Applied Computational Intelligence in Intelligent Manufacturing

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.

Knowledge, the candidate has knowledge about: - Basic insight into the theoretical foundation and practical applications of Computational Intelligence (CI), which includes Artificial Neural Networks (ANN), Fuzzy Logic Systems (FLS) and Genetic Algorithms (GAs).

Skills, the candidate can: - Be able to handle complex and uncertain Manufacaturing Systems (IMS) such as product design, process planning and control, production processes/systems and production management.

General competence, the candidate can: - Understand the impact and use of performance measurement in organizations and society. - Learn to use non-traditional intelligent approaches to solve modeling, prediction, classification, optimization and novel detection problems in engineering and management.

Lectures, exercises and projects.