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ME
463
Computational Intelligence in Mechanical Engineering
Introduction to Computational Intelligence, types of knowledge-based systems, knowledge acquisition and representation, search strategies and inference process, expert systems, neural networks, and other implementation tools of Computational Intelligence, case studies of Computational Intelligence applications such as robotics, manufacturing, and thermal sciences.
Prerequisites:
0600307
0630463
(3-0-3)

Textbook:

Artificial Intelligence: A Modern Approach[,]{.underline} Russell, S., and Norvig, P., Englewood Cliffs, NJ: Prentice Hall, latest edition.

Coordinators:

Materials and Manufacturing TAG.

Prerequisites by Topic:

  1. Computer programming
  2. Numerical analysis

Course Objectives[^1]:

  1. To provide the student with an understanding of the emerging field of artificial intelligence. (1,3,4,5,6,7)
  2. To enable the student to apply tools and techniques from artificial intelligence to mechanical engineering problems. (1,3,4,5,6,7)

Topics:

  1. First-Order Logic and Inference
  2. Knowledge Acquisition and Representation
  3. Implementation of expert Systems and Neural Networks in Mechanical Engineering
  4. Engineering Applications

Evaluation:

  1. Quizzes and exams.
  2. Homework/assignments
  3. Project (written report, oral presentation)

Course Learning Outcomes:

Objective 1

1.1 Categorize various branches of artificial intelligence (AI).

1.2 Describe knowledge representations and knowledge acquisition techniques.

1.3 Identify various mechanical engineering problems that can be solved using AI tools.

Objective 2

2.1 Apply knowledge acquisition techniques.

2.2 Apply AI programming tools to solve problems in mechanical engineering.

Course Classification

Student Outcomes Level Relevant Activities
H, M, L
1. An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics. L AI programming methods, Application of AI tools to solve real engineering problems
2. An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors. L Implementation of expert systems and neural network in mechanical engineering
3. An ability to communicate effectively with a range of audiences. M Assignments and project
4. An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts. L Ethical implications of automation, Development of AI application
5. An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives. M Assignments and project
6. An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
7. An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. L Assignments and project

[^1]: Numbers in parentheses refer to the student outcomes