Open Access. Powered by Scholars. Published by Universities.®
Operations Research, Systems Engineering and Industrial Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
Articles 1 - 4 of 4
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Artificial Neural Networks For Robotics Coordinate Transformation, Stephen Aylor, Luis Rabelo, Sema E. Alptekin
Artificial Neural Networks For Robotics Coordinate Transformation, Stephen Aylor, Luis Rabelo, Sema E. Alptekin
Industrial and Manufacturing Engineering
Artificial neural networks with such characteristics as learning, graceful degradation, and speed inherent to parallel distributed architectures might provide a flexible and cost solution to the real time control of robotics systems. In this investigation artificial neural networks are presented for the coordinate transformation mapping of a two-axis robot modeled with Fischertechnik physical modeling components. The results indicate that artificial neural systems could be utilized for practical situations and that extended research in these neural structures could provide adaptive architectures for dynamic robotics control.
Automatic Recognition Of Tool Wear On A Face Mill Using A Mechanistic Modeling Approach, Daniel Waldorf, Shiv G. Kapoor, Richard E. Devor
Automatic Recognition Of Tool Wear On A Face Mill Using A Mechanistic Modeling Approach, Daniel Waldorf, Shiv G. Kapoor, Richard E. Devor
Industrial and Manufacturing Engineering
A strategy is developed for identifying cutting tool wear on a face mill by automatically recognizing wear patterns in the cutting force signal. The strategy uses a mechanistic model development to predict forces on a lathe under conditions of wear and extends that model to account for the multiple inserts of a face mill. The extended wear model is then verified through experimentation over the life of the inserts. The predicted force signals are employed to train linear discriminant functions to identify the wear state of the process in a manner suitable for on-line application.
Introduction To Intellisim 1.0, Paul Savory
Introduction To Intellisim 1.0, Paul Savory
Department of Industrial and Management Systems Engineering: Faculty Publications
IntelliSIM is a prototype for a new generation of knowledge-based simulation tool that has been developed by the Systems Simulation Laboratory at Arizona State University. This tool is a computer environment that allows non-simulation trained modelers to predict the performance of a manufacturing system for which the necessary data is available. The system provides predictive data on such items as throughput time, queue levels, equipment utilization, reactions to machine failures, etc. With IntelliSIM, the benefits of discrete-event simulation can be exploited without requiring the high level of expertise necessary to successfully conduct a sound simulation study. The approach offered with …
On Capacity Modeling For Production Planning With Alternative Machine Types, Robert C. Leachman, Tali F. Carmon
On Capacity Modeling For Production Planning With Alternative Machine Types, Robert C. Leachman, Tali F. Carmon
Industrial and Manufacturing Engineering
Analyzing the capacity of production facilities in which manufacturing operations may be performed by alternative machine types presents a seemingly complicated task. In typical enterprise-level production planning models, capacity limitations of alternative machine types are approximated in terms of some single artificial capacitated resource. In this paper we propose procedures for generating compact models that accurately characterize capacity limitations of alternative machine types. Assuming that processing times among alternative machine types are identical or proportional across operations they can perform, capacity limitations of the alternative machine types can be precisely expressed using a formulation that is typically not much larger …