Research for development in the 21st century

Optimizing Process Parameters of Direct Ink Writing for Dimensional Accuracy of Printed Layers

Direct ink writing (DIW) belongs to extrusion-based three-dimensional (3D) printing techniques. The success of DIW process depends on well-printable ink and optimized process parameters. After ink preparation, DIW process parameters considerably affect the parts' dimensional accuracy, and process parameters optimization for dimensional accuracy of printed layers is necessary for quality control of parts in DIW. In this study, DIW process parameters were identified and divided into two categories as the parameters for printing a line and the parameter from lines to a layer. Then, a two-step method was proposed for optimizing process parameters. Step 1 was to optimize process parameters for printing a line. In Step 1, continuity and uniformity of extruded filaments and printed rectangular objects were observed in screening experiments to determine printability windows for each process parameter. Then, interaction effect tests were conducted and degree of freedom for experiments was calculated followed by orthogonal array selection for the Taguchi design. Next, main experiments of line printing based on the Taguchi method were conducted. Signal-to-noise ratio calculations and analysis of variance were performed to find the optimal combination and evaluate the significance, respectively. Step 2 was to optimize the parameter from lines to a layer. In Step 2, the average width of the printed line under optimal condition was first measured. Then, single-factor tests of rectangular object printing were conducted to find the optimal parameter from lines to a layer. After these two steps, confirmation results were conducted to verify the reliability of the proposed method and the method robustness on other shapes and other materials; parameter adaptability in 3D parts printing from printed layers' analyses for the proposed method; and parameter adaptability in constructs fabricated as 100% infill or with porosities.

Development of biodegradable customized tibial scaffold with advanced architected materials utilizing additive manufacturing

In the last decade, the development of customized biodegradable scaffolds and implants has attracted increased scientific interest due to the fact that additive manufacturing technologies allow for the rapid production of implants with high geometric complexity constructed via commercial biodegradable polymers. In this study, innovative designs of tibial scaffold in form of bone-brick configuration were developed to fill the bone gap utilizing advanced architected materials and bio-inspired diffusion canals. The architected materials and canals provide high porosity, as well as a high surface area to volume ratio in the scaffold facilitating that way in the tissue regeneration process and in withstanding the applied external loads. The cellular structures applied in this work were the Schwarz Diamond (SD) and a hybrid SD&FCC hybrid cellular material, which is a completely new architected material that derived from the combination of SD and Face Centered Cubic (FCC) structures. These designs were additively manufactured utilizing two biodegradable materials namely Polylactic acid (PLA) and Polycaprolactone (PCL), using the Fused Filament Fabrication (FFF) technique, in order to avoid the surgery, for the scaffold's removal after the bone regeneration. Furthermore, the additively manufactured scaffolds were examined in terms of compatibility and assembly with the bone's physical model, as well as, in terms of mechanical behavior under realistic static loads. In addition, non-linear finite element models (FEMs) were developed based on the experimental data to accurately simulate the mechanical response of the examined scaffolds. The Finite Element Analysis (FEA) results were compared with the experimental response and afterwards the stress concentration regions were observed and identified. Τhe proposed design of scaffold with SD&FCC lattice structure made of PLA material with a relative density of 20% revealed the best overall performance, showing that it is the most suitable candidate for further investigation (in-vivo test, clinical trials, etc.) and commercialization.

Starch as edible ink in 3D printing for food applications: a review

Three-dimensional (3D) printing has attracted more attention in food industry because of its potential advantages, including the ability to create customized products according to individual's sensory or nutritional requirements. However, the production of high-quality 3D printed foods requires the availability of edible bio-inks with the required physicochemical and sensory attributes. Starch, as one of the important sources of dietary energy, is widely used in food processing and is considered as one kind of versatile polymers. It is not only because starch has low prices and abundant sources, but also because desirable modified starch can be obtained by altering its physicochemical properties through physical, chemical and enzymatic methods. This article focuses on the utilization of starch as materials to create food-grade bio-inks. Initially, several kinds of commonly used 3D printers are discussed. The factors affecting the printing quality of starch-based materials and improvement methods are then reviewed, as well as areas where future researches are required. The applications of 3D printed starch-based materials in food industry are also introduced. Overall, starch appears to be one kind of useful substances for creating edible bio-inks that can be utilized within 3D food printing applications to create a wide variety of food products.

Smart Strawberry Farming Using Edge Computing and IoT

Strawberries are sensitive fruits that are afflicted by various pests and diseases. Therefore, there is an intense use of agrochemicals and pesticides during production. Due to their sensitivity, temperatures or humidity at extreme levels can cause various damages to the plantation and to the quality of the fruit. To mitigate the problem, this study developed an edge technology capable of handling the collection, analysis, prediction, and detection of heterogeneous data in strawberry farming. The proposed IoT platform integrates various monitoring services into one common platform for digital farming. The system connects and manages Internet of Things (IoT) devices to analyze environmental and crop information. In addition, a computer vision model using Yolo v5 architecture searches for seven of the most common strawberry diseases in real time. This model supports efficient disease detection with 92% accuracy. Moreover, the system supports LoRa communication for transmitting data between the nodes at long distances. In addition, the IoT platform integrates machine learning capabilities for capturing outliers in collected data, ensuring reliable information for the user. All these technologies are unified to mitigate the disease problem and the environmental damage on the plantation. The proposed system is verified through implementation and tested on a strawberry farm, where the capabilities were analyzed and assessed.