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Training / Education

Introduction to Failure Mode and Effects Analysis for Product and Process

2022-11-08
Failure Mode and Effects Analysis (FMEA) is a systematic method for preventing failure through the discovery and mitigation of potential failure modes and their cause mechanisms. Actions are developed in a team environment and address each high: severity, occurrence or detection ranking indicated by the analysis. Completed FMEA actions result in improved product performance, reduced warranty and increased product quality.
Training / Education

Weibull-Log Normal Analysis Workshop

2022-08-22
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.
Technical Paper

Driving Behaviour Analysis Software for Data-Driven Path Planning Functionalities for Automated Vehicles

2022-03-29
2022-01-0218
Autonomous driving is currently one of the most challenging Artificial Intelligence (AI) problems as it requires combination of state-of-the-art solutions in multiple areas including computer vision, sensor fusion, control theory and software engineering. Deep learning has been pivotal to solving some of these problems, especially in computer vision. This enabled some autonomous vehicle companies started leveraging the benefits of deep learning for creating smooth, natural, human-like motion planning systems. In particular, the plethora of driving data captured from modern cars is a key enabler for training data-driven path planning systems. , Developing deep learning-powered systems relies heavily on big and high-quality data required for training of the models, in which the intrinsic statistics of the data that the model is trained on can result in different agent behavior in different scenarios.
Technical Paper

Fault Diagnosis and Prediction in Automotive Systems with Real-Time Data Using Machine Learning

2022-03-29
2022-01-0217
In the automotive industry, a Malfunction Indicator Light (MIL) is a commonly employed to signify the failure or error in a vehicle system. To identify the root cause that has triggered a particular fault, a technician or engineer will typically run diagnostic tests and analyses. This type of analysis can take a significant amount of time and resources at the cost of customer annoyance and perceived quality. All modern vehicles generate data in the form of sensor readings accessible through vehicle Controller Area Network (CAN). This paper proposes the use of a recurrent neural network (RNN) to predict an impending fault before it occurs through the use of CAN data. Methods to pre-process the vehicle data for dimensionality reduction are proposed. The RNN then utilizes the processed data through short long-term memory to learn the system variables and input changes that contribute to the error over time.
Technical Paper

Use of Thermally Conductive Electrically Insulative (TCEI) Materials in E-motor Slot Liner Applications

2022-03-29
2022-01-0198
Slot liners are commonly used in electric motors to electrically insulate the motor windings from the laminated core. However, thermal conductivity of materials commonly used as slot liners is very low compared to other components in the motor thus creating a barrier for heat transfer. This thermal barrier affects overall motor performance and efficiency. Also, slot liners typically lack intimate contact with the laminated core resulting in air gaps which further increase thermal resistance in the system. Slot liners are traditionally made from high temperature films/papers that are cut and slid into slots of motors. The proposed work looks at developing an injection moldable slot liner to minimize air gaps. Additionally, use of TECI materials further lowers thermal resistance. A thermal finite element model has been developed to evaluate effects of slot liner thermal properties and air gaps on temperature distribution within the motor.
Technical Paper

Influence of Material Anisotropy on Identification of Plane Strain Yield Strength of Automotive Sheet Metals using Inverse Analysis of Notch Tests

2022-03-29
2022-01-0241
Plane strain test specimens used for the constitutive characterization of automotive sheets are typically limited to low strains levels due to the onset of necking and fracture at the specimen edges in uniaxial tension. In contrast, notched plane strain tensile tests for fracture characterization are commonly used for the calibration of stress-state dependent fracture models and possess strong stress and strain gradients to avoid failure in uniaxial tension at the edges. Inverse finite-element analysis can be used to exploit the stress gradients in the notch test to calibrate the local arc of the anisotropic yield surface from uniaxial-to-plane strain tension. However, the principal stress directions across the width are not constant due to the notch geometry and can be influenced by the tensile properties in the other directions leading to non-unique solutions in the inverse analysis.
Technical Paper

A Novel Tensile Testing Method to Characterize the Weld Metal Properties for Laser Welded Blank (LWB) with AHSS

2022-03-29
2022-01-0243
The automotive industry applies Laser Welded Blanks (LWB) to increase the material utilization and light-weighting of the vehicle structure. This paper introduces a novel tensile testing method to characterize the hardening behavior of the weld material with a digital image correlation (DIC) and apply it as a constitutive hardening model in forming simulations with the LWBs of GEN3 steel. Formability tests under biaxial conditions were performed with LWB of GEN3 steel. Experimental results were correlated with finite element analysis (FEA) predictions that were conducted with and without the weld material model. The results show the weld material model for the LWB improves the accuracy of FEA predictions of both necking failures on the base metal as well as cracking on the weld.
Technical Paper

Integrated Evaluation of Constant Amplitude Life Tests Towards SN Curves and Endurance Limit

2022-03-29
2022-01-0250
Establishing SN curves from constant amplitude life tests and locating the endurance limit are indispensable tasks in durability engineering. For both regimes, finite life and endurance limit, there are many approaches available, like linear regression or maximum likelihood. Especially on low load levels, tests may run very long and one may suspend them before failure. Especially the stair case method for evaluating the endurance limit systematically produces almost 50 percent suspended results. Hence, when data for both regimes is available, those run-outs need to be considered in a statistically proper way. If both regimes are evaluated separately it is often ambiguous if a single observations may be used for estimating the endurance limit or for the finite life re-gime. In this paper, we present an integrated approach, for simultaneous evaluation of both regimes. Every single ob-servation is mapped to one of the regimes with certain probabilities.
Technical Paper

Comparing stress gradient and other concepts for fatigue analysis of notched components

2022-03-29
2022-01-0252
Nowadays simulation of the fatigue life is an essential part of the development of components in the automotive and machinery industry. Weak points can be identified fast and reliable with respect to stiffness, strength and lightweight. A pure virtual optimization of the design can be performed without the need of prototypes. Only for the production release a final test is necessary. A lot of parameters influence the fatigue life as the local stress, material, surface roughness, size of the component, temperature etc. Notches have the strongest impact on fatigue life, depending on radius and shape. Stresses at the notch base are increased because the load flow is forced through a reduced cross section, or changes its direction around an inwardly curved edge. But notches cause not only an increase of the local stress. Also, the local fatigue strength is increased because of a support effect from the neighboring areas, where the stress is already reduced.
Technical Paper

Research on Vehicle State Segmentation and Failure Prediction Based on Big Data

2022-03-29
2022-01-0223
Vehicle failure prediction technology is an important part of PHM(Prognostic and Health Management) technology, which is of great significance to the safety of vehicles and to improve driving safety. Based on the vehicle operating data collected by the on-board terminal (T-box) of the telematics system, the research on the state of vehicle failure is conducted. First, this paper conducts statistical analysis on vehicle historical fault data. Preprocessing procedures such as cleaning, integration, and protocol are performed to group the data set. Then, three indexes including recency(R) frequency(F), and days(D) are selected to construct a vehicle security status subdivision system, and K -Means algorithm is utilized to divide different vehicle categories from the perspective of vehicle value. Labeled information of vehicles in different security status are further established.
Technical Paper

Early Detection of Engine Anomalies – A Case Study for AI-based Integrated Vehicle Health Management

2022-03-29
2022-01-0225
The increasing complexity of vehicle electronics and software is bringing an abundance of vehicle health related challenges, including quality issues and increasing costs of warranty claims, recalls, maintenance, and downtime. This negatively impacts both OEM and fleet profitability, user experience, and end customer costs. In order to reduce OEM costs and the total cost of ownership for consumers and fleets, new methods are needed to detect, predict, and diagnose vehicle health issues. Existing vehicle health management solutions rely on diagnostics trouble codes (DTC) and limited amounts of telematics data. These solutions can detect known failure modes using hard-coded signal behavior validation rules that are frequently based on thresholds. They also provide alerts based on pre-defined error codes. However, they are unable to detect and diagnose unforeseen failure modes that do not have hard-coded rules, nor can they prognose future vehicle health issues.
Technical Paper

Driver's driving style and driving condition recognition model based on SVM and XGBoost for online cloud platform

2022-03-29
2022-01-0227
At present, the remote monitoring cloud platform of many automobile companies only displays the collected data information, and it does not fully mine the deep-level information of the data. This paper uses data mining and machine learning methods to build a driver's driving style and driving condition prediction and recognition model based on the historical driving information generated by the vehicle, so as to improve the supervision and safety of the driver and the vehicle by automobile companies and other automobile-related industries. First, 36 standard driving cycles are utilized to construct an initial operating condition block data set. Second, we obtain the feature variables of driving style and driving conditions through feature engineering, and two recognition model data sets use the principal component analysis (PCA) and clustering algorithm for data dimensionality reduction and cluster analysis.
Technical Paper

Analysis on Irreversible Demagnetization Condition of Linear Oscillatory Actuator with Moving Magnets

2022-03-29
2022-01-0281
In this paper, a linear oscillatory actuator with moving magnets used in active engine mount is modeled and theoretically analyzed considering its performance decline at high temperature. Firstly, a finite element model of the linear oscillatory actuator with moving magnets is established. The actuator force is decomposed to ampere force and cogging force through formation mechanism analysis. By using the finite element model, ampere force and cogging force of the linear oscillatory actuator with moving magnets under different current loads and different mover positions are calculated. The finite element model and calculation method are validated by bench level test. The voice coil constant and cogging coefficient at room temperature are identified, which indicates the actuator force is a linear model related to the current and the mover position.
Technical Paper

The investigation of a contact and element-based approach for Cohesive zone modelling in the simulation of Delamination propagation

2022-03-29
2022-01-0259
The CAE industry always moves towards new ways to improve the productivity, efficiency and to reduce the solution times. Conventional method of Cohesive Zone Modelling has drawback of higher computation and modelling time. Due to this problem, sometimes Engineers need to avoid simulations and rely only on some sort of approximation of crack from previous designs. This approximation can lead to either product failure or overdesign of the product. A new approach is discussed in this paper to simulate crack initiation and propagation with Cohesive Zone Modelling. Conventional method uses Cohesive zone modelling with Hex or Penta elements by assigning material with cohesive properties, which increases computation and modelling time. The new approach models Cohesive zone as contact between two bodies, thus eliminating the need to use cohesive elements which will essentially reduce the computation time as well as modelling time.
Technical Paper

Technical Keynote: Durability Validation for Variable Vehicle Usage

2022-03-29
2022-01-0255
Durability engineering for vehicles is about relating real operational loading to the actual strength of the product and its components. In the first part of this presentation, we show how to calculate failure probabilities and safety factors based on the load and strength distributions. We discuss the uncertainty within the estimations, which is considerably large in case of extremely small failure probabilities as required for safety critical components. In the second part, we focus on modelling and simulating the loads based on real vehicle usage, such that the resulting statistics allows to understand and quantify the usage variability. The idea is, to simulate thousands of vehicle life spans of, say, 300.000 km or 15.000 h of operation each. The input data for such simulations typically consists of a combination of geographic data (like road network, topography, road conditions, traffic data, and points of interest) and properly segmented rich data from measurement campaigns.
Technical Paper

A fatigue life prediction method of rubber material for Automobile vibration isolator under road load spectrum

2022-03-29
2022-01-0253
Automobile rubber isolator was subjected to random load cycle for a long time in the service process, and its main rubber material for vibration isolation was prone to fatigue failure. Since the traditional Miner damage theory overlooked the load randomness, it had a prediction error problem. In order to improve the prediction accuracy of rubber fatigue life, the traditional Miner damage theory was modified by random uncertainty theory to predict the rubber fatigue life under random load. Firstly, the rubber dumbbell-shaped test column, which was vulcanized from rubber materials commonly used in vibration isolators, was taken as the research object. The uniaxial fatigue test of rubber under different strain amplitudes and strain mean values was carried out. Then the fatigue characteristic curve of rubber with equivalent strain amplitude as the damage parameter was established.
Technical Paper

Structure Optimization and Improvement of Commercial Vehicle Control Arm Based on Topology Optimization Method

2022-03-29
2022-01-0266
Automobile control arm is the guide and force transmission component of automobile suspension system, which makes the lightweight design of automobile according to a certain trajectory beneficial to energy saving and emission reduction. In this paper, the structure of the lower control arm of the front McPherson suspension is modeled and cleaned by UG software to simplify the model. The hexahedral shell element is used to establish the finite element model in HyperMesh. Considering the force and constraint conditions of the control arm under three different load conditions, the strength analysis is carried out by using the finite element software. It is found that the control arm is over-designed and has great potential for lightweight. The load and boundary conditions under different working conditions are set in HyperMesh, and the variable density method in topology optimization method is used to optimize the structure of automobile control arm under different working conditions.
Technical Paper

Design Optimization of Bicycle Wheel Hub Assembly for Automotive Applications

2022-03-29
2022-01-0262
The diminutive rolling resistance and wheel bearing drag characteristics of a bicycle wheel assembly makes it a lucrative choice of component in numerous 3-wheeled (3W) and 4-wheeled (4W) automotive applications. However, when a bicycle wheel is subjected to the loads encountered in such applications, complications pertaining to strength, durability and, performance are encountered. Since a bicycle wheel is intended to be arrested at either end of its axle, cantilever loading of the component as practiced in automotive applications diminishes the ability of the spindle to withstand longitudinal, and vertical forces encountered. Furthermore, while cornering on a bicycle, the maneuver of leaning in a corner significantly reduces the lateral stiffness requirement of the hub flanges. Therefore generic hub assemblies are designed without accounting for the action of lateral forces that are experienced at the hub with the wheel held vertical.
Technical Paper

Remove unwanted Vibrations for HVAC by Altering Modal Frequency using Finite Element Modeling and Validating Experimentally

2022-03-29
2022-01-0316
The main Objective of this paper is to remove the abnormal noise by altering the modal frequency. From the numerical method, very high deflection is reported at HVAC assembly level, cause unwanted vibrations. Due to high deflection at low frequency (1st modal frequency), abnormal noise coming near blower assembly under experimentally dynamic conditions. Then, improved the design by adding the stiffeners on the flange to minimize unwanted vibrations and hence abnormal nose. Thereafter, modal frequency has been increased and reduced the high deflection. The same has been validated experimentally with proto sample and found no abnormal noise from the blower side. A good correlation between the numerical and experimental result is observed and matching numerical & experimental modal frequencies within the accuracy of ±10%.
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