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Viewing 1 to 30 of 1864
2016-10-25
Technical Paper
2016-36-0169
Emilio C. Baraldi, Paulo Carlos Kaminski
Abstract The competition among automotive industries increases each year worldwide. Among their diverse needs, what can be highlighted are: market expansion, model diversification, competitive prices, customer-recognized quality, new products release in shorter time periods, among others. The occurrence of flaws that might compromise the health or safety of the product’s user is admittedly one of the largest issues for any manufacturer, especially if these flaws are identified after its commercialization (recall). In this work, a study on recall in the automotive industry in the Brazilian market will be presented, comprising the years of 2013 and 2014. Reasons and causes of recall are addressed, based on the sample of the aforementioned research, with special emphasis on flaws derived from the production process. The conclusion at the end of the work is that the final assembly in the automotive manufacturing process is what requires more attention from engineering area.
2016-09-27
Journal Article
2016-01-8011
Kevin Grove, Jon Atwood, Myra Blanco, Andrew Krum, Richard Hanowski
Abstract This study evaluated the performance of heavy vehicle crash avoidance systems (CASs) by collecting naturalistic driving data from 150 truck tractors equipped with Meritor WABCO OnGuardTM or Bendix® Wingman® AdvancedTM products. These CASs provide drivers with audio-visual alerts of potential conflicts, and can apply automatic braking to mitigate or prevent a potential collision. Each truck tractor participated for up to one year between 2013 and 2015. Videos of the forward roadway and drivers’ faces were collected along with vehicle network data while drivers performed their normal duties on revenue-producing routes. The study evaluated the performance of CAS activations by classifying them into three categories based on whether a valid object was being tracked and whether drivers needed to react immediately.
2016-09-27
Technical Paper
2016-01-8132
Sanket Pawar
Abstract Reliability engineering methods are used to assess risk and eliminate hazards by estimation, elimination, and management of risks of failures. The ISO 26262 functional safety standard gives detailed guidance on reliability engineering methods like Failure Mode and Effect Analysis (FMEA) [7], Fault Tree Analysis (FTA) [8] [2], and etc. While, there are many methods available for reliability engineering; no single method is foolproof for securing safety by eliminating hazards completely. Out of these methods, FMEA is widely being used as an integral part of the product development life cycle [10]. In this method, failure modes of individual components are analyzed considering one failure at a time. FMEA is an efficient method for analyzing failures in simple systems. For complex systems, FMEA becomes impractical. It is also difficult to consider variables in FMEA.
2016-04-05
Technical Paper
2016-01-0274
Sharon L. Honecker, David J. Groebel, Adamantios Mettas
Abstract In order to accurately predict product reliability, it is best to design a test in which many specimens are tested for a long duration. However, this scenario is not often practical due to economic and time constraints. This paper describes a reliability test in which a limited number of specimens are tested with little time remaining before the scheduled start of production. During the test, an unexpected failure mode that can be mitigated through a product redesign occurs. Because the scheduled start of production is near, there is not enough time to perform a test with redesigned specimens, so the current test proceeds as planned. We discuss several methods and the associated assumptions that must be made to account for the presence of the unexpected failure mode in the test data in order to make predictions of reliability of the redesigned product.
2016-04-05
Technical Paper
2016-01-0279
Chong Chen, Zhenfei Zhan, Jie Li, Yazhou Jiang, Helen Yu
Abstract To reduce the computational time of the iterations in robust design, meta-models are frequently utilized to approximate time-consuming computer aided engineering models. However, the bias of meta-model uncertainty largely affects the robustness of the prediction results, this uncertainty need to be addressed before design optimization. In this paper, an efficient uncertainty quantification method considering both model and parameter uncertainties is proposed. Firstly, the uncertainty of parameters are characterized by statistical distributions. The Bayesian inference is then performed to improve the predictive capabilities of the surrogate models, meanwhile, the model uncertainty can also be quantified in the form of variance. Monte Carlo sampling is finally utilized to quantify the compound uncertainties of model and parameter. Furthermore, the proposed uncertainty quantification method is used for robust design.
2016-04-05
Technical Paper
2016-01-0271
David A. Warren
Abstract The objective of the paper is to outline the steps taken to change the reliability and maintenance environment of a plant from completely reactive to proactive. The main systems addressed are maintenance function fulfillment with existing staffing; work order management, planning, and scheduling; preventive maintenance (PM) definition and frequency establishment; predictive maintenance (PdM) scheduling and method definition; and shutdown planning and execution. The work order management methods were evaluated and modified to provide planning and scheduling of work orders on a weekly basis. The computerized maintenance and management system (CMMS) was updated to automatically insert work orders into the backlog of work for completion. A failure modes and effects analysis (FMEA) was performed and the results of the FMEA led to implementation of the following PM and PdM activities: vibration analysis, thermal imaging, and temperature monitoring.
2016-04-05
Technical Paper
2016-01-0270
Zhigang Wei, Limin Luo, Michael Start, Litang Gao
Product validation and reliability demonstration require testing of limited samples and probabilistic analyses of the test data. The uncertainties introduced from the tests with limited sample sizes and the assumptions made about the underlying probabilistic distribution will significantly impact the results and the results interpretation. Therefore, understanding the nature of these uncertainties is critical to test method development, uncertainty reduction, data interpretation, and the effectiveness of the validation and reliability demonstration procedures. In this paper, these uncertainties are investigated with the focuses on the following two aspects: (1) fundamentals of the RxxCyy criterion used in both the life testing and the binomial testing methods, (2) issues and benefits of using the two-parameter Weibull probabilistic distribution function.
2016-04-05
Journal Article
2016-01-0269
Zhigang Wei, Michael Start, Jason Hamilton, Limin Luo
Durability and reliability performance is one of the most important concerns for vehicle components and systems, which experience cyclic fatigue loadings and may eventually fail over time. Durability and reliability assessment and associated product validation require effective and robust testing methods. Several testing methods are available and among them, three basic testing methods are widely used: life testing, binomial testing (bogey testing), and degradation testing. In fact, their commonalities, differences, and relationships have not been clearly defined and fully understood. Therefore, the maximum potential of these testing methods to generate efficient, optimized, and cost-effective testing plans, consistent results, and meaningful results interpretation have been significantly limited. In this paper, a unified framework for representing these testing methods and conducting reliability analysis in a single damage-cycle (D-N) diagram is provided.
2016-04-05
Technical Paper
2016-01-0320
Tejas Janardan Sarang, Mandar Tendolkar, Sivakumar Balakrishnan, Gurudatta Purandare
Abstract In the automotive industry, multiple prototypes are used for vehicle development purposes. These prototypes are typically put through rigorous testing, both under accelerated and real world conditions, to ensure that all the problems related to design, manufacturing, process etc. are identified and solved before it reaches the hands of the customer. One of the challenges faced in testing, is the low repeatability of the real world tests. This may be predominantly due to changes in the test conditions over a period of time like road, traffic, climate etc. Estimating the repeatability of a real world test has been difficult due to the complex and multiple parameters that are usually involved in a vehicle level test and the time correlation between different runs of a real world test does not exist. In such a scenario, the popular and the well-known univariate correlation methods do not yield the best results.
2016-04-05
Technical Paper
2016-01-0289
Balakrishna Chinta
Abstract Mahalanobis Distance (MD) is gaining momentum in many fields where classification, statistical pattern recognition, and forecasting are primary focus. It is a multivariate method and considers correlation relationships among parameters for computing generalized distance measure to separate groups or populations. MD is a useful statistic in multivariate analysis to test that an observed random sample is from a multivariate normal distribution. This capability alone enables engineers to determine if an observed sample is an outlier (defect) that falls outside the constructed (good) multivariate normal distribution. In Mahalanobis-Taguchi System (MTS), MD is suitably scaled and used as a measure of severity in abnormality assessment. It is obvious that computed MD depends on values of parameters observed on a random sample. All parameters may not equally impact MD. MD could be highly sensitive with respect to some parameters and less sensitive to some other parameters.
2016-04-05
Technical Paper
2016-01-0283
Joydip Saha, Harry Chen, Sadek Rahman
Abstract More stringent federal emission regulations and fuel economy requirements have driven the automotive industry toward more sophisticated vehicle thermal management systems in order to best utilize the waste heat and minimize overall power consumption. With all new technologies and requirements, how to properly design, optimize, and control the vehicle thermal and cooling systems become great challenges to automotive engineers. Model based approach has become essential to the new thermal management system architectures design and evaluation of the optimal system solutions. This paper will discuss how the model based vehicle thermal system simulation tools have been developed from analytical & empirical data, and have been used for assessment and development of new thermal management system architectures.
2015-09-15
Technical Paper
2015-01-2556
Thomas Rousselin, Guillaume Hubert, Didier Regis, Marc Gatti
Abstract The changes brought by the increasing integration density and the new technological trends have pushed the reliability at its limit. Safety analysis for critical system such as embedded electronics for avionics systems needs to take into account these changes. In this paper, we present the consequences on the deep sub-micron (DSM) CMOS devices concerning their single event effect (SEE) sensitivity. We also propose a new modeling method in order to address these issues.
2015-04-14
Technical Paper
2015-01-0487
Lev Klyatis
Abstract This paper will discuss the problem with successful predicting of product performance (reliability, quality, durability, safety, recalls, profit, life cycle cost, and other interconnected technical and economic components of performance). The best component for analysing the performance situation during service life, including predicting, is recalls, because, first, recall accumulates the safety, reliability, durability, quality, profit, and total economic situation. And second, there is open official and objective information about the number of recalls from Government (National Highway Trafic Safety Administration and others), as well as companies-producers. Therefore, for analyzing the situation with the product performance, including predicting, this paper considers the situation with recalls.
2015-04-14
Technical Paper
2015-01-0439
Daniel B. Kosinski
Abstract The current reliability growth planning model used by the US Army, the Planning Model for Projection Methodology (PM2), is insufficient for the needs of the Army. This paper will detail the limitations of PM2 that cause Army programs to develop reliability growth plans that incorporate unrealistic assumptions and often demand that infeasible levels of reliability be achieved. In addition to this, another reliability growth planning model being developed to address some of these limitations, the Bayesian Continuous Planning Model (BCPM), will be discussed along with its own limitations. This paper will also cover a third reliability growth planning model that is being developed which incorporates the advantageous features of PM2 and BCPM but replaces the unrealistic assumptions with more realistic and customizable ones.
2013-09-20
Journal Article
2013-01-9041
Shawki Abouel-Seoud, Mohamed Khalil, Sameh Metwalley, Essam Allam, Hany Assad
Reliability has always been an important aspect in the assessment of industrial products and/or equipments. Good product design is of course essential for products with high reliability. However, no matter how good the product design is, products deteriorate over time since they are operating under certain stress or load in the real environment, often involving randomness. Maintenance has, thus, been introduced as an efficient way to assure a satisfactory level of reliability during the useful life of a physical asset. The earliest maintenance technique is basically breakdown maintenance (also called unplanned maintenance, or run-to-failure maintenance), which takes place only at breakdowns. A later maintenance technique is time-based preventive maintenance (also called planned maintenance), which sets a periodic interval to perform preventive maintenance regardless of the health status of a physical asset. The vehicle component is judged to be safe depending on its reliability.
2013-09-17
Journal Article
2013-01-2201
Joshua Benhabib
Manufacturing operations introduce unreliability into hardware that is not ordinarily accounted for by reliability design engineering efforts. Inspections and test procedures normally interwoven into fabrication processes are imperfect, and allow defects to escape which later result in field failures. Therefore, if the reliability that is designed and developed into an equipment/system is to be achieved, efforts must be applied during production to insure that reliability is built into the hardware. There are various ways to improve the reliability of a product. These include: Simplification Stress reduction/strength enhancement Design Improvement Using higher quality components Environmental Stress Screening before shipment Process Improvements, etc. This paper concentrates on ‘Manufacturing Process Improvement’ effort through the use of design of experiments, (DOE). Hence, improved levels of reliability can be achieved.
2013-04-08
Journal Article
2013-01-0607
Mahdi Norouzi, Efstratios Nikolaidis
Estimation of the probability of failure of mechanical systems under random loads is computationally expensive, especially for very reliable systems with low probabilities of failure. Importance Sampling can be an efficient tool for static problems if a proper sampling distribution is selected. This paper presents a methodology to apply Importance Sampling to dynamic systems in which both the load and response are stochastic processes. The method is applicable to problems for which the input loads are stationary and Gaussian and are represented by power spectral density functions. Shinozuka's method is used to generate random time histories of excitation. The method is demonstrated on a linear quarter car model. This approach is more efficient than standard Monte Carlo simulation by several orders of magnitude.
2013-04-08
Journal Article
2013-01-0606
Vijitashwa Pandey, Zissimos Mourelatos
The classical definition of reliability may not be readily applicable for repairable systems. Commonly used concepts such as the Mean Time Between Failures (MTBF) and availability can be misleading because they only report limited information about the system functionality. In this paper, we discuss a set of metrics that can help with the design of repairable systems. Based on a set of desirable properties for these metrics, we select a minimal set of metrics (MSOM) which provides the most information about a system, with the smallest number of metrics. The metric of Minimum Failure Free Period (MFFP) with a given probability generalizes MTBF because the latter is simply the MFFP with a 0.5 probability. It also generalizes availability because coupled with repair times it provides a clearer picture of the length of the expected uninterrupted service. Two forms of MFFP are used: transient and steady state.
2013-04-08
Journal Article
2013-01-0946
Vicente Romero, Joshua Mullins, Laura Swiler, Angel Urbina
This paper discusses the treatment of uncertainties corresponding to relatively few samples of random-variable quantities. The importance of this topic extends beyond experimental data uncertainty to situations involving uncertainty in model calibration, validation, and prediction. With very sparse samples it is not practical to have a goal of accurately estimating the underlying variability distribution (probability density function, PDF). Rather, a pragmatic goal is that the uncertainty representation should be conservative so as to bound a desired percentage of the actual PDF, say 95% included probability, with reasonable reliability. A second, opposing objective is that the representation not be overly conservative; that it minimally over-estimate the random-variable range corresponding to the desired percentage of the actual PDF. The presence of the two opposing objectives makes the sparse-data uncertainty representation problem an interesting and difficult one.
2013-04-08
Journal Article
2013-01-1384
Zhen Jiang, Wei Chen, Yan Fu, Ren-Jye Yang
Reliability-based design optimization (RBDO) has been widely used to obtain a reliable design via an existing CAE model considering the variations of input variables. However, most RBDO approaches do not consider the CAE model bias and uncertainty, which may largely affect the reliability assessment of the final design and result in risky design decisions. In this paper, the Gaussian Process Modeling (GPM) approach is applied to statistically correct the model discrepancy which is represented as a bias function, and to quantify model uncertainty based on collected data from either real tests or high-fidelity CAE simulations. After the corrected model is validated by extra sets of test data, it is integrated into the RBDO formulation to obtain a reliable solution that meets the overall reliability targets while considering both model and parameter uncertainties.
2012-04-16
Journal Article
2012-01-0070
Jing Li, Zissimos Mourelatos, Amandeep Singh
Reliability is an important engineering requirement for consistently delivering acceptable product performance through time. It also affects the scheduling for preventive maintenance. Reliability usually degrades with time increasing therefore, the lifecycle cost due to more frequent failures which result in increased warranty costs, costly repairs and loss of market share. In a lifecycle cost based design, we must account for product quality and preventive maintenance using time-dependent reliability. Quality is a measure of our confidence that the product conforms to specifications as it leaves the factory. For a repairable system, preventive maintenance is scheduled to avoid failures, unnecessary production loss and safety violations. This article proposes a methodology to obtain the optimal scheduling for preventive maintenance using time-dependent reliability principles.
2012-04-16
Journal Article
2012-01-0064
Vijitashwa Pandey, Zissimos Mourelatos
In this article we present an approach to identify the system topology using simulation for reliability calculations. The system topology provides how all components in a system are functionally connected. Most reliability engineering literature assumes that either the system topology is known and therefore all failure modes can be deduced or if the system topology is not known we are only interested in identifying the dominant failure modes. The authors contend that we should try to extract as much information about the system topology from failure or success information of a system as possible. This will not only identify the dominant failure modes but will also provide an understanding of how the components are functionally connected, allowing for more complicated analyses, if needed. We use an evolutionary approach where system topologies are generated at random and then tested against failure or success data. The topologies evolve based on how consistent they are with test data.
2011-10-18
Technical Paper
2011-01-2606
Wolfgang R. Habel, Nadine Kusche, Sven Munzenberger, Vivien G. Schukar
Strain sensors embedded in or attached to structural components have to measure the real deformation of the structure over the whole period of use. The user must know how reliably installed sensors provide strain measurement results. For this purpose, test facilities or coupon tests are used. In order to characterize the strain transfer quality from the host structure into surface-applied strain sensors, a unique testing facility has been developed. This facility can be used both for fiber optic and resistance strain sensors. Originally developed for fiber Bragg grating based sensors, the KALFOS facility (= \bc\ba\blibration of \bfiber \boptic \bsensors) uses Digital Image Correlation (DIC) and Electronic Speckle Pattern Interferometer (ESPI) as unbiased referencing methods. It is possible to determine experimentally the strain transfer mechanism under combined thermal and mechanical loading conditions.
2011-10-18
Technical Paper
2011-01-2804
Philippe Goupil, Andres Marcos
The state-of-practice for aircraft manufacturers to diagnose guidance & control faults and obtain full flight envelope protection at all times is to provide high levels of dissimilar hardware redundancy. This ensures sufficient available control action and allows performing coherency tests, cross and consistency checks, voting mechanisms and built-in test techniques of varying sophistication. This hardware-redundancy based fault detection and diagnosis (FDD) approach is nowadays the standard industrial practice and fits also into current aircraft certification processes while ensuring the highest level of safety standards. In the context of future “sustainable” aircraft (More Affordable, Smarter, Cleaner and Quieter), the Electrical Flight Control System (EFCS) design objectives, originating from structural loads design constraints, are becoming more and more stringent.
2011-10-18
Journal Article
2011-01-2803
Ali Zolghadri, Anca Gheorghe, Jérôme Cieslak, David Henry, Philippe Goupil, Rémy Dayre, Hervé Le Berre
This paper discusses the design of a model-based fault detection scheme for robust and early detection of runaways in aircraft control surfaces servo-loop. The proposed scheme can be embedded within the structure of in-service monitoring systems as a part of the Flight Control Computer (FCC) software. The final goal is to contribute to improve the performance detection of unanticipated runaway faulty profiles having very different dynamic behaviors, while retaining a perfect robustness. The paper discusses also the tradeoffs between adequacy of the technique and its implementation level, industrial validation process with Engineering support tools, as well as the tuning aspects. The proposed methodology is based on a combined data-driven and system-based approach using a dedicated Kalman filtering. The technique provides an effective method ensuring robustness and good performance (well-defined real-time characteristics and well-defined error rates).
2011-10-18
Journal Article
2011-01-2802
Halim Alwi, Christopher Edwards
This paper presents a preliminary evaluation of the results from using second order sliding mode observer schemes applied to an aircraft fault detection benchmark problem for a class of sensor faults. The scheme has been evaluated on the ADDSAFE Functional Engineering Simulator (FES). This is part of ongoing work on a European FP7 funded project entitled Advanced Fault Diagnosis for Sustainable Flight Guidance and Control (ADDSAFE) which aims to study advanced fault detection and isolation (FDI) methods for aircraft. The simulation and verification FES used in this evaluation incorporates a high fidelity nonlinear aircraft model from AIRBUS (which includes sensor and process noise).
2011-10-18
Journal Article
2011-01-2800
Florian Moliere, Alain Bravaix, Bruno Louis Foucher, Philippe Perdu
Up to now, the reliability achieved by COTS components was largely sufficient for avionics, in terms of failure rate as well as time to failure. With the implementation of new and more integrated technologies (90 nm node, 65 nm and below), the question has arisen of the impact of the new technologies on reliability. It has been stated that the lifetime of these new technologies might decrease. The drift is expected to be technology dependent: integration, technology node, materials, elementary structure choices and process pay a key role. Figures have been published, which gives smaller lifetime than the 30 years generally required for avionics. This would of course impact not only the reliability, but also the maintenance of COTS-based avionics. Hence a new policy should be defined for the whole COTS supply chain. Faced with these impending risks, different methodologies have been developed [1], [2].
2011-10-18
Journal Article
2011-01-2714
Vincent Rouet, Bruno Foucher
TRIADE is a European Union project that focuses on the development of technological building blocks for Structure Health Monitoring (SHM) sensing devices in aeronautics. It is funded under the 7th framework program. In terms of objectives, the TRIADE project focuses on providing these technological building blocks and fully integrated prototypes in order to achieve power generation, power conservation, energy management and embedded powerful intelligence for data processing and storage for SHM sensing devices. The principal technological building blocks that the TRIADE project will provide are: - A low profile battery with high energy density which will be able to function in a harsh environment, - An energy harvester from vibration and electromagnetic RF, - Ultra low power sensors which will be designed in SOI technology, and - A neural network for data recording and damage assessment.
2011-10-18
Technical Paper
2011-01-2704
Ravi Rajamani, Nicholas Waters
The use of Engine Health Management (EHM) systems has been growing steadily in both the civilian and the military aerospace sectors. Barring a few notable exceptions (such as certain temperature and thrust margin monitoring) regulatory authorities around the world have not required these systems to be certified in any way. This is changing rapidly. New airframes and engines are increasingly being designed with the assumption that EHM will be an integral part of the way customers will operate these assets. This leads to a need for better guidelines on how such systems should be certified. The SAE E-32 committee on Propulsion System Health Monitoring is leading an industry-wide effort to develop a set of guidelines for certifying EHM systems.
2011-10-18
Journal Article
2011-01-2701
Hannes Wagner, Galin Nikolov, Andreas Bierig, Holger Spangenberg
Flight control systems of civil aircraft have undergone huge developments in the last decades. The current more/ all electric aircraft concepts lead to the replacement of the hydraulic actuators in the primary flight control systems by electromechanical systems. Integrating electromechanical systems in safety critical applications implies three main challenges: (a) the detection of all fault cases which could lead to a safety critical state, (b) finding measurement parameters capable to detect faults, and (c) the development of algorithms to detect faults under all flight conditions. Putting the scope on the health monitoring of the mechanical components of a direct drive actuator, a new technology based on piezoresistive thin film sensors (TFS) is presented and its potential shown by using defective ball bearings as an example.
Viewing 1 to 30 of 1864

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