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 of Experiments (DOE) is a methodology that can be effective for general problem-solving, as well as for improving or optimizing product design and manufacturing processes. Specific applications of DOE include identifying proper design dimensions and tolerances, achieving robust designs, generating predictive math models that describe physical system behavior, and determining ideal manufacturing settings. This course utilizes hands-on activities to help you learn the criteria for running a DOE, the requirements and pre-work necessary prior to DOE execution, and how to select the appropriate designed experiment type to run.
RMS (Reliability-Maintainability-Safety-Supportability) engineering is emerging as the newest discipline in product development due to new credible, accurate, quantitative methods. Weibull Analysis is foremost among these new tools. New and advanced Weibull techniques are a significant improvement over the original Weibull approach. This workshop, originally developed by Dr. Bob Abernethy, presents special methods developed for these data problems, such as Weibayes, with actual case studies in addition to the latest techniques in SuperSMITH® Weibull for risk forecasts with renewal and optimal component replacement.
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!
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.
Lithium-ion batteries (LIBs) serve as the main power source for contemporary electric vehicles (EVs). Safeguarding these batteries against damage is paramount, as it can trigger accelerated performance deterioration, potential fire hazards, environmental threats, and more. This study explores the damage progression of a commercial vehicle LIB module containing prismatic cells under crush loading. We employed computational simulations of mechanical loading tests to investigate this behavior. Physical tests involved subjecting modules to low-speed (0.05 m/s) indentations using a V-shaped stainless-steel wedge, under 6 unique loading conditions. During the tests, the force and voltage change with wedge displacement were monitored. Utilizing experimental insights, we constructed a finite element (FE) model, which included the key components of the battery module, such as the prismatic cells, steel frames and various plastic parts.