Browse Topic: Manufacturing
ABSTRACT The Bradley Combat Vehicle Motor Chatter case study focuses on one aspect of a combat vehicle program, specifically, responding to a vehicle production situation where combat vehicles produced with in-spec components and subsystems exhibit out-of-spec and failing system behavior. This typically results in an extended production line-down or line-degraded situation lasting for several quarters until the problem can be diagnosed, fixed, validated and verified. Subsequently, adequate quantities of the modified or replaced sub-systems must be put back into the production flow. The direct and indirect costs of an occurrence like this in peace-time are measured in the 10’s to 100’s of Millions of dollars. The schedule, program and perception impact to the vehicle platform can be potentially devastating. In war-time all of these impacts are magnified greatly by the added risk to soldiers’ lives. This paper describes the Bradley Combat Vehicle Motor Chatter case study and the
Summary This paper discusses the latest techniques in vehicle modeling and simulation to support ground vehicle performance and fuel economy studies, enable system design optimization, and facilitate detailed control system design. The Autonomie software package, developed at Argonne National Laboratory, is described with emphasis on its capabilities to support Model-in-the-Loop, Software-in-the-Loop (SIL), Component-in-the-Loop (CIL), and Hardware-in-the-Loop simulations. Autonomie supports Model-Based Systems Engineering, which is growing in use as ground vehicles become more sophisticated and complex, with many more subsystems interacting within the vehicle and the environmental conditions in which the vehicles operate becoming more challenging and varied. With the advent of hybrid powertrains, the additional dimension of vehicle architecture has become one of the design variables that must be considered. This complexity results in the need for a simulation tool that is capable of
ABSTRACT Ground vehicles are complex systems with many interrelated subsystems - finding the sweet-spot among competing objectives such as performance, unit cost, O&S costs, development risk, and growth potential is a non-trivial task. Whole Systems Trade Analysis (WSTA) is a systems analysis and decision support methodology and tool that integrates otherwise separate subsystem models into a holistic system view mapping critical design choices to consequences relevant to stakeholders. As a highly integrated and collaborative effort WSTA generates a holistic systems and Multiple Objective Decision Analysis (MODA) model. The decision support model and tool captures and synthesizes outputs from individual analyses into trade-space visualizations designed to facilitate rapid and complete understanding of the trade-space to stakeholders and provide drill down capability to supporting rationale. The approach has opened up trade space exploration significantly evaluating up to 1020+ potential
ABSTRACT There is a dire need for low-cost mobile robots for the purpose of mine detection and disposal. Countries with low gross domestic product (GDP) and infected with landmines generally cannot support expensive high-tech solution. A de-mining mobile robot has to be cost effective compared to local labor costs. Presently commercially available mobile robots consist of mainly custom made parts. The design and manufacturing of such parts make the robots very expensive. This paper describes how careful selection of commercially available parts leads to reducing the development time and costs for a demining robot while ensuring its reliability, convenient operation and application domain. An actual example of how a low cost mine detection robot was successfully integrated within two months is outlined
ABSTRACT Supporting Open Architecture is a key to most major automation and control suppliers. In every industry, there is a desire to make a unified control system architecture that can easily integrate control system equipment from multiple suppliers. Whether it is a Navy military application or an industrial application, the needs are almost identical. Some of the keys to providing this transparency among control systems are utilizing an open standard that can pull together communications from multiple suppliers. In this paper, SIEMENS will demonstrate the capabilities of utilizing an open standard, which is PROFINET. By adhering to the PROFINET standards, Open Architecture is achieved at many levels in a naval application. Open Architecture is intended to yield modular, interoperable systems that adhere to open standards with published interfaces. As will be demonstrated by this paper, PROFINET provides these capabilities and more. By implementing PROFINET as the infrastructure for
Abstract On the Mobile Detection Assessment Response System (MDARS) production program, General Dynamics Robotics Systems (GDRS) and International Logistics Systems (ILS), are working with the US Army’s Product Manager – Force Protection Systems (PM-FPS) to reduce system costs throughout the production lifecycle. Under this process, GDRS works through an Engineering Change Proposal (ECP) process to improve the reliability and maintainability of subsystem designs with the goal of making the entire system more producible at a lower cost. In addition, GDRS recommends substitutions of Government requirements that are cost drivers with those that reduce cost impact but do not result in reduced capability for the end user. This paper describes the production lifecycle process for the MDARS system and recommends future considerations for fielding of complex autonomous robotic systems
This specification covers a corrosion- and heat-resistant steel in the form of bars, wire, forgings, mechanical tubing, flash-welded rings, and stock for forging or flash-welded rings
Mode identification, particularly Modal Map Generation, is pivotal within the NVH (Noise, Vibration, and Harshness) domain for managing the performance of complex systems like TBIW/Powertrain. This study addresses the critical task of accurately identifying Global / Local behavior of a particular system as single entity (Complete TBIW, Power train) or all the systems attached to main structure (Sub Systems i.e Seat , Fuel Tank , Pump etc), which is crucial for effective NVH post-processing. Introducing a novel tool/methodology developed by the Applus IDIADA team, this paper presents an efficient approach to Global & Local mode identification across subsystems, TBIW, and Powertrain levels. Leveraging ".op2" file content, mainly Strain Energy Density[1] and Displacement [2], the tool integrates Machine Learning Techniques [3] to produce mode predictions along with detailed visual outputs such as graphs , pie chart , modal charts etc. Implemented as a Python-based solution compatible with
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