Course Name Code Semester T+U Hours Credit ECTS
Intelligent Maufacturing Systems ENM 406 8 3 + 0 3 5
Precondition Courses Artificial İntelligence and Expert Systems
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Optional
Course Coordinator Doç.Dr. ESRA TEKEZ
Course Lecturers
Course Assistants Res.Asst. Aysegul Aydin
Course Category
Course Objective Introducing and examining of intelligent manufacturing systems (IMS) which is becoming an area of growing interest in todays competitive and customer-oriented market.
Course Content Examining of intelligent manufacturing systems (IMS), characteristics of IMS, application samples of intelligent systems in manufacturing
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Student can define intelligent manufacturing systems Lecture, Question-Answer, Testing, Oral Exam,
2 Student can sort intelligent manufacturing systems Lecture, Question-Answer, Oral Exam, Testing,
3 Student can built model of intelligent manufacturing system Question-Answer, Self Study, Lecture, Testing, Homework,
4 Student can develop an intelligent manufacturing system Lecture, Question-Answer, Self Study, Testing, Homework,
5 Student can evaluate results of developed intelligent manufacturing system Case Study, Lecture, Testing,
6 Student can examine what goal intelligence use in manufacturing systems Case Study, Lecture, Homework,
Week Course Topics Preliminary Preparation
1 Evaluation of traditional manufacturing systems
2 The need to IMS and emergence of IMS
3 Examining of IMS
4 Intelligent Design
5 Intelligent Process Planning
6 Intelligent Process Planning
7 Intelligent Production Planning
8 Intelligent Production Planning / Quiz 1
9 Intelligent Quality Systems
10 Intelligent Quality Systems
11 Intelligent Quality Systems
12 Automatic Material Handling Systems
13 Automatic Material Handling Systems / Quiz 2
14 Agent-based Approaches in IMS
Course Notes
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Engineering graduates with sufficient knowledge background on science and engineering subjects of their related area, and who are skillful in implementing theoretical and practical knowledge for modelling and solving engineering problems. X
2 Engineering graduates with skills in identifying, describing, formulating and solving complex engineering problems, and thus,deciding and implementing appropriate methods for analyzing and modelling. X
3 Engineering graduates with skills in designing a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; for this purpose, skills in implementing modern design methods. X
4 Engineering graduates with skills in developing, selecting and implementing modern techniques and tools required for engineering applications as well as with skills in using information technologies effectively. X
5 Engineering graduates with skills in designing and conducting experiments, collecting data, analyzing and interpreting the results in order to evaluate engineering problems. X
6 Engineering graduates who are able to work within a one discipline or multi-discipline team,as well as who are able to work individually X
7 Engineering graduates who are able to effectively communicate orally and officially in Turkish Language as well as who knows at least one foreign language
8 Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology X
9 Engineering graduates with well-structured responsibilities in profession and ethics X
10 Engineering graduates having knowledge about practices in professional life such as project management, risk management and change management, and who are aware of innovation and sustainable development. X
11 Engineering graduates having knowledge about universal and social effects of engineering applications on health, environment and safety, as well as having awareness for juridical consequences of engineering solutions. X
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 60
1. Kısa Sınav 12
1. Ödev 15
2. Kısa Sınav 13
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 2 32
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 12 12
Assignment 1 10 10
Performance Task (Laboratory) 1 14 14
Total Workload 116
Total Workload / 25 (Hours) 4.64
dersAKTSKredisi 5