Powder bed generation in integrated modelling of additive layer manufacturing of orthopaedic implants

This paper presents an original model of powder bed generation developed within the frame of an integrated modelling approach for studying the interaction of physical mechanisms in additive layer manufacturing (ALM) of orthopaedic implants. The model is based on cellular automata (CA) approach and describes the relationship between moving particles of different sizes during deposition on a surface in three dimensions. The surface is defined by the horizontal two-dimensional CA on which particles fall and irreversibly stick to a growing deposit. The model allows for consideration of different restructuring cases when particles are allowed to rotate as often as necessary until achievement of a local minimum position. Changes in the packing density of the powder bed have been investigated numerically depending on technological parameters, such as particle size distribution, deposition rate and sequence of powder deposition. The model has been developed with the aim of merging to the finite element (FE)-based integrated model and is applicable to a different ranges of materials including metals and also non-metals

Selective laser sintering of hydroxyapatite-polyamide composites

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A hybrid M5 ′ -genetic programming approach for ensuring greater trustworthiness of prediction ability in modelling of FDM process

Recent years have seen various rapid prototyping (RP) processes such as fused deposition modelling (FDM) and three-dimensional printing being used for fabricating prototypes, leading to shorter product development times and less human intervention. The literature reveals that the properties of RP built parts such as surface roughness, strength, dimensional accuracy, build cost, etc are related to and can be improved by the appropriate settings of the input process parameters. Researchers have formulated physics-based models and applied empirical modelling techniques such as regression analysis and artificial neural network for the modelling of RP processes. Physics-based models require in-depth understanding of the processes which is a formidable task due to their complexity. The issue of improving trustworthiness of the prediction ability of empirical models on test (unseen) samples is paid little attention. In the present work, a hybrid M5 ′ -genetic programming (M5 ′ -GP) approach is proposed for empirical modelling of the FDM process with an attempt to resolve this issue of ensuring trustworthiness. This methodology is based on the error compensation achieved using a GP model in parallel with a M5 ′ model. The performance of the proposed hybrid model is compared to those of support vector regression (SVR) and adaptive neuro fuzzy inference system (ANFIS) model and it is found that the M5 ′ -GP model has the goodness of fit better than those of the SVR and ANFIS models

The use of rapid prototyping to assist medical applications

Purpose - This paper aims to illustrate a number of instances where RP and associated technology has been successfully used for medical applications. Design/methodology/approach - A number of medical case studies are presented, illustrating different uses of RP technology. These studies have been analysed in terms of how the technology has been applied in order to solve related medical problems. Findings - It was found that RP has been helpful in a number of ways to solve medical problems. However, the technology has numerous limitations that have been analysed in order to establish how the technology should develop in the future. Practical implications - RP can help solve medical problems, but must evolve if it is to be used more widespread in this field. Originality/value - This paper has shown a number of new applications for RP, providing a holistic understanding how the technology can solve medical problems. It also identifies a number of ways in which the technology can improve in order to better solve such problems. © Emerald Group Publishing Limited.link_to_subscribed_fulltex

Selective laser sintering of dental prostheses

status: publishe

Fabrication of porous bioactive structures using the selective laser sintering technique.

Hydroxyapatite, a ceramic with which natural bone inherently bonds, has been incorporated into a polymer matrix to enhance the bioactivity of implant materials. In order to manufacture custom-made bioactive implants rapidly, selective laser sintering has been investigated to fabricate hydroxyapatite and polyamide composites and their properties investigated. One objective of this research was to identify the maximum hydroxyapatite content that could be incorporated into the matrix, which was sintered at various parameters. The study focused on investigating the control of porosity and pore size of the matrix by manipulating the selective laser sintering parameters of the laser power and laser scan speed. The interception method was used to analyse the internal porous morphology of the matrices which were cross-sectioned through the vertical plane. Most notably, all structures built demonstrated interconnection and penetration throughout the matrix. Liquid displacement was also used to analyse the porosity of the matrices. The laser power showed a negative relationship between porosity and variation in parameter values until a critical power value was reached. However, the same relationship for laser scan speed matrices was inconsistent. The effects of the laser power and laser scanning speed on the features of porous structures that could influence cell spreading, proliferation, and bone regeneration are presented