NDLI: Design of an optimized procedure to predict opposite performances in porthole die extrusion

Content Provider	Springer Nature Link
Author	Ambrogio, G. Gagliardi, F.
Copyright Year	2012
Abstract	The main objective of advanced manufacturing control techniques is to provide efficient and accurate tools in order to control the set-up of machines and manufacturing systems. Recent developments and implementations of expert systems and neural networks support this aim. This research explores the combined use of neural networks and Taguchi’s method to enhance the performance of porthole die extrusion process; the energy saving and the quality of the welding line are two conflicting objectives of the process taken into account. The complexity of the analysis, due to the number of the involved variables, does not allow the representation of the specified outputs by means of a simple analytical approach. The implementation of a more accurate and sophisticated tool, such as the neural network, results more efficient and easier to be integrated into a simple “ready to use” procedure for predicting the investigated outputs. The main limit to wider implementation of neural networks is the huge computation resources (times and capacities) required to build the data set; a finite element approach was adopted to overcome the time and money wasting typical of experimental investigations. Satisfactory results in terms of prediction capability of the highlighted outputs were found. Finally, a simple and integrated interface was designed to make easier the application of the proposed procedure and to allow the generalization to other manufacturing processes.
Starting Page	195
Ending Page	206
Page Count	12
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	23
Issue Number	1
e-ISSN	14333058
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-04-01
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Extrusion Porthole ANN DoE Taguchi Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Probability and Statistics in Computer Science Computational Science and Engineering Image Processing and Computer Vision Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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