Search for: All records

Abstract Fused deposition modeling (FMD) is considered one of the most common additive manufacturing methods for creating prototypes and small functional parts. Many researchers have studied Polylactic acid (PLA), Polycarbonate (PC), and Acrylonitrile butadiene styrene (ABS) as a material for fused deposition modeling printing. Among them, Polylactic Acid (PLA) is considered one of the most popular thermoplastic materials due to its low cost and biodegradable properties. In this study, silk PLA material was used. In Fused deposition modeling (FMD), the selection of printing parameters plays a pivotal role in determining the overall quality and integrity of the 3D-printed products. These parameters significantly influence the quality and strength of 3-D printed products. This study investigates the mechanical properties of silk-PLA printed specimens under different printing conditions, such as layer thickness, nozzle temperature, and print speed. All the tensile specimens were tested using ASTM D638 to characterize Young’s modulus and ultimate tensile strength. The thickness of the layers of tensile specimens was set to 0.1 mm, 0.15 mm, and 0.2 mm. The temperatures of the nozzle used during printing varied from 200°C, 210°C, and 220°C, whereas print speeds of 100 mm/s, 120 mm/s, and 140 mm/s were considered. The other printing parameters were kept consistent for all specimens. The result indicates tensile strength generally increases with increasing temperature of the nozzle, up to 220°C; however, a decline was observed in the average Young’s modulus value when the thickness of the layer increased from 0.10 mm to 0.20 mm. According to the results of the ANOVA analysis, the interaction between layer thickness, nozzle temperature, and printing speed significantly affects the tensile strength and Young’s modulus of Silk-PLA. This study reveals that nozzle temperature is the most critical parameter regarding the ultimate tensile strength and Young’s modulus, providing crucial insights for optimizing 3D printing parameters. 

Abstract Additive manufacturing, an innovative process that assembles materials layer by layer from 3D model data, is recognized as a transformative technology across diverse industries. Researchers have extensively investigated the impact of various printing parameters of 3D printing machines, such as printing speed, nozzle temperature, and infill, on the mechanical properties of printed objects. Specifically, this study focuses on applying Finite Element Analysis (FEA) in G code modification in Fused Deposition Modeling (FDM) 3D Printing. FDM involves extruding a thermoplastic filament in layers over a build plate to create a three-dimensional object. In the realm of load-bearing structures, the Finite Element Analysis (FEA) process is initiated on the target object, employing the primary load to identify areas with high-stress concentrations. Subsequently, optimization techniques are used to strategically assign printing parameter combinations to improve mechanical properties in potentially vulnerable regions. The ultimate objective is to tailor the G code, a set of instructions for the printer, to strengthen particular areas and improve the printed object’s overall structural integrity. To evaluate the suggested methodology’s efficacy, the study conducts a comprehensive analysis of printed objects, both with and without the optimized G code. Simultaneously, mechanical testing, such as tensile testing, demonstrates quantitative data on structural performance. This comprehensive analysis aims to identify the impact of G code alteration on the finished product. Preliminary experimental results using simple tensile specimens indicate notable improvements in structural performance. Importantly, these improvements are achieved without any discernible mass increase, optimizing material usage and reducing the cost of additive manufacturing. The modified G code targets to strengthen critical areas using updated printing parameters without a net increase in the overall material consumption of the object. This finding holds significant implications for industries reliant on additive manufacturing for load-bearing components, offering a promising avenue for improved efficiency and durability. Integrating advanced techniques, such as G code modification and finite element analysis (FEA), as the additive manufacturing landscape evolves presents a pathway toward optimizing mechanical properties. By contributing valuable insights and laying the groundwork for further exploration and refinement of these methodologies, this study paves the way for enhanced structural performance in various additive manufacturing applications. Ultimately, it encourages innovation and progress in the field, propelling the industry toward new heights of efficiency and reliability. 

This Work-in-progress paper presents the pilot study of implementing a Virtual Reality (VR) environment to teach a junior-level Mechanical Engineering laboratory class at Prairie View A&M University. The target class is the manufacturing processes laboratory, which initially aimed to provide a hands-on experience with various manufacturing equipment. Providing students with systematic training followed by repetitive access to manufacturing equipment is required for longer knowledge retention and safety in laboratories. Yet, complications from the pandemic and other logistical events have negatively affected many universities' laboratory courses. The objective of this study is to examine the potential and effectiveness of the VR framework in engineering education. More specifically, this paper details the project's first phase, which includes the development and deployment of machining VR modules and preliminary outcomes. The VR module in this phase is based on the existing hammer fabrication project that requires the utilization of a milling machine, drill press, lathe, tap, and threading dies. A virtual replica of the machining laboratory was created using C# and the unity 3D game engine and published as an Android Package Kit (APK) for the META platform to be used in Oculus Quest 2 devices. The module is composed of three submodules, each corresponding to different hammer parts. These VR submodules replace traditional verbal and video training and are deployed in two semesters with 46 student participants. The student performance in project reports is compared with a control group for a quantitative assessment. Early conclusions indicate that the students remember the operation procedures and functions of equipment longer and are more confident in operating each manufacturing equipment leading to better quality parts and reports. 

The frontal impact is the most common in automotive collision accidents, and bending the sub-frame can directly lead to severe passenger injury and property damage. This research analyzed the crashworthiness, design, mechanical integrity, and optimization of an automotive front sub-frame structure. From the original geometry, a new sub-frame with similar mass and mounting locations is designed. Loads were applied to the front side members of the sub-frame to simulate a common frontal and partial frontal crash. A sub-frame with enhanced structural efficiency was designed using topology optimization. This improvement may preserve the lifespan of the sub-frame, reinforce the protection of passengers and the engine, and improve crashworthiness. Topology optimization is a numerical analysis technique that allows engineers to distribute materials optimally for a specific cost function. Iterative update of design variables typically relies on sensitivity information from performance analysis in each step. A simple parametric study on material candidates and design constraints was executed to evaluate various design options. Sub-frames with optimized geometries were mechanically tested against two different simplified loads mimicking frontal crashes. The dynamic behaviors were also analyzed and compared to the original design for validation.