Mohammad Azar Bargir, Nitin G. Phafat, and Vijya Sonkamble
Advances in Oral and Maxillofacial Surgery, Vol 12, Iss , Pp 100447- (2023)
Ti 6Al–4V alloy, Zirconia, Co–Cr–Mo alloy additive manufacturing, Osteoarthritis, Knee joint, FDM, Internal medicine, RC31-1245, Surgery, and RD1-811
Additive manufacturing (Rapid Prototyping) is a significant innovation in medical field. It allows scientists to create custom-made parts that are often more precise and robust than their standard counterparts. Osteoarthritis (OA) is very common and serious problems in aging people. It is a progressive disease that affects the cartilage, the substance that cushions the bones and joints. Artificial knee joints are being developed as a sort of replacement for the human knee joint. One of the most intricate parts of the human body is the knee joint. This complex joint comprises of a ball-and-socket relationship, which is a very difficult part of the anatomy to design. The joint consists of both the kneecap and the Cartilage, and it has been designed with the intention of having the joint supported by a bone, rather than a cartilage. In this review article the results of a recent study, which was performed by researchers from the various renowned universities of Europe & United States of America over Artificial Knee Joint by Additive Manufacturing Technology.
Cleaner Engineering and Technology, Vol 17, Iss , Pp 100683- (2023)
Post-consumer recycling, Circular economy, Metalized film, Thermal properties, Mechanical properties, Renewable energy sources, TJ807-830, Environmental engineering, and TA170-171
In the recycling point of view, the metalized plastic film is widely known to be one of the most difficult materials to be recycled due to its structural complexity. This paper investigates the effects of the ground metalized-plastic film (MF) as a filler and reinforcement in recycled polypropylene (rPP) packaging to produce a new material through circular economy. MF was incorporated to rPP from 2 to 10 wt% and it was processed by using a twin-screw extruder and an injection molding machine. For MF, elemental analysis, and x-ray diffractometer (XRD) confirmed the existence of C, O, and Al, while the differential scanning calorimetry (DSC) result evidenced the melting position of linear-low density polyethylene (LLDPE). For, rPP/MF composites, MF was found to significantly reinforce rPP with the increased tensile strength. A maximum increase of the tensile strength by around 33% was observed when MF was added at 8 wt%. Elongation at break was found to reduce with MF loading. However, there was no significant difference among rPP with 6–10 wt% MF. DSC results indicated the shifts of both crystallization and melting peaks together with the reduction of the degree of crystallinity (Xc). Based on the tensile strength, tensile elongation at break results together with the statistical analysis and waste utilization issues, the rPP with 10 wt% MF formulation was selected as a final product prototyping.
Computer vision systems use corner detection to identify features in an image. In applications such as motion detection, tracking, picture registration, and object recognition, corner detection is often one of the initial steps. In this paper, a real-time image processing system based on Harris corner detection was designed and implemented using Zynq architecture and model-based design tools. The system was based on a development board containing the Zynq-7000 chip, which consists of a combination of FPGA and microprocessor, and the image taken with a high-resolution camera was processed in real-time by applying color conversion and Harris corner detection. The filter hardware designs used in the system were made using the HDL Coder tool in Matlab/Simulink without writing HDL code. The hardware that receives images from the camera was designed on a model-based basis with the Xilinx Vivado 2020. The HDL code that was implemented on the Xilinx ZedBoard using Vivado software was then validated to ensure real-time operation with the incoming video stream. The results achieved exhibited superiority compared to prior implementations in terms of area efficiency (reduced number of gates on the target FPGA) and speed performance on an identical target card. Using the rapid prototyping approach, two alternative hardware accelerator designs were created using various high-level synthesis tools. This design used less than 50% of the host FPGA's logic resources and was at least 30% faster than current implementations.
Jonah Meyerhoff, Rachel Kornfield, Emily G. Lattie, Ashley A. Knapp, Kaylee P. Kruzan, Maia Jacobs, Caitlin A. Stamatis, Bayley J. Taple, Miranda L. Beltzer, Andrew B.L. Berry, Madhu Reddy, David C. Mohr, and Andrea K. Graham
Internet Interventions, Vol 34, Iss , Pp 100677- (2023)
Digital mental health, Human-centered design, Methodology, Information technology, T58.5-58.64, Psychology, and BF1-990
As digital mental health interventions (DMHIs) proliferate, there is a growing need to understand the complexities of moving these tools from concept and design to service-ready products. We highlight five case studies from a center that specializes in the design and evaluation of digital mental health interventions to illustrate pragmatic approaches to the development of digital mental health interventions, and to make transparent some of the key decision points researchers encounter along the design-to-product pipeline. Case studies cover different key points in the design process and focus on partnership building, understanding the problem or opportunity, prototyping the product or service, and testing the product or service. We illustrate lessons learned and offer a series of questions researchers can use to navigate key decision points in the digital mental health intervention (DMHI) development process.
Large-scale pretrained language models have been a revolution in human-machine communication. Recently, such language models also generate code for required tasks. The objective of this work is to evaluate the functionality of the codes generated by ChatGPT (version 15-Dec-2022) for point cloud processing. The programming language selected for the test was MATLAB due to the extensive use in prototyping and toolboxes for Computer Vision and LiDAR. Using the Question-Answer system, the ChatGPT was asked for codes to calculate surface normals, curvature, eigenvalues, and eigenfeatures, with specific parameters and outputs. The provided codes were compiled and executed. The results show that ChatGPT can generate functional code for very specific and short applications, however, it is not capable of generating large code involving the correct use of loops, indexes, or equations.
Malgorzata A. Zboinska, Sanna Sämfors, and Paul Gatenholm
Materials & Design, Vol 236, Iss , Pp 112472- (2023)
Nanocellulose, Alginate, Hydrogel, Films, 3D printing, Architectural design, Materials of engineering and construction. Mechanics of materials, and TA401-492
Cellulose nanofibril hydrogel mixed with an aqueous solution of sodium alginate is a novel bio-based material suitable for 3D printing of lightweight membranes with exquisite properties and sustainable traits. However, fundamental knowledge enabling its applications in architectural design is still missing. Hence, this study examines the macro-scale features of lightweight membranes from cellulose nanofibril-alginate hydrogel, relevant for the design of various interior architectural products, such as wall claddings, ceiling tiles, room partitions, tapestries, and window screens. Through iterative prototyping experiments involving robotic 3D printing of lightweight membranes, their upscaling potential is demonstrated. Correlations between toolpath designs and shrinkages are also characterized, alongside an in-depth analysis of coloration changes upon ambient drying. Further, the tunability potential of various architectural features, enabled by bespoke 3D printing toolpath design, is discussed and exemplified. The aim is to expose the wide palette of design possibilities for cellulose nanofibril-alginate membranes, encompassing variations in curvature, porosity, translucency, texture, patterning, pliability, and feature sizes. The results comprise an important knowledge foundation for the design and manufacturing of custom lightweight architectural products from cellulose nanofibril-alginate hydrogel. These products could be applied in a variety of new bio-based, sustainable interior building systems, replacing environmentally harmful, fossil-based solutions.
In the single point incremental hole flanging (SPIHF) process, a sheet material with pre-cut holes is deformed using the SPIF technique to generate a flange, making it an effective approach for low volume manufacturing and quick prototyping. In the case of the SPIHF technique, the post-forming hardness property, the forming limit diagram (FLD), and spring-back phenomena are not completely evaluated. To this end, this paper employs experimental investigation and numerical validation to analyse the impact of SPIHF process parameters like tool diameter, feed rate, spindle speed, and initial hole diameter on these aspects for the truncated incrementally formed components made from AA1060 aluminium alloy and DC01 carbon steel. The plasticity behaviour of both sheet metals was simulated using the Workbench LS-DYNA model and ANSYS software version 18. Additionally, Cowper Symonds power-law hardening was added to the model to account for material properties. The average post-hardness of AA1060 and DC01 was evaluated using an SPIHF prediction model based on the performance of an artificial neural network (ANN). This ANN model was developed using a feed-forward back-propagation network trained using the Levenberg-Marquardt approach. The ANNs 4-n-1 were created by varying the transfer functions and the number of hidden neurons. Greater spindle speed and bigger pre-cut holes were shown to significantly increase the post-formed hardness of the truncated components, whereas the converse was seen when using a higher feed rate and a larger tool diameter. In addition, the FLD and spring-back improved dramatically with larger hole diameters. Employing correlation coefficient (R) and mean square error (MSE) as validation measures, it was shown that the established ANN models accurately predicted the SPIHF process response. Both the DC01 and AA1060 neural network models with a 4-8-1 network architecture performed very well, with MSE and R values of 0.0000105 and 1 for DC01 and 0.02613 and 0.99982 for AA1061.
Mitchell A. Gabalski, Kylie R. Smith, Jeremy Hix, and Kurt R. Zinn
Science and Technology of Advanced Materials, Vol 24, Iss 1 (2023)
Biomedical imaging, 3D printing, prototyping, material science, polymer characterization, Materials of engineering and construction. Mechanics of materials, TA401-492, Biotechnology, and TP248.13-248.65
ABSTRACTIn biomedical imaging, it is desirable that custom-made accessories for restraint, anesthesia, and monitoring can be easily cleaned and not interfere with the imaging quality or analyses. With the rise of 3D printing as a form of rapid prototyping or manufacturing for imaging tools and accessories, it is important to understand which printable materials are durable and not likely to interfere with imaging applications. Here, 15 3D printable materials were evaluated for radiodensity, optical properties, simulated wear, and capacity for repeated cleaning and disinfection. Materials that were durable, easily cleaned, and not expected to interfere with CT, PET, or optical imaging applications were identified.
Aakanksha Pant, Phoebe Xin Ni Leam, Chee Kai Chua, and U-Xuan Tan
Virtual and Physical Prototyping, Vol 18, Iss 1 (2023)
3d food printing, extrusion, food waste, sustainability, dysphagia, hydrocolloids, Science, Manufactures, and TS1-2301
Food waste utilisation and zero waste approach are among the many ways of building a sustainable economy. Food waste as authentic edible food being accepted by the consumers still has many barriers to overcome. One tool to help in the valorisation of food waste to value-added products is three-dimensional food printing (3DFP). These products can lead to easier and greater acceptance of food waste by consumers, having familiar nature with respect to taste, texture and appearance as other consumables. In the present study, food ink recipes were formulated from spinach stems and kale stalks, the common green leafy vegetable wastes. These spinach and kale inks were then characterised on their rheological properties of shear thinning and yield stress. The inks were subjected to IDDSI tests meant for standardisation of soft foods for dysphagia patients. This paper demonstrates ways of converting vegetable wastes into edible diets that are aesthetically pleasing through 3DFP.
ABSTRACTThe dynamic landscape of additive manufacturing (AM) is undergoing a transformative phase with the advent of multiple wire arc AM (MWAAM) processes. This systematic review offers an exhaustive exploration of the latest advancements and multifaceted applications of these innovative techniques within the realms of AM and welding. Prominently discussed processes encompass Bi-Metallic Wire Arc Additive Manufacturing, Twin Wire Arc Additive Manufacturing, Tandem Gas Metal Arc Welding, Twin-Wire Plasma Arc Additive, and Hybrid Wire Arc Additive Manufacturing. These techniques, instrumental in fabricating an array of materials from titanium aluminides to low-carbon steel, underscore the versatility and potential of modern AM. The application breadth spans key industries such as aerospace, naval, automotive, and energy, highlighting the ubiquity and relevance of these processes. While they promise enhanced productivity, improved material attributes, and economic efficiencies, challenges persist, including the need for meticulous parameter control, an in-depth grasp of foundational physics, and the development of sophisticated predictive models. Projecting into the future of AM, this review anticipates a harmonised integration of computational advancements with automation, positioning these MWAAM processes as pivotal in the next wave of manufacturing innovations.