Course Catalog 2009-2010 Basic Basic Pori International Postgraduate Open University |Degrees|     |Study blocks|     |Courses|

Person responsible

Lastra Jose Martinez

Implementations

	Lecture times and places	Target group recommended to
Implementation 1	Periods 4 4 - 5

Requirements

Final exam AND Assignment(s)

Principles and baselines related to teaching and learning

-

Learning outcomes

This course provides an in-depth look at different knowledge representation languages and their application to intelligent manufacturing systems. The course will explore how reasoning machines are able to collaborate and automatically reconfigure to meet evolving production needs and achieve rapid product changeover. This is the basis for creating Rapidly Reconfigurable Manufacturing Systems (RRMS). Considering knowledge as the fundamental premise for attaining intelligence, the course will cover different automatic reasoning mechanisms based on logics and inference.

Content

Content	Core content	Complementary knowledge	Specialist knowledge
1.	Knowledge Representation Languages: First-Order Logic, Horn rules, production rules, Description Logics and Semantic Web Ontology Language (OWL), Concrete Domains and Description Logic Programming.
2.	Reasoning: Resolution, Classification and Subsumption.
3.	Knowledge Domains and Ontologies: manufacturing processes, machine skills, process and skill composition, introduction to situation calculus, product state and world state evolution.

Study material

Type	Name	Author	ISBN	URL	Edition, availability, ...	Examination material	Language
Book	Domain Ontologies and Reasoning Machines in Factory Automation	Martinez Lastra, J.L., Delamer, I.M., Ubis Lopez, F.	952-15-1522-8		TUT library		English
Book	Semantic Web Services in Factory Automa	Martinez Lastra J.L., Delamer I.M.	952-15-1374-8		TUT library		Suomi

Prerequisites

Additional information about prerequisites
Students interested on the course and no having the selected prerequisites are invited to visit the course's responsible and discuss his/her case in order to participate

Correspondence of content

There is no equivalence with any other courses

More precise information per implementation

	Description	Methods of instruction	Implementation
Implementation 1	This course provides an in-depth look at different knowledge representation languages and their application to intelligent manufacturing systems. The course will explore how reasoning machines are able to collaborate and automatically reconfigure to meet evolving production needs and achieve rapid product changeover. This is the basis for creating Rapidly Reconfigurable Manufacturing Systems (RRMS). Considering knowledge as the fundamental premise for attaining intelligence, the course will cover different automatic reasoning mechanisms based on logics and inference.

Last modified	07.04.2010
Modifier	Andrei Lobov