Title :
Neural net implementation for assigning a product to a production line
Author :
Romano, Roberto ; Maimon, O. ; Furst, M.
Author_Institution :
Fac. of Eng., Tel-Aviv Univ., Israel
Abstract :
Summary form only given. Assigning a new product to a production line is one of many problems whose solution is very complex and is approached by either exact mathematical programming or quick heuristics. The solution proposed imitates a foreman´s decision when he faces a real problem. A perceptron-type neural network is developed whose input parameters are a function of planning data, real-time status, and local expertise. Its output is the foreman´s decision. The robustness of this approach is demonstrated by a case study.<>
Keywords :
neural nets; production control; exact mathematical programming; foreman´s decision; local expertise; perceptron-type neural network; planning data; product assignment; production control; production line; quick heuristics; real-time status; Neural networks; Production control;
Conference_Titel :
Neural Networks, 1989. IJCNN., International Joint Conference on
Conference_Location :
Washington, DC, USA
DOI :
10.1109/IJCNN.1989.118325