Expert Systems (IE416) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Expert Systems IE416 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type N/A
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
Major Area Courses
Supportive Courses X
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 An ability to apply knowledge of mathematics, science and engineering to Industrial Engineering; an ability to apply theoretical and practical knowledge to model and solve engineering problems.
2 An ability to identify, formulate and solve complex engineering problems; an ability to select and apply proper analysis and modeling methods.
3 An ability to design a complex system, process, tool or component to meet desired needs within realistic constraints; an ability to apply modern design.
4 An ability to develop, select and put into practice techniques, skills and modern engineering tools necessary for engineering practice; an ability to use information technology effectively.
5 An ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or disciplinary research topics.
6 An ability to work individually, on teams, and/or on multidisciplinary teams.
7 Ability to communicate effectively in Turkish orally and in writing; knowledge of at least one foreign language; effective report writing and understand written reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instruction.
8 A recognition of the need for, and an ability to engage in life-long learning; an ability to use information-seeking tools and to follow the improvements in science and technology.
9 An ability to behave according to the ethical principles, an understanding of professional and ethical responsibility. Information on standards used in industrial engineering applications.
10 Knowledge of business applications such as project management, risk management and change management. A recognition of entrepreneurship, innovativeness. Knowledge of sustainable improvement.
11 Information on the effects of industrial engineering practices on health, environment and security in universal and societal dimensions and the information on the problems of the in the field of engineering of the era. Awareness of the legal consequences of engineering solutions.
12 An ability to design, development, implementation and improvement of integrated systems that include human, materials, information, equipment and energy.
13 Knowlede on appropriate analytical, computational and experimental methods to provide system integration.

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