Process parameter optimization for direct metal laser sintering (DMLS)

Ph.DDOCTOR OF PHILOSOPH

Shrinkage behaviour of semi-crystalline polymers in laser sintering: PEKK and PA12

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordShrinkage is extensively mentioned in the literature as one of the main causes for dimensional instability or poor performance in Laser Sintering (LS). This study proposes and examines a methodology to describe shrinkage in cooling from a material perspective. Thermal behaviour and crystallisation effects were measured to determine the influence of powder structure and density on overall LS shrinkage. PEKK and PA12 powders were used to assess such behaviour in LS. The shrinkage parameter associated with powder bulk properties has the greatest impact in PEKK, contributing to 57% of the total shrinkage observed in cooling for this material as supported by the low values of bulk density, irregular morphology and internal porosity observed for these particles. For PA12, crystallisation is responsible for 60% of the overall shrinkage observed. In LS, PEKK shows an overall shrinkage approximately 30% lower than PA12, which makes it a promising material for maintaining final part dimensions.Arkema Innovations Chemistr

Study on Parametric Optimization of Fused Deposition Modelling (FDM) Process

Rapid prototyping (RP) is a generic term for a number of technologies that enable fabrication of physical objects directly from CAD data sources. In contrast to classical methods of manufacturing such as milling and forging which are based on subtractive and formative principles espectively, these processes are based on additive principle for part fabrication. The biggest advantage of RP processes is that an entire 3-D (three-dimensional) consolidated assembly can be fabricated in a single setup without any tooling or human intervention; further, the part fabrication methodology is independent of the mplexity of the part geometry. Due to several advantages, RP has attracted the considerable attention of manufacturing industries to meet the customer demands for incorporating continuous and rapid changes in manufacturing in shortest possible time and gain edge over competitors. Out of all commercially available RP processes, fused deposition modelling (FDM) uses heated thermoplastic filament which are extruded from the tip of nozzle in a prescribed manner in a temperature controlled environment for building the part through a layer by layer deposition method. Simplicity of operation together with the ability to fabricate parts with locally controlled properties resulted in its wide spread application not only for prototyping but also for making functional parts. However, FDM process has its own demerits related with accuracy, surface finish, strength etc. Hence, it is absolutely necessary to understand the shortcomings of the process and identify the controllable factors for improvement of part quality. In this direction, present study focuses on the improvement of part build methodology by properly controlling the process parameters. The thesis deals with various part quality measures such as improvement in dimensional accuracy, minimization of surface roughness, and improvement in mechanical properties measured in terms of tensile, compressive, flexural, impact strength and sliding wear. The understanding generated in this work not only explain the complex build mechanism but also present in detail the influence of processing parameters such as layer thickness, orientation, raster angle, raster width and air gap on studied responses with the help of statistically validated models, microphotographs and non-traditional optimization methods. For improving dimensional accuracy of the part, Taguchi‟s experimental design is adopted and it is found that measured dimension is oversized along the thickness direction and undersized along the length, width and diameter of the hole. It is observed that different factors and interactions control the part dimensions along different directions. Shrinkage of semi molten material extruding out from deposition nozzle is the major cause of part dimension reduction. The oversized dimension is attributed to uneven layer surfaces generation and slicing constraints. For recommending optimal factor setting for improving overall dimension of the part, grey Taguchi method is used. Prediction models based on artificial neural network and fuzzy inference principle are also proposed and compared with Taguchi predictive model. The model based on fuzzy inference system shows better prediction capability in comparison to artificial neural network model. In order to minimize the surface roughness, a process improvement strategy through effective control of process parameters based on central composite design (CCD) is employed. Empirical models relating response and process parameters are developed. The validity of the models is established using analysis of variance (ANOVA) and residual analysis. Experimental results indicate that process parameters and their interactions are different for minimization of roughness in different surfaces. The surface roughness responses along three surfaces are combined into a single response known as multi-response performance index (MPI) using principal component analysis. Bacterial foraging optimisation algorithm (BFOA), a latest evolutionary approach, has been adopted to find out best process parameter setting which maximizes MPI. Assessment of process parameters on mechanical properties viz. tensile, flexural, impact and compressive strength of part fabricated using FDM technology is done using CCD. The effect of each process parameter on mechanical property is analyzed. The major reason for weak strength is attributed to distortion within or between the layers. In actual practice, the parts are subjected to various types of loadings and it is necessary that the fabricated part must withhold more than one type of loading simultaneously.To address this issue, all the studied strengths are combined into a single response known as composite desirability and then optimum parameter setting which will maximize composite desirability is determined using quantum behaved particle swarm optimization (QPSO). Resistance to wear is an important consideration for enhancing service life of functional parts. Hence, present work also focuses on extensive study to understand the effect of process parameters on the sliding wear of test specimen. The study not only provides insight into complex dependency of wear on process parameters but also develop a statistically validated predictive equation. The equation can be used by the process planner for accurate wear prediction in practice. Finally, comparative evaluation of two swarm based optimization methods such as QPSO and BFOA are also presented. It is shown that BFOA, because of its biologically motivated structure, has better exploration and exploitation ability but require more time for convergence as compared to QPSO. The methodology adopted in this study is quite general and can be used for other related or allied processes, especially in multi input, multi output systems. The proposed study can be used by industries like aerospace, automobile and medical for identifying the process capability and further improvement in FDM process or developing new processes based on similar principle

Fundamental Understanding of Poly(ether ketone ketone) for High Temperature Laser Sintering

High-Temperature Laser Sintering (HT-LS) is a powder bed fusion technique employed to manufacture polymers with high service temperature, usually above 150 oC. The aerospace, automotive, and medical industries have driven the demand for processing high-performance polymers, as they could offer a lighter and cheaper alternative while maintaining the mechanical and chemical performance required to replace metallic parts in particular environments. Kepstan 6002 poly(ether ketone ketone) (PEKK) belongs to poly(aryl ether ketone)s (PAEKs) family and has a promising application in LS. The lower melting temperature united to the high glass transition temperature of PEKK (similar to PEK HP3, first commercially available HT-LS grade) enabled processing at lower temperatures whilst maintaining the high-temperature resistance of the polymer. Furthermore, the kinetics of crystallisation of Kepstan 6002 PEKK is very slow, which can assist layer adhesion during LS and improve mechanical properties in Z orientation. The present research project was developed in collaboration with Arkema. Three different grades of Kepstan 6002 PEKK were selected for initial analyses – HL1327, HL1320, and P12S959a. The powders were characterised for powder size, distribution, morphology, flow, moisture effect, and coalescence behaviour. This screening enabled the selection of HL1327 grade as the most promising for HT-LS application. The PEKK particle and powder analyses continued with an in-depth study of particle size and shape changes as a function of temperature and coalescence. The study revealed individual particle shrinkage prior to melting, followed by increased growth. The same phenomenon was observed for pairs of particles during coalescence and was attributed to the recovering of elastic deformation of the polymeric chains. The effect of intrinsic PEKK characteristics was successfully evaluated and quantified in the overall shrinkage in LS. The results identified powder properties as the main factor causing shrinkage of PEKK, as opposed to crystallisation. These results are supported by the powder characterisation developed in previous chapters. The interaction between material and process was investigated and optimised by testing different combinations of laser parameters and processing temperatures. The resulting properties were monitored regarding mechanical performance, surface topography, porosity, and crystallisation. The optimised PEKK specimens showed excellent mechanical strength (∼90 MPa) and modulus, but poor elongation, a common drawback from the LS process. The combination of fundamental material properties and process optimisation led to the development of a novel route to improve elongation and control the mechanical performance of LS PEKK. The experimental method successfully related cooling time, mechanical properties, and crystallisation of PEKK, and was able to increase elongation at break by 5.4 times. The improvement of elongation at break was attributed to the largely amorphous phase of PEKK when subjected to short cooling times. Lastly, powder recyclability was investigated from a chemical and physical perspective. PEKK can be reused following additional treatment steps, e.g., sieving. The potential for recyclability is an important remark as the material cost is significantly reduced and therefore preferred over the use of metals for high-performance applications

Modeling and simulation of surface generation in manufacturing

The paper describes the state-of-the-art in modeling and simulation of surface texture and topography generation at micro and nano dimensional scales. Three main classes of manufacturing processes used for the generation of engineering surfaces are considered: material removal processes, material conservative processes, and material additive processes. Types of modeling techniques for the simulation of surface generation are reviewed and discussed including analytical models, numerical multi-physics models, and data-driven methods. After presenting the application of those modeling techniques for the prediction of characteristics and geometry of surfaces generated by different manufacturing processes, their performance, implementation, and accuracy are discussed. Finally, a roadmap for the realization of a complete surface generation digital twin in manufacturing is outlined

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808