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)
  • Assoc. Prof. Dr. Kamil Demirberk ÜNLÜ
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 [1] Chapter 1
2 Knowledge acquisition and knowledge validation representation [1] Chapter 1
3 Knowledge acquisition and knowledge validation representation [1] Chapter 1
4 The tools for building efficient expert systems for industrial engineering applications [1] Chapter 3
5 The tools for building efficient expert systems for industrial engineering applications [1] Chapter 3
6 User interface and design issues and integration with decision support system [1] Chapter 3
7 User interface and design issues and integration with decision support system [1] Chapter 4
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 [1] Chapter 5
10 Basic concepts and procedures on how to select, initiate, implement, and manage the the expert system and how to cope with uncertainty [1] Chapter 5
11 Evaluation of expert systems approaches [1] Chapter 6
12 Evaluation of expert systems approaches Midterm II [1] Chapter 6
13 Use of expert systems in industry, intelligent decision support systems, case studies in industrial engineering applications [1] Chapter 7
14 Use of expert systems in industry, intelligent decision support systems, case studies in industrial engineering applications [1] Chapter 7
15 The future of expert systems [1] Chapter 12
16 Final Exam

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 3 30
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 40
Toplam 5 100
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 Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. X
2 Ability to formulate, and solve complex mechatronics engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. X
3 Ability to design a complex mechatronics engineering system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. X
4 Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in mechatronics engineering and robot technology practices; ability to employ information technologies effectively. X
5 Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex mechatronics engineering and robot technology problems or research questions. X
6 Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7 Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
8 Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself
9 a-) Knowledge on behavior according to ethical principles, professional and ethical responsibility b-) Knowledge on standards used in engineering practices.
10 a-) Knowledge about business life practices such as project management, risk management, and change management b-) Awareness in entrepreneurship, innovation; knowledge about sustainable development.
11 Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.
12 Competency on defining, analyzing and surveying databases and other sources, proposing solutions based on research work and scientific results and communicate and publish numerical and conceptual solutions in the field of mechatronics engineering.
13 Consciousness on the environment and social responsibility, competencies on observation, improvement and modify and implementation of projects for the society and social relations and be an individual within the society in such a way that planning, improving or changing the norms with a criticism.

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
Presentation/Seminar Prepration 3 8 24
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 20 20
Prepration of Final Exams/Final Jury 1 33 33
Total Workload 125