitable option.
Jimit R. Patel, G. M. Deheri
Simulation and Optimization Study on Polishing of Spherical Steel by Non-newtonian Fluids
Abstract
The spherical surfaces will become important in the areas of industrial production such as jet engines, optical lenses, mould techniques, artificial knee joints, and bearings. These surfaces require high surface quality and form accuracy for the application process. To improve machining quality, the non-Newtonian fluid polishing methods are used to polish the complex surfaces. The process utilizing the shear thickening effect of non-Newtonian fluid based on abrasive slurries to achieve low surface roughness of product. During machining, the main factors affecting the surface quality of workpieces and material removal rate include polishing angles (A), work gap between the workpiece and bottom of the polishing tank (G), and tank velocity (V). The effects of these factors on the machining process are simulated by ANSYS software. The cutting pressure (P) and polishing velocity (Vm) will be discussed and analyzed in this chapter. Finally, the multi-responses optimization is utilized to optimize the maximum pressures and polishing velocity on the workpiece surfaces in machining process. Based on the simulation and optimization results, the best machining parameters were established for improving the maximum pressure and polishing velocity which is distributed on the workpiece surface in polishing process. Moreover, the optimal parameters that are determined during the simulation will be a good support for establishing the conditions for the next experiment process. It was found that the optimal parameters for polishing spherical steel with better pressure and polishing velocity are polishing angle of 13.34°, work gap of 14.25 mm and tank velocity of 2.2 m/s.
Duc-Nam Nguyen, Ngoc Thoai Tran, Thanh-Phong Dao
3D Modeling and Analysis of Femur Bone During Jogging and Stumbling Condition
Abstract
Femur bone is the strongest and largest bone in human body. Femur bone takes major load when a person is doing activities such as standing, walking, and running. The present study is mainly focusing on the different forces coming on the femur bone during different conditions. The FEM analysis is done to know the behavior of material properties, load resistance and chance of failure of femur bone. In the present study the two human activity conditions are taken jogging and stumbling for the different weight category. The 3D CAD model is developed from the CT scan data. The FEM analysis is done by applying boundary conditions and the suitable loading condition. The results are obtained and comparative study has been done for different parameters. It has been observed that during stumbling the total deformation obtained is very large as compare to jogging condition. The different stress parameters are also compare between jogging and stumbling condition.
Imran Ahemad Khan
On Parametric Optimization of TSE for PVDF-Graphene-MnZnO Composite Based Filament Fabrication for 3D/4D Printing Applications
Abstract
In past two decades numerous engineering applications of thermoplastic composite has been reported for manufacturing 3D printed prototypes. The present work also highlighted the enhancement of mechanical properties in polyvinylidene fluoride (PVDF) polymer matrix-based composite for 3D and 4D printing of smart prototypes. In order to ensure rheological, thermal and mechanical properties of PVDF and its matrix based PVDF-Graphene-Mn doped ZnO (PGMZ) composite, a pilot study was conducted. On behalf of this experiment, PGMZ composite was processed through twin screw extrusion (TSE). The TSE process parameters considered for the experimentation were screw temperature, applied torque and weight. The result of experimental study suggested that screw temperature of 190 °C, 0.3 Nm torque and dead weight of 10 kg are the best processing parameters for fabrication of PGMZ composite filament wire for printing 3D prototype. PGMZ shows high modulus of toughness (MoT) 4.68 N and Young’s modulus 1405.16 Mpa at these settings. Further parametric optimization of TSE process highlighted that screw temperature and torque plays the most significant role in processing of composite to prepare the in-house developed feedstock filament.
Vinay Kumar, Rupinder Singh, Inderpreet Singh Ahuja
Multi-factor Optimization for Joining of Polylactic Acid-Hydroxyapatite-Chitosan Based Scaffolds by Rapid Joining Process
Abstract
In past two decades no. of studies has been reported on rapid joining process using 3-dimensional (3D) printed substrate and tool materials. Also, significant work has been reported on optimizing tensile, flexural, compressive and other mechanical properties of 3D printed polymer composite joined by friction stir spot welding process but hither to little has been reported on multi factor optimization by considering different elements of flexural samples prepared by rapid joining process. This paper outlines multi-factor optimization for joining of polylactic acid (PLA)-hydroxyapatite (HAp)-chitosan (CS) based scaffolds by rapid joining process as a case study. This research work has been an extension work of previous reported work in which PLA-HAp-CS based 3D printed biocompatible and biodegradable functional prototypes have been joined using rapid joining process with the help of friction stir spot welding (FSSW).
N. Ranjan, R. Singh, I. P. S. Ahuja
Analysis of Dimensional Accuracy of Fused Filament Fabrication Parts Using Genetic Algorithm and Taguchi Analysis
Abstract
The dimensional accuracy of parts created through Fused Filament Fabrication (FFF) process has been always a subject of investigation for researchers due to variation in results of different optimization algorithms. The situation becomes more complex when different response parameters with equal weightages are required to be optimized. The present investigation aims to solve the dimensional variations issues of FFF parts with different attributes such as length, width, diameter and thickness. Genetic Algorithm is implemented along with Taguchi optimization DOE technique for achieving the minimum dimensional variability in all the attributes. Total 27 experimental results were used for Taguchi and ANOVA analysis followed by Genetic Algorithm. The variable parameters of FFF process are layer thickness, orientation angle, raster angle, raster width and air gap. The results predicted by Genetic Algorithm were more accurate than Taguchi Analysis with higher prediction and validation accuracy. The recommended parametric settings were 0.1405, 0.0000, 0.0000, 0.5064, 0.0080 for layer thickness, orientation angle, raster angle, raster width and air gap respectively with objective function value of 0.5802.
J. S. Chohan, R. Kumar, S. Singh
Introduction to Optimization in Manufacturing Operations
Abstract
With the extensive growth of production industries, manufacturing, as a process, is receiving its due importance. The entire production events starting from collection of raw materials to building a finished product, are strategically encapsulated in the form of a process. The industrial revolution resulted in a substantial leap in global product requirements. A need for optimization arises in order to meet the vast requirements, safely manufacturing a product, managing the cost and a timely delivery of the product. Optimization, in general is a branch of operations research which tackles the problem of minimization or maximization. The questions such as ‘how fast?’, ‘how cheap?’, ‘how efficient?’ etc., are best addressed by an effective optimization algorithm which seeks the better answer considering the profit-loss, efficiency-accuracy, time-precision bound trade-offs. Optimization in manufacturing process is used at all stages be it strategic, tactical or operative and for each stage, objective and constraints are declared. The nature inspired optimization algorithm (NIOAs) enact the behavior of interaction of the natural habitats such as ants, flies, birds etc. and find an optimal solution to a problem. Evolutionary Algorithms (EAs), on the other hand, are simpler and based on Darwin’s theory of’Survival of The Fittest’. NIOAs such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) etc., and EAs such as Genetic Algorithm (GA), are in present time, used to solve numerous existing optimization problems related to computer science, energy, food processing, process control, chemistry, banking and so on and also prove to be potential optimizer to many other real-life problems. This chapter leads through the basic building blocks of optimization algorithms and an attempt is made to bring into light, their uses in manufacturing process. The prerequisite concepts of maxima-minima, unimodal-multimodal problems, local optima-global optima, exploration–exploitation, gradient descent, deterministic-stochastic approaches are visited thoroughly. Three optimization algorithms namely GA, PSO and ACO are studied in detail, in line with the manufacturing operations backed by mathematical theories.
Debojyoti Sarkar, Anupam Biswas
Potential Application of CEM43 °C and Arrhenius Model in Neurosurgical Bone Grinding
Abstract
This book chapter provides comprehensive information about the potential applications of thermal dose models in the neurosurgical bone grinding operations. Firstly, CEM43 °C thermal dose thresholds have been explained along with its in-vivo significance. Subsequently, the relationship between the Arrhenius model and CEM43 °C have been established and explained. The kinetic coefficients and recommendations made by the past researchers have been accentuated. The threshold levels of the thermal damage have been explained as reported by the previous researchers. The time–temperature relation of cell death has been discussed. It has been observed that two factors namely exposure time and exposure temperature determine the rate of cell killing. The temperature generated during the bone grinding operation is converted into the equivalent number of minutes at 43 °C since this temperature has been considered as the threshold for thermogenesis. However, bone necrosis has been reported at a temperature of 47 °C for 1 min of thermal exposure. In the present chapter, detailed in-vivo and in-vitro case studies have been provided to understand the use of thermal dose model in predicting the degree/level of tissue damage owing to the generation of heat amid bone grinding operation.
Atul Babbar, Vivek Jain, Dheeraj Gupta, Chander Prakash, Deepak Agrawal
An Effective Selection of Laser Cutter Used in Stent Manufacturing Through Fuzzy TOPSIS
Abstract
Nowadays, stents are very indispensable for medical fields. Particularly the patients who have problems with coronary artery disease are in the need of stent. Medical practitioners advise the patients to take stents for better treatment. There are different types of stents available with different laser cutting. Due to more requirements, patients prefer better beam quality, low cost, and high stability and reliability. Therefore, the present study aims to determine the most preferable laser cutter used in stent manufacturing by fuzzy TOPSIS method. Here, six types of lasers and six types of features of lasers are chosen as attributes and criteria respectively. By utilizing fuzzy TOPSIS with trapezoidal fuzzy number, the fiber laser is selected among six alternatives. Finally, this study concludes that fiber laser has high beam quality, low cost and high stability and reliability.
M. Stephen, A. Felix, A. Parthiban
Metadaten
Titel
Numerical Modelling and Optimization in Advanced Manufacturing Processes
herausgegeben von
Dr. Chander Prakash
Dr. Sunpreet Singh
Dr. Aminesh Basak
Prof. Dr. J. Paulo Davim
Copyright-Jahr
2022
Electronic ISBN
978-3-031-04301-7
Print ISBN
978-3-031-04300-0
DOI
https://doi.org/10.1007/978-3-031-04301-7

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