Neural Simulation of a Prototype Keyboard Assembly Cell with Adaptive Control

Publication Type

Journal Article

Publication Date

10-1996

Abstract

This paper describes the integration of a feedforward neural network with a real-time adaptive control technique to model an assembly cell for computer keyboards. The simulation model is able to undertake real-time forecasting of the expected behaviour of the cell, and also able to display in real time the current status of the assembly cell. The potential of integrating artificial neural networks into simulation together with an on-line real-time interface between the simulation model and the real-world system is investigated in this study. A simulation model was built in SIMAN with a neural network written in NeuralWork Professional II Plus embedded in the model to allow training and testing of the network. The control of the cell was achieved through a third-party program written in C that interfaces directly to the cell.

Keywords

Neural simulation, keyboards, SIMAN, assembly control

Discipline

Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Intelligent Systems and Optimization

Publication

Journal of Intelligent Manufacturing

Volume

7

Issue

5

First Page

379

Last Page

386

ISSN

0012-3914

Identifier

10.1007/bf00123914

Publisher

Springer Verlag

Additional URL

https://doi.org/10.1007/BF00123914

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