Calls for papers

 

International Journal of Machining and Machinability of Materials

 

Special Issue on: "Artificial Intelligence Applied in Machining"

Guest Editors:
Professor Ramón Quiza, University of Matanzas, Cuba
Professor Rogelio Hecker, University of la Pampa, Argentina
Professor J. Paulo Davim, University of Aveiro, Portugal

At the present, almost every branch of science and engineering uses the artificial intelligence tools and techniques. The industrial impact of artificial intelligence has primarily been in control and diagnosis applications; however, much research work has been done in applying these techniques in other fields.

In machining research, artificial intelligence tools have been widely used. Several topologies of neural networks (such as multilayer perceptrons, radial basis function networks and recurrent neural networks), as well as support vector machines, have been successfully applied to predictive modelling, adaptive control, tool condition diagnosis and fault detection in turning, drilling, milling, grinding and another machining processes.

Furthermore, a great variety of intelligent controllers and real-time monitoring systems, all of them based on fuzzy sets, has been reported in the specialised bibliographies. On the other hand, non-conventional meta-heuristic optimisation techniques, such as ant colony, simulated annealing and evolutionary computation, have been employed in process planning, tool paths planning and cutting parameters selection. The above-mentioned samples illustrate but do not include all applications of artificial intelligence techniques to the machining sciences.

This special issue of IJMMM invites the submission of high quality research articles on artificial intelligence applications to the machining processes.

Subject Coverage
Suitable topics include, but are not limited to, the application to the machining processes of the following techniques:

• Expert systems
• Case-based reasoning
• Neural networks
• Support vector machines
• Fuzzy logic
• Evolutionary algorithms and other meta-heuristic optimisation techniques
• Data mining
• Distributed intelligent systems

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere

All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page

Important Dates

Submission: 30 September 2008

Decision: 31 October 2008

Revised manuscripts: 31 December 2008