AIMS:
The aims of the course are to develop student ability for conceptual planning and implementation of intelligent manufacturing systems and processes by deploying the theory of planning, machine learning and evolutiveness, based on artificial intelligence paradigms. After he/she becomes familiar with intelligent agents structure, with simulations and specialized software, the student will acquire knowledge necessary for the intelligent manufacturing systems development.
LEARNING OUTCOMES:
Implementation of software developed for modeling and analysis of intelligent manufacturing systems and processes. Independent selection of methods based on the application of artificial neural networks in the function of conceptual planning of autonomous mobile robots intelligent behavior. Advanced use of the software for simulation, with analysis and presentation of the results obtained. Capability for team work.
THEORETICAL TEACHING (Syllabus):
Introduction to knowledge - and machine learning-based intelligent systems. Machine learning model; deduction, induction and analogy. Machine learning as a basis of intelligent systems and processes. Evolutiveness and intelligent systems. Autonomy, basic concepts and importance. Autonomous mobile robots. The theory of manufacturing systems and processes planning. Tools for manufacturing systems planning. Components of manufacturing processes planning. Concepts of manufacturing processes planning. Group technology. Classification and coding. Causes for the CAPP systems development and introduction. Building components of the CAPP systems. Knowledge necessary for manufacturing processes planning. Automata. Logical approach. Graphs. Recognition of technological forms. CAPP systems architectures. Examples of developed systems.
PRACTICAL TEACHING (Syllabus):
Modeling and analysis of intelligent manufacturing systems and processes (laboratory work). Exemplified application of developed intelligent systems (laboratory work). Software architectures for intelligent systems machine learning. Empirical control algorithm-based on intelligent behavior. Architecture of intelligent systems based on proper competence level (autonomous mobile robot intelligent behavior planning). Computer aided manufacturing processes planning (CAPP - Computer Aided Process Planning). Data import in CAPP. Syntactic recognition. Integration of product planning and process planning via technological forms. Project design (CAPP; Intelligent control of autonomous mobile robot).
LEARNING RESOURCES:
[1] Z. Miljković, D. Aleksendrić, Artificial neural networks – solved examples with short theory introduction, Additional textbook, FME, 2009, 18.1 /In Serbian/ [2]B. Babić, FLEXY - Intelligent system for FMS design, Series IMS, Vol. 5, FME, 1994, 18.1 /In Serbian/ [3] Z. Miljković, Systems of artificial neural networks in production technologies, Series IMS, Vol. 8, FME, 2003, 18.1 /In Serbian/ [4] B. Babić, Design of manufacturing processes, Textbook 2nd ed., FME, 2004, 18.1 /In Serbian/ [5] Z. Miljković, Laboratory mobile robot prototype, Laboratory CeNT, FME, 18.12