This course is verified by Probitas Authentication as meeting the AS9104/3A requirements for continuing Professional Development. In the Aerospace Industry there is a focus on Defect Prevention to ensure that quality goals are met. Failure Mode and Effects Analysis (PFMEA) and Control Plan activities are recognized as being one of the most effective, on the journey to Zero Defects. This two-day course is designed to explain the core tools of Design Failure Mode and Effects Analysis (DFMEA), Process Flow Diagrams, Process Failure Mode and Effects Analysis (PFMEA) and Control Plans as described in AS13100 and RM13004.
In applications demanding high performance under extreme conditions of pressure and temperature, a range of Mechanically Attached Fittings (MAFs) is offered by various Multinational Corporations (MNCs). These engineered fittings have been innovatively designed to meet the rigorous requirements of the aerospace industry, offering a cost-effective and lightweight alternative to traditional methods such as brazing, welding, or other mechanically attached tube joints. One prominent method employed for attaching these fittings to tubing is through Internal Swaging, a mechanical technique. This process involves the outward formation of rigid tubing into grooves within the fitting. One of the methods with which this intricate operation is achieved is by using a drawbolt - expander assembly within an elastomeric swaging machine.
Selective Laser Melting (SLM) has gained widespread usage in aviation, aerospace, and die manufacturing due to its exceptional capacity for producing intricate metal components of highly complex geometries. Nevertheless, the instability inherent in the SLM process frequently results in irregularities in the quality of the fabricated components. As a result, this hinders the continuous progress and wider acceptance of SLM technology. Addressing these challenges, in-process quality control strategies during SLM operations have emerged as effective remedies for mitigating the quality inconsistencies found in the final components. This study focuses on utilizing optical emission spectroscopy and IR thermography to continuously monitor and analyze the SLM process within the powder bed, with the aim of strengthening process control and minimizing defects.
Bio-composites have gained significant attention within the aerospace industry due to their potential as a sustainable solution that addresses the demand for lightweight materials with reduced environmental impact. These materials blend natural fibers sourced from renewable origins, such as plant-based fibers, with polymer matrices to fabricate composite materials that exhibit desirable mechanical properties and environmental friendliness. The aerospace sector's growing interest in bio-composites originates from those composites’ capacity to mitigate the industry's carbon footprint and decrease dependence on finite resources. This study aims to investigate the suitability of utilizing plant derived flax fabric/PLA (polylactic acid) matrix-based bio-composites in aerospace applications, as well as the recyclability potential of these composites in the circular manufacturing economy.
This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. This course provides both a functional understanding of the principles involved in conducting a Design for Manufacture/Design for Assembly (DFM/DFA) study and the process for implementing a DFM/DFA culture into the organization.
Design for Manufacturing and Assembly (DFM+A), pioneered by Boothroyd and Dewhurst, has been used by many companies around the world to develop creative product designs that use optimal manufacturing and assembly processes. Correctly applied, DFM+A analysis leads to significant reductions in production cost, without compromising product time-to-market goals, functionality, quality, serviceability, or other attributes. In this two-day course, you will not only learn the Boothroyd Dewhurst Method, you will actually apply it to your own product design!
This work puts forward an original autonomous planning and control framework addressing inherent modeling complexity limit through efficient heterosis between latency-connective graph estimation and generative exploration with an aim to enhance trajectory quality and resiliency in unpredicted conditions. The holistic approach encompasses state and cost prediction facilitated via morphable signature mechanism utilizing anti-cloak characteristics derived from environmental graph. In principle, a dynamic graph neural network is proposed with regards to adaptively capture essential influence caused by interactive agents and reciprocal belief augmentation. Moreover, high efficiency exploration is concerted with signature-enhanced prediction system for non-ideal perception conditions. The exploration scheme takes advantage of confidence optimization function to generate trajectory refinement over non-conventional operating circumstances.
To satisfy recent stringent exhaust gas regulations, large amounts of Rh and Pd have been often employed in three-way catalysts (TWCs) as main active components. However, application of Pt-based TWCs are limited due to their lower thermal stability than Pd. Previously, we found that Pt-based TWCs with a small amount of CeO2 showed high catalytic performance in gasoline vehicles test. Especially, calcined CeO2 at high temperature before Pt loading (cal-CeO2) showed higher catalytic activity than untreated CeO2 after endurance at 1000 degree centigrade. This result could be attributed to higher redox performance and Pt dispersion derived from strong interaction between Ce and Pt. Even though cal-CeO2 has low specific surface area (SSA) given by preliminary calcination, it shows strong effects on catalytic performance. In other word, improvement of its SSA could be the most powerful way to prepare highly active Pt catalysts.
Heavy vehicles such as construction machinery generally require a large traction force. For this reason, axle components are equipped with a final reduction gear to provide a structure that can generate a large traction force. Basic analysis of vertical load, horizontal load (traction force), centrifugal force, and torsional torque applied to the wheels of heavy vehicles such as construction machinery and industrial vehicles, as well as actual working load analysis during actual operations, were conducted and compiled into a load analysis diagram. The loosening tendency of wheel bolts and nuts that fasten the wheel under actual working load was measured, and the loosening analysis method was presented. The causes of wheel fall-off accidents in heavy trucks, which have recently become a problem, were examined. Wheel bolts are generally tightened by the calibrated wrench method using a torque wrench.
In electric vehicle applications, the majority of the traction motors can be categorized as Permanent Magnet (PM) motors due to their outstanding performance. As indicated in the name, there are strong permanent magnets used inside the rotor of the motor, which interacts with the stator and causes strong magnetic pulling force during the assembly process. How to estimate this magnetic pulling force can be critical for manufacturing safety and efficiency. In this paper, a full 3D magnetostatic model has been proposed to calculate the baseline force using a dummy non-slotted cylinder stator and a simplified rotor for less meshing elements. Then, the full 360 deg model is simplified to a 90deg quarter model based on motor symmetry to save the simulation time from 2 days to 4 hours. A rotor position sweep was conducted using the quarter model to find the max pulling force position. The result shows that the max pulling force happens when the rotor is 1mm overlapping with the stator core.
A crucial component utilized in the trunk space is the luggage board. Positioned at the bottom of the trunk, the luggage board separates the vehicle body from the interior and provides support for luggage.The luggage board serves multiple functions, including load-bearing stiffness for luggage, partition structure functionality, noise insulation, and thermal insulation. To meet the increasing demand for luggage boards in response to the changing market environment, there is a need for a competitive new luggage board manufacturing method. To address this, the "integrated sandwich molding method" is required. The integrated sandwich molding method utilizes three key methodologies: grouping processes to integrate similar functions, analyzing materials to replace them with suitable alternatives, and overcoming any lacking functionality through integrated design structures.
Side doors are pivotal components of any vehicle, not only for their aesthetic and safety aspects but also due to their direct interaction with customers. Therefore, ensuring good structural performance of side doors is crucial, especially under various loading conditions during vehicle use. Among the vital performance criteria for door design, torsional stiffness plays an important role in ensuring an adequate life cycle. This paper focuses on investigating the impact of several door structural parameters on the torsional stiffness of side doors. These parameters include the positioning of the latch, the number of hinge mounting points on doors (single or double bolt), and the design of inner panel with or without Tailor Welded Blank (TWB) construction.
A lot of parts about 20,000 to 40,000 are composed of a car. When developing new car, design, manufacturing, cost, quality control and etc. are reviewed for these parts. In order to develop parts with low price and high quality, various factors such as design, manufacturing and cost need to optimize specifications for each part in development stage. In particular, this optimization is most effective when it is done at the design stage. A comprehensive review should be made based on various information such as design, manufacturing and cost for each component to optimize these specifications. However, the information is managed separately by each development department, so access to the information is limited. In addition, there are many inefficiencies in generating, searching, analyzing and processing the information.