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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.  This course will include information on how DFM+A fits in with QFD, Concurrent Engineering, Robust Engineering, and other disciplines.

This course covers metal forming and related manufacturing processes, emphasizing practical applications. From forged or P/M connecting rods to tailor-welded blank forming, metal parts are integral to the automotive industry. As a high value adding category of manufacturing, metal forming is increasingly important to the core competency of automobile manufacturers and suppliers. A thorough survey of metal forming processes and metal forming mechanics will be performed, including bulk deformation, sheet-metal, and powder metallurgy operations. Design considerations are fully integrated into the course and are presented with every process.

Fatigue is a structural failure mode that must be recognized and understood to develop products that meet life cycle durability requirements. In the age of lightweighting, fatigue strength is an important vehicle design requirement as engineers struggle to meet stringent weight constraints without adversely impacting durability. This technical concept course introduces the fatigue failure mode and analysis methods. It explains the physics of material fatigue, including damage accumulation that may progress to product failure over time, and it provides the needed foundation to develop effective fatigue prediction capabilities.

The Process FMEA and Control Plan program introduces the basic concepts behind this important tool and provides training in how to conduct an effective PFMEA. First, the course explains what a PFMEA is and how it improves the long-term performance of your products, services and related processes by addressing process related failures. The role of the PFMEA in the overall framework of Quality Management System Requirements is explained as well as the role of the PFMEA in the Advanced Product Quality Planning (APQP) process. Additionally, the differences and relationships between the DFMEA and PFMEA are well defined.

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!

Alyson Lyon, executive leadership coach, discusses the value of effective and efficient communication. SAE Members can view the full version by logging into the Member Connection. Not a Member? Join us today at sae.org/join.

Alyson Lyon, executive leadership coach, discusses the value of being a mentor and/or a mentee. SAE Members can view the full version by logging into the Member Connection. Not a Member? Join us today at sae.org/join.

Alyson Lyon, Executive Leadership Coach, discusses how accurately defining goals leads to success. Members can view the full version by logging into the Member Connection here Not a Member? Get a taste of the Member Connection and join at connection.sae.org.

Alyson Lyon, Executive Leadership Coach, explains how the most successful people manage their time. Members can view the full version by logging into the Member Connection here Not a Member? Get a taste of the Member Connection and join at connection.sae.org.

This set includes: SAE International Journal of Aerospace March 2010 - Volume 2 Issue 1 SAE International Journal of Commercial Vehicles October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Engines October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Fuels and Lubricants October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Materials and Manufacturing October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Passenger Cars - Electronic and Electrical Systems October 2009 - Volume 2, Issue 1 SAE International Journal of Passenger Cars - Mechanical Systems October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract A number of semi-deterministic and stochastic formulations of multi-degree of freedom, frequency domain load models for heavy truck chassis are proposed and evaluated. The semi-deterministic models aim at reproducing the damage of a specific vehicle, while the stochastic ones aim to describe a collection of vehicle loads. The stochastic models are divided into two groups: Monte Carlo based and models based on single spectrum matrices. In both cases, the objective is to provide a load model that may be used to produce a design with a certain probability of survival. The goodness of the models is evaluated through a comparison of their damage outcomes with the corresponding damages of a set of time domain loads. This original time domain load set consists of chassis accelerations collected from seven physical trucks.

Abstract Electric heavy-duty tractor-trailers (EHDTT) offer an important option to reduce greenhouse gases (GHG) for the transportation sector. However, to increase the range of the EHDTT, this effort investigates critical vehicle design features that demonstrate a gain in overall freight efficiency of the vehicle. Specifically, factors affecting aerodynamics, rolling resistance, and gross vehicle weight are essential to arrive at practical input parameters for a comprehensive numerical model of the EHDTT, developed by the authors in a subsequent paper. For example, drag reduction devices like skirts, deturbulators, vortex generators, covers, and other commercially available apparatuses result in an aggregated coefficient of drag of 0.367. Furthermore, a mixed utilization of single-wide tires and dual tires allows for an optimized trade-off between low rolling resistance tires, traction, and durability.

Abstract The following article illustrates the detailed study of the development of a unique flywheel-based regenerative braking system (f-RBS) for achieving regenerative braking in a commercial electric bus. The f-RBS is designed for installation in the front wheels of the bus. The particular data values for modeling the bus are taken from multiple legitimate sources to illustrate the development strategy of the regenerative braking system. Mechanical components used in this system have either been carefully designed and analyzed for avoiding fatigue failure or their market selection strategies explained. The positioning of the entire system is decided using MSC Adams View®, hence determining a suitable component placement strategy such that the f-RBS components do not interfere with the bus components. The entire system is modeled on MATLAB Simulink® with sufficient accuracy to get various results that would infer the performance of the system as a whole.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.

Abstract The paper presents a complete description of the design and manufacturing of a Carbon Fiber/epoxy mold with an embedded Carbon Fiber resistor heater, and the mold performances in terms of its surface temperature distribution and thermal deformations resulting from the heating. The mold was designed for manufacturing aileron skins from Vacuum Bag Only prepreg cured at 135°C. The glass transition temperature of the used resin-hardener system was about 175°C. To ensure homogenous temperature of the mold working surface in the course of curing, the Carbon Fiber heater was embedded in a layer of a highly heat-conductive cristobalite/epoxy composite, forming the core of the mold shell. Because the cristobalite/epoxy composite displayed much higher thermal expansion than CF/epoxy did, thermal stresses could arise due to this discrepancy in the course of heating.

Abstract This paper presents a machine learning application of the force/torque sensor in a human-robot collaborative manufacturing scenario. The purpose is to simplify the programming for physical interactions between the human operators and industrial robots in a hybrid manufacturing cell which combines several robotic applications, such as parts manipulation, assembly, sealing and painting, etc. A multiclass classifier using Light Gradient Boosting Machine (LightGBM) is first introduced in a robotic application for discriminating five different contact states w.r.t. the force/torque data. A systematic approach to train machine-learning based classifiers is presented, thus opens a door for enabling LightGBM with robotic data process. The total task time is reduced largely because force transitions can be detected on-the-fly. Experiments on an ABB force sensor and an industrial robot demonstrate the feasibility of the proposed method.