Browse Topic: Quality, Reliability, and Durability

Items (10,233)
During the development phase of any product, it is crucial to ensure functionality and durability throughout their whole lifecycle. Physical tests have been traditionally used as the main tool to evaluate the durability of a product, especially in the automotive industry. And the evolution of computational methods combined with the Engineering Fundamentals allowed Computer Aided Engineering (CAE) simulations to predict failures in considering different conditions without building a prototype to perform a test. The use of virtual product validation using CAE simulations leads to product design flexibility on early development phase and both development costs and time reduction. This paper presents a methodology for computing the operation reaction loads in an automotive fuel filler door, which is an input needed to virtually validate the subsystem in terms of durability. The methodology is based on rigid body motion assumptions and the result shows good accuracy when comparing the
Pereira, Rômulo FrancoEspinosa-Aguilar, JonathanSilva, LucasSarmento, AlissonChou, Chun Heng
The path towards clean mobility points in the direction of battery electric vehicles (BEVs) as a possible transportation solution. Despite a growing market penetration worldwide, emerging countries are struggling to successfully adopt BEV with current vehicle models. The literature presents an embracing discussion about BEV barriers but lacks into suggesting practical actions into BEV design. Based on a product development methodology and value analysis, this research aims to review factors holding back the BEV adoption in developing countries and to apply these factors into BEV features and design specifications. The literature was systematically reviewed based on the Brazilian case scenario to cast customer requirements for numerical evaluation through the Mudge Method. These were later translated into design requirements and ranked according to their relative importance with the quality function deployment (QFD). The results show that vehicle safety, pricing, and range anxiety are
Colpo, Leonardo R.Nora, Macklini DallaRomano, Leonardo N.Glufke, Ronaldo M.Rech, Cassiano
Mechanical component failure often heralds superficial damage indicators such as color alteration due to overheating, texture degradation like rusting or false brinelling, spalling, and crack propagation. Conventional damage assessment relies heavily on visual inspections performed by technicians, a practice bogged down by time constraints and the subjective nature of human error. This research paper delves into the integration of deep learning methodologies to revolutionize surface damage evaluation, addressing significant bottlenecks in diagnostic precision and processing efficiency. We detail the end-to-end process of developing an intelligent inspection system: selecting appropriate deep learning architectures, annotating datasets, implementing data augmentation, optimizing hyperparameters, and deploying the model for widespread user accessibility. Specifically, the paper highlights the customization and assessment of state-of-the-art models, including EfficientNet B7 for
Cury, RudonielGioria, GustavoChandrasekaran, Balaji
LM (Lean manufacturing) is the manufacturing strategy focused on continuous improvement of manufacturing operations. This study has been carried out in manufacturing industry of northern India to assess important success factors, LM strategies applied, and important benefits of both LM strategies and approach. Questionnaire survey has been performed to achieve the desired objectives. Results indicated that manufacturing organizations have great affinity for LM strategies viz. small incremental improvements (kaizen) for strategic success. Production rates are highly improved after implementing LM approach. Mediating role of every success factor have been measured using regression analysis and structural equation modeling. Moreover, correlation shows the highly significant relations between LM strategies and benefits of the LM approach
Kumar, RajeshKumar, AshwiniKumar, Rajender
Traditional vehicle diagnostics often rely on manual inspections and diagnostic tools, which can be time-consuming, inconsistent, and prone to human error. As vehicle technology evolves, there is a growing need for more efficient and reliable diagnostic methods. This paper introduces an innovative AI-based diagnostic system utilizing Artificial Intelligence (AI) to provide expert-level analysis and solutions for automotive issues. By inputting various details such as the vehicle’s make, model, year, mileage, problem description, and symptoms, the AI system generates comprehensive diagnostics, identifies potential causes, suggests step-by-step repair solutions, and offers maintenance tips. The proposed system aims to enhance diagnostic accuracy and efficiency, ultimately benefiting mechanics and vehicle owners. The system’s effectiveness is evaluated through various experiments and case studies, showcasing its potential to revolutionize vehicle diagnostics
Sasikala, T.Swathi, B.Raj, J. Joshua DanielShetty, G. ShreyasDidagur, Darshan
In manual transmission, bearing preload is a vital factor for optimum durability and performance of tapered roller bearings (TRB). To achieve better optimization of bearing preload, a precise measurement method is a minimum requisite. This technical paper investigates multiple ideas and develops a novel methodology for accurate bearing preload measurement, overcoming the challenges produced by the complexity of transmission design. This paper provides a systematic approach to bearing preload measurement in manual transmission along with identification of key parameters responsible for influencing bearing preload, such as rigidity and fit of the components. A comprehensive experimental study at both part level and system level was conducted to quantify the effects of above-mentioned parameters on preload and transmission performance. Furthermore, the paper explores the effect of bearing preload optimization on the durability performance of the transmission unit
Gaurav, KumarKumar, ArunSingh, Maninder PalDhawan, SoumilSingh, KulbirKumar, KrishanSingh, Manvir
Assembly simulation plays a pivotal role in predicting and optimizing the distortion of an assembly, particularly in the automotive industry where precision and efficiency are paramount. In BIW parts assembly, factors such as clamping, mechanical & thermal joining, and loading direction are important. These factors affect the quality of the final assembly. Predicting and optimizing these parameters in the early design stage can help reduce development time, cost and improve the quality of the final product. Currently, LS-DYNA is used for closures like doors, hoods, and fenders. However, the pre-processing, computation and post-processing time is significantly high in LS-DYNA making it challenging to use for the Entire BIW. Employing a comprehensive approach, authors assess the distortion results, preprocessing, calculation, and post-processing time of both simulation techniques. Notably, the study reveals that AutoForm offers over 50%-time savings across all stages compared to LS-DYNA
Talawar, VaishnavchandanNalam, Swaroop RajuDhanajkar, NarendraKumar, AjayPasupathy, VivekanandChava, Seshadri
Wire Electrical Discharge Machining (WEDM) has attracted considerable attention in contemporary manufacturing because of its capacity to accurately form conductive materials. This study aims to optimize the parameters of Wire Electrical Discharge Machining (WEDM) for SAE 1010 material, which is a commonly used low-carbon steel. The Taguchi-based Grey Relational Approach (GRA) is employed for this purpose. The goal is to optimize machining efficiency and quality while minimizing production costs. The research methodology combines the Taguchi method for experimental design with the GRA for multi-response optimization. The Taguchi L27 orthogonal array is utilized to carry out experiments, taking into account three controllable factors: pulse-on time, pulse-off time, and discharge current. In addition, the performance characteristics to be optimized include surface roughness (Ra) and material removal rate (MRR). The experimental results are analyzed using the GRA (Grey Relational Analysis
Natarajan, ManikandanPasupuleti, ThejasreeKiruthika, JothiKrishnamachary, PCSilambarasan, R
Wire Electrical Discharge Machining (WEDM) is an important method engaged to make intricate shapes in conductive materials like Cupronickel, which is well-known for its ability to resist corrosion and conduct heat. The intention of this exploration is to enhance the effectiveness and accuracy of Wire Electrical Discharge Machining (WEDM) for Cupronickel material by utilizing a Taguchi-based Grey Relational Analysis (GRA). The study examines the impact of WEDM parameters, specifically pulse-on time, pulse-off time, and discharge current, on key machining outcomes such as surface roughness (Ra), material removal rate (MRR). A comprehensive dataset is generated for analysis through a systematic series of experiments designed using the Taguchi method. Grey relational grades are assessed to measure the connections between the input parameters and machining responses, making it easier to determine the best parameter settings. The Taguchi-based GRA approach provides a systematic approach for
Pasupuleti, ThejasreeNatarajan, ManikandanKiruthika, JothiRamesh Naik, MudeSilambarasan, R
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has become a highly promising method for creating intricate shapes using different materials. Polyethylene Terephthalate Glycol (PETG) is a highly utilized thermoplastic that is recognized for its exceptional strength, resistance to chemicals, and effortless processing. This study aims to optimize the process parameters of the FDM technique for PETG material using Taguchi Grey Relational Analysis (GRA). An empirical study was carried out to examine the impact of various FDM process parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on important outcome variables like dimensional accuracy, surface quality, and mechanical properties. The Taguchi method was used to systematically design a series of experiments, while GRA was used to optimize the process parameters and performance characteristics. The results unveiled the most effective parameter combinations for attaining
Natarajan, ManikandanPasupuleti, ThejasreeKiruthika, JothiD, PalanisamySilambarasan, R
Spot welds are integral to automotive body construction, influencing vehicle performance and durability. Spot welding ensures structural integrity by creating strong bonds between metal sheets, crucial for maintaining vehicle safety and performance. It is highly compatible with automation, allowing for streamlined production processes and increased efficiency in automotive assembly lines. The number and distribution of spot welds directly impact the vehicle's ability to withstand various loads and stresses, including impacts, vibrations, and torsion. Manufacturers adhere to strict quality control standards to ensure the integrity of spot welds in automotive production. Monitoring spot weld count and weld quality during manufacturing processes through advanced inspection techniques such as Image processing by YOLOv8 helps identify the number of spots and quality that could compromise safety. Automating quality control processes is paramount, and machine vision offers a promising
Kadam, Shubham NarayanDolas, AniketMishra, Jagdish
The increase in vehicular traffic on Indian roads has led to a significant rise in the frequency of horn usage, particularly in city driving conditions and during peak traffic hours. Existing electro-mechanical horns are designed to have a mission life of 100,000 cycles according to Indian standards IS 1884 [1]. However, the intensified usage patterns have prompted a re-evaluation of the efficacy of these requirements. Studies reveal that the average horn blow frequency for normal usage vehicles is approximately three times per kilometer. When extrapolated to various usage categories, such as public transport and privately owned vehicles, observed increase in average horn blowing frequency per kilometer. When extrapolated, this corresponds to more than 4 lakhs cycles for a vehicle mission life of 2.5 lakhs kilometers. This insight drives the need to review and update validation test specifications to better align with customer usage patterns, thereby enhancing component reliability. By
Joshi, Vivek S.Jape, Akshay
Manual installation of vehicle underbody Grommets is tedious task which sometimes results in incomplete & inaccurate installation. Based on process quality guidelines, this comes under potential defect category at End of line inspection area for which few hours of manual efforts are required for identifying location of error & doing rework activity. Existing deep learning & image comparison method falls short in identifying error location. To overcome this challenge, deep learning algorithm with co-ordinate system developed which comprises of identifying class or category of entities present in test and reference image and indexing it as Grommet or Hole. This further comprises of determining 2D position in terms of X and Y co-ordinate of each indexed hole & Grommet between reference & test image. This approach results in precise comparison & identification of error in terms of missing or misplacing of Grommets which also offers significant saving in manual installation and rework
Dhumal, Abhishek TrimbakMishra, JagdishTote, AnujNurukurthi, LakshmiKumar, Prakash
The future of wireless technology - from charging devices to boosting communication signals - relies on the antennas that transmit electromagnetic waves becoming increasingly versatile, durable and easy to manufacture. Researchers at Drexel University and the University of British Columbia believe kirigami, the ancient Japanese art of cutting and folding paper to create intricate three-dimensional designs, could provide a model for manufacturing the next generation of antennas. Recently published in the journal Nature Communications, research from the Drexel-UBC team showed how kirigami - a variation of origami - can transform a single sheet of acetate coated with conductive MXene ink into a flexible 3D microwave antenna whose transmission frequency can be adjusted simply by pulling or squeezing to slightly shift its shape
Increased use of advanced composite structural materials on aircraft has resulted in the need to address the more demanding quality and nondestructive testing procedures. Accordingly, increased utilization of solid laminate composites is driving changes to airline NDI/NDT training requirements and greater emphasis on the application of accurate NDI/NDT methods for composite structures. Teaching modules, including an introduction to composite materials, composite NDI/NDT theory and practice, special cases and lessons learned, are included in this document as well as various hands-on NDI/NDT exercises. A set of proficiency specimens containing realistic composite structures and representative damage are available to reinforce teaching points and evaluate inspector’s proficiency. Extensive details of the guidance modules, hands-on exercises, and proficiency specimens are all presented in this document. This document does not replace OEM guidance as may be specific to material, process
AMS CACRC Commercial Aircraft Composite Repair Committee
ABSTRACT The durability and reliability of military vehicle systems are traditionally tested at Aberdeen Proving Ground by driving vehicles on a set of paved roads, secondary roads, trails, and cross-country terrains. However, driving mile-for-mile over the proving ground test courses is very time-consuming and costly. The U.S. Army Aberdeen Test Center (ATC) has recently conducted accelerated durability tests of wheeled vehicles using two different methods: accelerated hardware-in-the-loop simulation and accelerated field testing. This paper discusses the methods used to date and associated technical details to highlight options for future accelerated testing
Ramsey, GregSchultz, GregClerkin, James
ABSTRACT When the components of a military vehicle are designed, consideration is given to long term durability under repeated mission applications. In reality, surface and subsurface defects have always existed in weldments, forgings, and castings. These defects came from the manufacturing process or nucleated during the life of the vehicle. These defects may grow under repeated operations, resulting in ultimate failure of parts well before the design life is achieved. In such situations, a design based on crack initiation alone will not suffice, and a fracture mechanics based fatigue should also be included to predict the design life of a part accurately. In this paper a methodology is given on how to predict the available design life given the presence of defects in different parts of a military vehicle. An example will be provided with the process to demonstrate each step of the process
Porter, William De
Abstract This paper presents a fault-tolerant powertrain topology for series hybrid electric vehicles (SHEVs). The introduction of a redundant phase leg that is shared by three converters in a standard SHEV drive system allows to maximize the reliability improvement with minimal part-count increase. The new topology features fast response in fault detection and isolation, and post-fault operation at rated power throughput. The operating principle, control strategy, and fault diagnostic methods are elaborated. The substantially improved reliability over the standard topology is verified by the Markov reliability model. Time-domain simulation based on a Saber model has been conducted and the results have verified the feasibility and performance of the proposed SHEV drive system with fault-tolerant capability. The experimental results from a prototype have further validated the robust fault detection scheme and excellent post-fault performance
Song, YantaoWang, Bingsen
ABSTRACT Vehicle prognostics are used to estimate the remaining useful life of components or subsystems, based on a limited number of measured vehicle parameters. Ideally, sensors would be available for every component and failure mode of interest, such that accurate data could be measured and used in prognostic estimates. However, this is impractical in terms of the number of sensors required and the costs to install such a system and maintain its integrity. A better solution is to relate the loading on a specific component to more generic vehicle behavior. This paper reviews a methodology referred to as the “Durability Transfer Concept”, which suggests that damage, or severity of usage, at various points of interest on a vehicle can be predicted simply from measured accelerations at some nominal location – a wheel axle, for example. Measured accelerations are double integrated to get displacements. Those displacements are then filtered using the Rupp or Lalanne method. A transfer
Halfpenny, AndrewHussain, ShabbirMcDougall, ScottPompetzki, Mark
Many of the “ilities” (Reliability, Maintainability, etc) are afterthoughts in the creation of a specification, and are often relegated to a set of templated boilerplate requirements, that are largely ignored. The Reliability / Robust Design professionals often use a P-Diagram (Parameter Diagram) as a key part of understanding the system under design. A way of integrating the Reliability effort more into the mainstream of the design activity, and give them a stronger voice, is to put their P-Diagram right into the specification, before it gets released to industry. This paper describes the rationale and the manner in which to do this
Dutcher, Kevin J.
ABSTRACT The concept of Autonomous Vehicles ultimately generating an “order of magnitude” potential increase in the duty or usage cycle of a vehicle needs to be addressed in terms of impact on the reliability domain. Voice of the customer data indicates current passenger vehicle usage cycles are typically very low, 5% or less. Meaning, out of a 24 hour day, perhaps the average vehicle is actually driven only 70 minutes or less. Therefore, approximately 95% of the day, the vehicles lay dormant in an unused state. Within the context of future fully mature Autonomous Vehicle environment involving structured car sharing, the daily vehicle usage rate could grow to 95% or more
Wasiloff, James
ABSTRACT Value Engineering (VE) is an organized effort directed at analyzing the function of a product, service, or process to achieve the lowest total cost of effective ownership while meeting the customer’s needs. A comparison as to how VE is applied and to what extent is made between the automotive industry and the Government using the Program Executive Office Ground Combat Systems (PEO GCS) as a standard. Both the automotive industry and the Government use common VE techniques to conduct VE studies. Both use VE to manage functionality to yield value to the customer. Neither the Government nor the automotive industry sacrifices the quality of the product or its reliability in the name of cost. Both the auto industry and the PEO employ a systematic team approach to analyze and improve the value of a product, facility design, system, or service. Applying systems engineering principles helps ensure successful execution of the PEO GCS VE program. The auto industry uses VE more widely
Dmoch, Barbara J.Wiklund, George
ABSTRACT The key to a better correlation between the interface of systems engineering and project management is in fact a strong sigma relationship. In the recent past this would be termed Value Engineering and was that activity that took place prior to cutting the tools, but it is considerably more common today with the computer systems and software suites in use for modeling and the emphasis on Design for Six Sigma and time to market. All of these tools and methodologies are placing the focus on the final product performance, quality and cost and in so doing helping to again strengthen the manufacturing posture and job outlook of America and re-shore much of the work that was outsourced to save money. Whether of Military or U.S. vehicle manufacturing requirements, for the safety of our programs this work can and should stay in the United States when appropriate. This paper will develop better tools solutions, to provide better risk decisions which improve safety, budget, predictions
Maholick, WilliamGodell, Carl J
ABSTRACT The increasing application of sensors, actuators, and complex algorithms for delivering artificial intelligence and connectivity in products and product-systems will drive an unprecedented growth in design complexity and software content, making it increasingly more difficult to ensure dependability in an economical manner. Much learning about the dependability of such new and innovative products is likely to happen as they are conceived and designed. Consequently, accelerated verification and validation iterations supported by easy and rapid storage and retrieval of failure knowledge must be enabled. No single software solutions provider effectively covers all three critical areas required for developing and delivering dependable smart connected products, namely, reliability engineering, systems engineering, and failure knowledge management. This paper mainly presents a potential map of the commonly used reliability engineering tools overlaid on the systems engineering
Agaram, Venkatesh
ABSTRACT Systems Engineering (SE) would always benefit from the inclusion of the Six-Sigma perspective in both the planning and execution of project systems. This applies to not only System Engineers but also to Systems Extended Team Members, all who must provide cumulated knowledge along with competency to the project. It is difficult to obtain a high level of competency among single members of the team to be highly successful. Strength in one area is very often an underlying factor of weakness in another area. Determining and integrating sigma characteristics from the development cycle into all remaining phases of the product project, especially at critical component interfaces, with a resultant sigma value given to those connections that develop a sigma-risk factor for each function and process pathway within the operational configuration. This sigma-risk factor concept is the key in uniting knowledge with experience
Maholick, WilliamGodell, Carl J
ABSTRACT Today’s battlefield requires access to information in a multitude of environments with varying terrains (both urban and rural) in either passive or active engagements. Ground vehicles need sensors that can be rapidly deployed to different locations and networked into the family of vehicles in order to effectively share information. Masted sensor systems, in particular, are a potential valuable resource with their ability to perform long-range surveillance over obstructions while minimizing vehicle exposure. To maximize effectiveness these systems must withstand harsh battlefield conditions without undue maintenance. The need for variable mast heights, on-the-move (OTM) sensor performance, the ability to support a wide variety of long-range sensors, internal cabling to better resist battlefield damage, resistance to armored vehicle vibration and shock environments, and rapid mast deployment and stowage have driven Lockheed Martin to a robust mast solution that meets this
Neely, DavidFosen, KeithPoteat, DanielCarmichael, D. Brian
ABSTRACT High life cycle costs coupled with durability and environmental challenges of tracked vehicles in South West Asia (SWA) have focused R&D activities on understanding failure modes of track components as well as understanding the system impacts on track durability. The durability limiters for M1 Abrams (M1, M1A1, and M1A2) T-158LL track systems are the elastomeric components. The focus of this study is to review test methodology utilized to collect preliminary data on the loading distribution of a static vehicle. Proposed design changes and path forward for prediction of durability of elastomers at the systems level from component testing will be presented
Ostberg, DavidBradford, Bill
ABSTRACT BAE Systems has departed from traditional design rules of thumb and implemented a full-vehicle durability fatigue life analysis process at the design concept level to support lighter weight component designs. The durability process includes derivation of test duty cycles, generation of virtual loads from vehicle dynamic simulations, cascading of hundreds of channels of suspension attachment loads, and prediction of accumulated damage/fatigue life for both quasi-static and transient responses using a finite element vehicle structural model. The fatigue analysis process is typically deterministic, however the stochastic nature of the loads, material properties, and build variations should also be considered to ensure a robust durability process. The process is demonstrated on a heavy wheeled-vehicle platform using a generic duty cycle with examples shown at each stage of the process. This study additionally demonstrates the effects of variability of loads, materials, and
Purushothaman, NammalwarJayakumar, ParamsothyCritchley, JamesDatta, SandipPisipati, Venkat
ABSTRACT State-of-the-art Diesel engines used for on-highway operation are integrated systems containing multiple subsystems for performance and emissions enhancements. The drive to lower tailpipe emissions on on-highway engines drives system complexity which is both undesired and unnecessary for military ground vehicles. There are, however, on-highway technologies such as high pressure fuel injection systems and advanced turbocharger systems that allow improving the engines’ efficiency and therefore lowering its fuel consumption. The aforementioned technologies are currently available and present possible near term opportunities for military ground vehicles. The adaptation to allow reliable operation in military vehicles will be discussed as part of this near term view. The authors will also discuss the electronic controls architecture requirements that come along with these sophisticated technologies and discuss the advantages and opportunities that present themselves using advanced
Tatur, MarekTomazic, DeanKoehler, Erik
ABSTRACT A toolchain must be functionally cohesive with a business process, especially in technical domains such as complex systems engineering. Despite the industry-wide shift towards model-based digitization within engineering organizations, there is a lack of development in implementing model-based RAMS (Reliability, Availability, Maintenance, Safety) processes. This results in a missed opportunity to create value throughout the entire system lifecycle, from conceptual design to operations. This paper proposes some reasons for this and outlines a framework for evaluating model-based toolchains in the context of the entire Engineering cycle. A model-based architecture for RAMS is proposed and contrastively evaluated with respect to SysML. Key use cases are identified, and benefits are demonstrated using Maintenance Aware Design Environment Software. Citation: J. Langton, S. Hilton, “Iterative Co-Design Of Organizational Processes and Toolchains For Model-Based Reliability
Langton, JakeHilton, Sam
ABSTRACT The main goal of this paper is to report recent progress on two example projects supported within the Ground Robotics Reliability Center (GRRC), a TARDEC supported research center headquartered at the University of Michigan. In the first project, the concept of Velocity Occupancy Space (VOS), a new navigation algorithm that allows a robot to operate using only a range finding sensor in an unknown environment was developed. This method helps a mobile robot to avoid stationary and moving obstacles while navigating towards a target. The second project highlighted is related to energy and power requirement of mobile robots. Hazardous terrains pose challenges to the operation of mobile robots. To enable their safe and efficient operations, it is necessary to detect the terrain type and to modify operation and control strategies in real-time. A research project supported by GRRC has developed a closed-form wheel-soil model. Computational efficiency of this model is improved by
Peng, HueiUlsoy, A. Galip
ABSTRACT Accurate reliability assessment requires accurate output distribution. To obtain correct output distribution, a very large number of output physical test data is required, which is prohibitively expensive. Regarding this, simulation-based methods have been developed under the assumption that: (1) accurate input distribution models obtained from large number of input test data; and (2) accurate simulation model (including surrogate model if utilized) that correctly represents physical phenomena. However, in real application, only limited numbers of input test data are available. Thus, input distribution models are uncertain. In addition, the simulation model could be biased due to assumptions and idealizations. Furthermore, only a limited number of physical output test data is available. As a result, a target output distribution to which simulation model can be validated is uncertain and the corresponding reliability is also uncertain. This paper proposes a confidence-based
Choi, K.K.Cho, HyunkyooMoon, Min-yeongGaul, NicholasLamb, DavidGorsich, David
ABSTRACT Leader-follower autonomous vehicle systems have a vast range of applications which can increase efficiency, reliability, and safety by only requiring one manned-vehicle to lead a fleet of unmanned followers. The proper estimation and duplication of a manned-vehicle’s path is a critical component of the ongoing development of convoying systems. Auburn University’s GAVLAB has developed a UWB-ranging based leader-follower GNC system which does not require an external GPS reference or communication between the vehicles in the convoy. Experimental results have shown path-duplication accuracy between 1-5 meters for following distances of 10 to 50 meters. Citation: K. Thompson, B. Jones, S. Martin, and D. Bevly, “GPS-Independent Autonomous Vehicle Convoying with UWB Ranging and Vehicle Models,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022
Thompson, KyleJones, BenMartin, ScottBevly, David
ABSTRACT This research paper addresses the ground vehicle reliability prediction process based on a new integrated reliability prediction framework. The paper is an extension of the paper presented last year at the GVSETS symposium. The integrated stochastic framework combines the computational physics-based predictions with experimental testing information for assessing vehicle reliability. The integrated reliability prediction approach incorporates the following computational steps: i) simulation of stochastic operational environment, ii) vehicle multi-body dynamics analysis, iii) stress prediction in subsystems and components, iv) stochastic progressive damage analysis, and v) component life prediction, including the effects of maintenance and, finally, iv) reliability prediction at component and system level. To solve efficiently and accurately the challenges coming from large-size computational mechanics models and high-dimensional stochastic spaces, a HPC simulation-based
Ghiocel, Dan M.Negrut, DanLamb, DavidGorsich, David
ABSTRACT Significant Design for Reliability (DfR) methodology challenges are created with the integration of autonomous vehicle technologies via applique systems in a ground military vehicle domain. Voice of the customer data indicates current passenger vehicle usage cycles are typically 5% or less (approximately 72 minutes of use in a twenty-four hour period) [2]. The time during which vehicles currently lay dormant due to drivers being otherwise occupied could change with autonomous vehicles. Within the context of the fully mature autonomous military vehicle environment, the daily vehicle usage rate could grow to 95% or more. Due to this potential increase in the duty or usage cycle of an autonomous military vehicle by an order of magnitude, several issues which impact reliability are worth exploring. Citation: M. Majcher, J. Wasiloff, “New Design for Reliability (DfR) Needs and Strategies for Emerging Autonomous Ground Vehicles”, In Proceedings of the Ground Vehicle Systems
Majcher, MonicaWasiloff, James
ABSTRACT The U.S. Army Tank-Automotive Research, Development and Engineering Center (TARDEC) contracted DornerWorks Ltd. to evaluate Ethernet-based networking protocols for the safety-critical RDECOM Modular Active Protection Systems (MAPS) framework (MAF). The MAF requires a universal and robust high-speed communication network that can transmit heterogeneous data at near gigabit speeds in a deterministic fashion with bounded and predictable latency. The objectives were to evaluate candidate protocols through rigorous stressing scenarios to: 1) assess and estimate upper bound of performance including data throughput and reliability; and, 2) detect and identify causes and conditions of data loss or corruption. We assessed four protocols: SAE AS6802 (TTEthernet; TTE), ARINC664p7 (rate-constrained; RC), COTS UDP integrated with these two protocols (best-effort; BE), and UDP on a COTS network under three levels of network saturation and with varying payload sizes. On an unsaturated
Verbree, David A.Shvartsman, Andrey
ABSTRACT Problem: The traditional four (4) methods for improving reliability; 1) High design safety margin, 2) Reduction in component count or system architectural complexity, 3) Redundancy, and 4) Back-up capability, are often ignored or perceived as being excessively costly in weight, space claim as well as money. Solution 1: Discussed here are the practical and very cost effective methods for achieving improved reliability by Functional Interface Stress Hardening (FISHtm or FISHingtm). The Author has been able to apply FISH to eliminate 70-92% of unscheduled equipment downtime, within 30-60 days, for more than 30 of the Fortune 500 and many other large companies which utilize automation controls, computers, power electronics and hydraulic control systems. Solution 2: From Structured Innovation the 33 DFR Methods & R-TRIZ Tool can be used to grow or improve reliability, via rapid innovation. The R-TRIZ tool) is provided so that users can instantly select the best 2, 3 or 4 of these
Cooper, Howard C
ABSTRACT The functionality of the next-generation Department of Defense platforms, such as the Small Unmanned Ground Vehicles (SUGV) and Small Unmanned Arial Vehicles (SUAV), requires strongly electronics-rich architectures. The reliability of these systems will be dependent on the reliability of the electronics. These electronic systems and the critical components in them can experience extremely harsh thermal and vibrations environments. Therefore, it is imperative to identify the failure mechanisms of these components through experiments and simulation based on physics-of-failure methods. One of the key challenges in recreating life-cycle vibration conditions during design and qualification testing in the lab is the re-creation of simultaneous multi-axial excitation that closely mimics what the product experiences in the field. Currently, there are two common approaches in the industry when testing a prototype or qualifying a product for multi-axial vibration environments. One
Habtour, EdMortin, DavidChoi, CholminDasgupta, Abhijit
ABSTRACT The demand for mobile, secure communications has been and will continue to be a fundamental requirement for dismounted, urban and distributed operations in the field. It is imperative that soldiers on the front lines receive actionable information in a timely, secured and uninterrupted manner to increase force protection and effectiveness. In this paper, we describe a novel, high technical maturity (TRL 8+) communications link that offers the mounted and dismounted soldier secure, beyond line of sight, encrypted capability for weapons control and command & control of multiple platforms. An innovative spread spectrum waveform was designed from the ground up to deliver necessary functionality for reliable communications amongst multiple nodes with a data rate and range commensurate with battlefield scenarios
Mehta, Amish A.Cambridge, AndrewGardner, Brian
ABSTRACT The Integrated Systems Engineering Framework (ISEF) is an Army Research, Development, and Engineering Command (RDECOM) solution to address stovepiped systems engineering(SE) information and processes, disparate tools united by custom, one-off integrations, and a lack of accepted, common standards that exists in today’s Department of Defense (DoD) operating environment. Ever increasing technical complexity of fielded solutions combined with budgetary constraints push DoD engineers to “do more with less,” requiring a technical management solution that allows them collaborate virtually yet effectively with distributed engineers and other stakeholders. Easy access to systems engineering tools and information through a single “cloud” based application allows connections between federated databases, and facilitates knowledge preservation over time to avoid “reinventing the wheel” when new programs replace retired ones. ISEF is an ever-expanding collection of systems engineering
Umpfenbach, EdwardMendonza, PradeepGraf, Lisa
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