ECTS - Expert Systems
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 Lecturer(s) |
|
| 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;
|
| 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 | An ability to apply knowledge in mathematics and basic sciences and computational skills to solve manufacturing engineering problems | |||||
| 2 | An ability to define and analyze issues related with manufacturing technologies | |||||
| 3 | An ability to develop a solution based approach and a model for an engineering problem and design and manage an experiment | |||||
| 4 | An ability to design a comprehensive manufacturing system based on creative utilization of fundamental engineering principles while fulfilling sustainability in environment and manufacturability and economic constraints | |||||
| 5 | An ability to chose and use modern technologies and engineering tools for manufacturing engineering applications | |||||
| 6 | An ability to utilize information technologies efficiently to acquire datum and analyze critically, articulate the outcome and make decision accordingly | |||||
| 7 | An ability to attain self-confidence and necessary organizational work skills to participate in multi-diciplinary and interdiciplinary teams as well as act individually | |||||
| 8 | An ability to attain efficient communication skills in Turkish and English both verbally and orally | |||||
| 9 | An ability to reach knowledge and to attain life-long learning and self-improvement skills, to follow recent advances in science and technology | |||||
| 10 | An awareness and responsibility about professional, legal, ethical and social issues in manufacturing engineering | |||||
| 11 | An awareness about solution focused project and risk management, enterpreneurship, innovative and sustainable development | |||||
| 12 | An understanding on the effects of engineering applications on health, social and legal aspects at universal and local level during decision making process | |||||
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 | ||