JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

UNIT - I

Knowledge and Processing – Knowledge and Intelligence- logic frames- production systems. Fundamentals of Fuzzy logic-characteristics of fuzzy logic and systems-Fuzzy sets-Fuzzy number- Equality of fuzzy sets- Empty Fuzzy set –Fuzzy point-universal Fuzzy set. Operations on Fuzzy sets- Intersection-union –complement.

UNIT - II

Fuzzy Relations-classical N-Array Relation-Reflexivity-Anti reflexivity-symmetricity –Transitivity- Equivalence-Binary fuzzy relations, operation on Fuzzy relations-Intersection-union-projection- Cartesian product.

UNIT - III

Fuzzy Implications, Translation rules, Triangular norms, Triangular conorm, Fuzzy Rule base system, Fuzzy logic controller, Defuzzification Methods, Fuzzy logic applications-prevention of Road accidents-control room temperature-Robot control system-domestic applications-Industrial applications.

UNIT - IV

Basic concepts of Neural Network-Processing units-connection between units-output rules- Network topologies-paradigms of learning –perception, Back-propagation, classification Models-Association Models, optimization models.

UNIT - V

Rule Based Neural Networks-Network Training –Application of Neural Network in Mathematical Modeling- Knowledge based approaches-applications in Mechanical Engineering –Fuzzy –Neural, example, Neuro –Fuzzy examples-Intelligence in Automation.

REFERENCES:

• 1. Fuzzy logic &Neural Networks/ Chennakesava R. Alavala/ New Age International, 2008
• 2. Intelligent Control Fuzzy Logic Applications/ Clarence W.de Silva/ CRS Press, 1995.
• 3. Fuzzy Logic with engineering Applications/ Timothy J. Ross/ McGraw Hill Inc., 1995.
• 4. Neural Networks in Computer Intelligence/ Limin Fu / Tata McGraw Hill Publishing Company Ltd., 2003
• 5. Stamations and Understanding Neural Networks and Fuzzy Logic/ V. Karthalopoulos Basic concepts Applications, IEE Neural Networks Council PHI 2001.
• 6. Neural Networks Algorithms, Applications/ James A. Freeman and David M. Skapura & Programming Techniques/ Pearson Education Asia, 2001
• 7. Artificial Neural Networks/ Yegnarayane. B/ Prentice Hall- 2001.
• 8. N.P. Padhya & S.P. Simon, soft computing with MAT LAB Programming, Oxford University Press, 2015. I Year -I Sem. M. Tech (Automation) MANUFACTURING SIMULATION & PRECISION ENGINEERING LABORATORY A. MANUFACTURING SIMULATION The students will be given training on the use and application of the following software to manufacturing problems:
• 1. Auto MOD Software.
• 2. PROMODEL
• 3. SLAM-II
• 4. CAFIMS
• 5. Flexsim They also learn how to write sub routines in C-language and interlinking with the above packages. Problems for modelling and simulation experiments:
• 1. AGV planning
• 2. ASRS simulation and performance evaluation
• 3. Machines, AGVs and AS/RS integrated problems
• 4. JIT system
• 5. Kanban flow
• 6. Material handling systems
• 7. M.R.P. Problems
• 8. Shop floor scheduling etc. B. PRECISION ENGINEERING
• 1. Hydraulic and Pneumatic circuits
• 2. Closed loop control systems
• 3. Study of the chip formation in turning process
• 4. Study of operation of tool and cutter grinder, twist drill grinder, Centreless grinder
• 5. Determination of cutting forces in turning
• 6. Experiments in unconventional manufacturing processes-AJM and study of USM, EDM, Laser Machining and Plasma spraying
• 7. Inspection of parts using tool makers microscope, roughness and form tester
• 8. Study of micro-controllers, programming on various CNC machine tools and also controllers
• 9. Studies on PLC programming
• 10. Study and programming of robots
• 11. Condition monitoring in machining process using acoustic emission.