Survey on Additive Manufacturing, Cloud 3D Printing and Services

Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure

Layerless fabrication with continuous liquid interface production

Despite the increasing popularity of 3D printing, also known as additive manufacturing (AM), the technique has not developed beyond the realm of rapid prototyping. This confinement of the field can be attributed to the inherent flaws of layer-by-layer printing and, in particular, anisotropic mechanical properties that depend on print direction, visible by the staircasing surface finish effect. Continuous liquid interface production (CLIP) is an alternative approach to AM that capitalizes on the fundamental principle of oxygen-inhibited photopolymerization to generate a continual liquid interface of uncured resin between the growing part and the exposure window. This interface eliminates the necessity of an iterative layer-by-layer process, allowing for continuous production. Herein we report the advantages of continuous production, specifically the fabrication of layerless parts. These advantages enable the fabrication of large overhangs without the use of supports, reduction of the staircasing effect without compromising fabrication time, and isotropic mechanical properties. Combined, these advantages result in multiple indicators of layerless and monolithic fabrication using CLIP technology

Characterization of shape and dimensional accuracy of incrementally formed titanium sheet parts with intermediate curvatures between two feature types

Single point incremental forming (SPIF) is a relatively new manufacturing process that has been recently used to form medical grade titanium sheets for implant devices. However, one limitation of the SPIF process may be characterized by dimensional inaccuracies of the final part as compared with the original designed part model. Elimination of these inaccuracies is critical to forming medical implants to meet required tolerances. Prior work on accuracy characterization has shown that feature behavior is important in predicting accuracy. In this study, a set of basic geometric shapes consisting of ruled and freeform features were formed using SPIF to characterize the dimensional inaccuracies of grade 1 titanium sheet parts. Response surface functions using multivariate adaptive regression splines (MARS) are then generated to model the deviations at individual vertices of the STL model of the part as a function of geometric shape parameters such as curvature, depth, distance to feature borders, wall angle, etc. The generated response functions are further used to predict dimensional deviations in a specific clinical implant case where the curvatures in the part lie between that of ruled features and freeform features. It is shown that a mixed-MARS response surface model using a weighted average of the ruled and freeform surface models can be used for such a case to improve the mean prediction accuracy within ±0.5 mm. The predicted deviations show a reasonable match with the actual formed shape for the implant case and are used to generate optimized tool paths for minimized shape and dimensional inaccuracy. Further, an implant part is then made using the accuracy characterization functions for improved accuracy. The results show an improvement in shape and dimensional accuracy of incrementally formed titanium medical implants

An Efficient Triangle Mesh Slicing Algorithm for All Topologies in Additive Manufacturing

To date, slicing algorithms for additive manufacturing are most effective for favourable triangular mesh topologies; worst case models, where a large percentage of triangles intersect each slice-plane, take significantly longer to slice than a like-for-like file. In larger files, this results in a significant slicing duration, when models are both worst case and contain more than 100,000 triangles. The research presented here introduces a slicing algorithm which can slice worst case large models effectively. A new algorithm is implemented utilising an efficient contour construction method, with further adaptations, which make the algorithm suitable for all model topologies. Edge matching, which is an advanced sorting method, decreases the number of sorts per edge from n total number of intersections to two, alongside additional micro-optimisations that deliver the enhanced efficient contour construction algorithm. The algorithm was able to slice a worst-case model of 2.5 million triangles in 1025s. Maximum improvement was measured as 9,400% over the standard efficient contour construction method. Improvements were also observed in all parts in excess of 1000 triangles. The slicing algorithm presented offers novel methods that address the failings of other algorithms described in literature to slice worst case models effectively

A modular multi electrode array system for electrogenic cell characterisation and cardiotoxicity applications

Multi electrode array (MEA) systems have evolved from custom-made experimental tools, exploited for neural research, into commercially available systems that are used throughout non-invasive electrophysiological study. MEA systems are used in conjunction with cells and tissues from a number of differing organisms (e.g. mice, monkeys, chickens, plants). The development of MEA systems has been incremental over the past 30 years due to constantly changing specific bioscientific requirements in research. As the application of MEA systems continues to diversify contemporary commercial systems are requiring increased levels of sophistication and greater throughput capabilities. [Continues.

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Challenges of additive manufacturing technologies from an optimisation perspective

Three-dimensional printing offers varied possibilities of design that can be bridged to optimisation tools. In this review paper, a critical opinion on optimal design is delivered to show limits, benefits and ways of improvement in additive manufacturing. This review emphasises on design constrains related to additive manufacturing and differences that may appear between virtual and real design. These differences are explored based on 3D imaging techniques that are intended to show defect related processing. Guidelines of safe use of the term “optimal design” are derived based on 3D structural information