Cost modeling and design for manufacturing guidelines for advanced composite fabrication

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2002.Includes bibliographical references.Experience shows that the majority of costs are committed during the early stages of the development process. Presently, many cost estimation methods are available to the public for metal processing, but there are almost none (excluding proprietary) for advanced composite materials. Therefore, the central objective of this thesis is to provide a comprehensive overview of the costs of common composite production technologies such as Hand Layup, Resin Transfer Molding, Automated Tow Placement, Pultrusion, Forming, and Assembly. The work includes information on investment costs for production equipment and tooling as well as estimation guidelines for labor and material. Designers are presented with Design for Manufacturing guidelines (DFM) explaining how process selection and part design can lead to potential cost saving opportunities. Process based or technical cost models are well suited to quantify manufacturing costs and relate them to part design features, such as size and shape complexity. These physically based scaling principles can be easily adapted to changes in process technology and thereby reducing data requirements. In order to identify all relevant cost drivers, a detailed process plan is compiled for each composite manufacturing method. These processes can include up to 50 process steps and a total of 270 cost equations are used to calculate the cost contribution of each.(cont.) A number of case studies conducted in concert with our industrial sponsors clearly identifies the best point of each production process and for example help to explain the economic benefits of co-curing versus mechanical assembly. Users can therefore study the economic consequences of design changes in detail and consequently highlight any favorable design/process combinations. To further facilitate the comparison of process performance and to promote the feedback from industry all of the models are available on the Internet at http://web.mit.edu/lmp/www/composites/costmodel/.by Sascha M. Haffner.Ph.D

Prediction of Robot Execution Failures Using Neural Networks

In recent years, the industrial robotic systems are designed with abilities to adapt and to learn in a structured or unstructured environment. They are able to predict and to react to the undesirable and uncontrollable disturbances which frequently interfere in mission accomplishment. In order to prevent system failure and/or unwanted robot behaviour, various techniques have been addressed. In this study, a novel approach based on the neural networks (NNs) is employed for prediction of robot execution failures. The training and testing dataset used in the experiment consists of forces and torques memorized immediately after the real robot failed in assignment execution. Two types of networks are utilized in order to find best prediction method - recurrent NNs and feedforward NNs. Moreover, we investigated 24 neural architectures implemented in Matlab software package. The experimental results confirm that this approach can be successfully applied to the failures prediction problem, and that the NNs outperform other artificial intelligence techniques in this domain. To further validate a novel method, real world experiments are conducted on a Khepera II mobile robot in an indoor structured environment. The obtained results for trajectory tracking problem proved usefulness and the applicability of the proposed solution

Neural Extended Kalman Filter for State Estimation of Automated Guided Vehicle in Manufacturing Environment

To navigate autonomously in a manufacturing environment Automated Guided Vehicle (AGV) needs the ability to infer its pose. This paper presents the implementation of the Extended Kalman Filter (EKF) coupled with a feedforward neural network for the Visual Simultaneous Localization and Mapping (VSLAM). The neural extended Kalman filter (NEKF) is applied on-line to model error between real and estimated robot motion. Implementation of the NEKF is achieved by using mobile robot, an experimental environment and a simple camera. By introducing neural network into the EKF estimation procedure, the quality of performance can be improved

Aeronautical engineering: A continuing bibliography, supplement 122

This bibliography lists 303 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1980

Selected Papers from the 5th International Electronic Conference on Sensors and Applications

This Special Issue comprises selected papers from the proceedings of the 5th International Electronic Conference on Sensors and Applications, held on 15–30 November 2018, on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups. In this 5th edition of the electronic conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Papers which attracted the most interest on the web or that provided a particularly innovative contribution were selected for publication in this collection. These peer-reviewed papers are published with the aim of rapid and wide dissemination of research results, developments, and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications

Technology 2002: The Third National Technology Transfer Conference and Exposition, volume 2

Proceedings from symposia of the Technology 2002 Conference and Exposition, December 1-3, 1992, Baltimore, MD. Volume 2 features 60 papers presented during 30 concurrent sessions

Aeronautical engineering: A continuing bibliography with indexes (supplement 227)

This bibliography lists 418 reports, articles, and other documents introduced into the NASA scientific and technical information system in May, 1988