Course content

Intelligent Manufacturing Systems (IMS), Computational Intelligence (CI), learning rules of Artificial Neural Networks (ANNs), models of ANNs, modeling/classification/predication/diagnosis of systems, configuration of production systems, business predication, quality control, intelligent diagnosis of mechanical systems, Fuzzy Logic Systems (FLS), FLS for part routing, modeling supply chain, Gennetic algorithms (GAs), parameter optimization, process planning, scheduling, hybrid CI systems, neuro-fuzzy systems for cutting tool condition monitoring, development tool: NEUframe and Genehunter.

Learning outcome

The objective of the course is to give students an introduction to an advanced information process techniques - Computational Intelligence (CI), which includes Artificial Neural Networkes, Fuzzy Logic Systems (FLS) and Genetic Algorithms (GAs). The focus is placed on the applications of CI to Intelligent Manufacturing Systems (IMS) such as product design, process planning and control, production processes/systems and production management.

Learning methods and activities

Lectures, exercises and projects.

Compulsory assignments

• Exercises

Recommended previous knowledge

None.

Course materials

Kesheng Wang: Applied Computational Intelligence in Intelligent Manufacturing Systems, Advanced Knowledge International, (ISSN 0-9751004-9-1), 2005.

Credit reductions