Expert Systems (IE416) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Expert Systems IE416 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Observation Case Study, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This course will provide students with the skills needed to identify appropriate areas for the application of expert system technologies and to familiarize them with the methodologies and tools used in industrial engineering. Students should be able to recognize organizational and societal impacts of expert system technologies in service and/or production environments. Students should be aware of cost considerations and implementation strategies.
Course Learning Outcomes The students who succeeded in this course;
  • Students will be able to make use of ES steps such as knowledge acquisition and knowledge validation representation.
  • Students will be able to design a knowledge structured integrated system for a variety of production and operations management modules.
  • Students will use various knowledge representation methods and export system structures for industrial engineering purposes.
  • Students will be able to follow the developments in AI and ES supporting the industrial engineering area.
Course Content Technology of expert systems and applications; development of a simple expert system; artificial intelligence concepts, heuristics, problem solving, intelligent attributes; use of expert systems in industry; intelligent decision support systems; case studies about engineering environments.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Fundamentals of expert systems
2 Knowledge acquisition and knowledge validation representation
3 Knowledge acquisition and knowledge validation representation
4 The tools for building efficient expert systems for industrial engineering applications
5 The tools for building efficient expert systems for industrial engineering applications
6 User interface and design issues and integration with decision support system
7 User interface and design issues and integration with decision support system
8 Midterm I
9 Basic concepts and procedures on how to select, initiate, implement, and manage the the expert system and how to cope with uncertainty
10 Basic concepts and procedures on how to select, initiate, implement, and manage the the expert system and how to cope with uncertainty
11 Evaluation of expert systems approaches
12 Evaluation of expert systems approaches Midterm II
13 Use of expert systems in industry, intelligent decision support systems, case studies in industrial engineering applications
14 Use of expert systems in industry, intelligent decision support systems, case studies in industrial engineering applications
15 The future of expert systems
16 Final Examination Period

Sources

Course Book 1. Jackson, P., Introduction to Expert Systems, Addison-Wesley, 1998
Other Sources 2. Durkin, J., Expert Systems Design and Development, Macmillan Publishing Company, 1994. Sillince, J., Business Expert Systems , Prentice Hall Professional Technical Reference, 1997 Liebowitz, J. and Letsky, C., Developing Your First Expert System - An Inte

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 60
Final Exam/Final Jury 1 40
Toplam 3 100
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Applies knowledge in mathematics, science, and computing to solve engineering problems related to manufacturing technologies.
2 Analyzes and identifies problems specific to manufacturing technologies.
3 Develops an approach to solve encountered engineering problems, and designs and conducts models and experiments.
4 Designs a comprehensive manufacturing system (including method, product, or device development) based on the creative application of fundamental engineering principles, within constraints of economic viability, environmental sustainability, and manufacturability.
5 Selects and uses modern techniques and engineering tools for manufacturing engineering applications.
6 Effectively uses information technologies to collect and analyze data, think critically, interpret, and make sound decisions.
7 Works effectively as a member of multidisciplinary and intra-disciplinary teams or individually; demonstrates the confidence and necessary organizational skills.
8 Communicates effectively in both spoken and written Turkish and English.
9 Engages in lifelong learning, accesses information, keeps up with the latest developments in science and technology, and continuously renews oneself.
10 Demonstrates awareness and a sense of responsibility regarding professional, legal, ethical, and social issues in the field of Manufacturing Engineering.
11 Effectively utilizes resources (personnel, equipment, and costs) to enhance national competitiveness and improve manufacturing industry productivity; conducts solution-oriented project and risk management; and demonstrates awareness of entrepreneurship, innovation, and sustainable development.
12 Considers the health, environmental, social, and legal consequences of engineering practices at both global and local scales when making decisions.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 10 1 10
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 20 40
Prepration of Final Exams/Final Jury 1 27 27
Total Workload 125