CEI334 Intelligent Automation Syllabus:
CEI334 Intelligent Automation Syllabus – Anna University Regulation 2021
COURSE OBJECTIVES:
1. To identify potential areas for automation and justify need for automation
2. Study the concepts of Artificial Intelligence.
3. Learn the methods of solving problems using Artificial Intelligence.
4. Apply the concept of AI to attain industrial automation
UNIT I INTRODUCTION TO AUTOMATION
Introduction to Industrial Automation – Automation in Production System- Principles and Strategies of Automation – Basic Elements of an Automated System- Advanced Automation Functions- Levels of Automations- Production Economics – Methods of Evaluating Investment Alternatives- Costs in Manufacturing- Break Even Analysis- Unit cost of production- Cost of Manufacturing Lead time and Work-in-process.
UNIT II INTRODUCTION TO ARTIFICAL INTELLIGENCE
Introduction to Artificial Intelligence -Introduction-Foundations of AI- History of AI- Intelligent agents: Agents and Environment- Reactive agent- deliberative- goal driven- utility driven and learning agents -Artificial Intelligence programming techniques. Introduction to ML and DL Concepts.
UNIT III KNOWLEDGE AND REASONING
Knowledge Representation and Reasoning – Ontologies-foundations of knowledge representation and reasoning-representing and reasoning about objects- relations- eventsactions- time- and space- predicate logic-situation calculus- description logics-reasoning with defaults-reasoning about knowledge-sample applications- Representing Knowledge and reasoning in an Uncertain Domain- Bayes rule-Bayesian networks-probabilistic inferencesample applications- Planning: planning as search- partial order planning- construction and use of planning graphs.
UNIT IV EXPERT SYSTEMS
Expert systems -Expert systems – Architecture of expert systems, Roles of expert systems – Knowledge Acquisition – Meta knowledge- Heuristics. Typical expert systems – MYCIN – ARTXOON.
UNIT V AI IN CONTROL SYSTEMS
Industrial AI applications and Case studies – Applications of Industrial AI in Monitoring optimization and control- AI applications in Industry Automation using -natural language processing-computer vision-speech recognition-computer vision.
TOTAL: 45 PERIODS
SKILL DEVELOPMENT ACTIVITIES (Group Seminar/Mini Project/Assignment/Content Preparation / Quiz/ Surprise Test / Solving GATE questions/ etc)
1 A seminar on detailed study about existing control methods using AI
2 Designing an AI to recognize face and to authenticate.
3 Train an AI to read alarm codes and take action.
COURSE OUTCOMES:
CO1 Understand the basics AI algorithms.
CO2 Identify appropriate AI methods to solve a given problem.
CO3 Illustrate about AI/ML/DL techniques in Industrial Automation.
CO4 Summarize the levels of automation.
CO5 Ability to apply AI concepts for industrial optimization and control.
REFERENCES
1 Anuradha Srinivasaraghavan, Vincy Joseph “Machine Learning”, Wiley, 2019.
2 Stuart Russell and Peter Norvig, “Artificial Intelligence: A Modern Approach”, 2nd Edition, Prentice Hall, 2003.
3 Rajiv Chopra, “Deep Learning”, 1st edition, Khanna Publishing House,2018.