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 | 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 | ||