IE307 Quality and Reliability Engineering
Syllabus | International University of Sarajevo - Last Update on Apr 04, 2026
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Industrial Engineering
Benjamin Duraković
Course Lecturer
Course Objectives
•Introduce analyses of quality concepts •Develop skills to analyse quality culture in companies •Provide basic knowledge of quality and reliability in engineering
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
1) Montgomery, Dougles C.; Statistical Quality Control, Wiley, 2009, Asia
Additional Literature
(2) Summers, Donna C. S.; Quality, Pearson, 2010, London; (3) Chandrupatla, Tirupati R.; Quality and Reliability in Engineering, Cambridge University Press, 2009, CambridgeTeaching Methods
Lecture discussion and review questions; Short reports and homework assignments; Student presentation and discussions; Problem solving.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | General Introduction | Chapter 1 |
| 2 | Modern quality management | Chapter 1, 2 |
| 3 | Quality Control and Improvement | Chapter 3 |
| 4 | Statistical Inference in Quality Control | Chapter 4 |
| 5 | Statistical Inference in Quality Control | Chapter 4 |
| 6 | Regression in quality | Chapter 4 |
| 7 | Regression in quality | Chapter 4 |
| 8 | SPC Methods | Chapter 5 |
| 9 | Midterm | Ch. 1 – 4 |
| 10 | SPC - Variables Control charts (x̅R, x̅s, s2) | Chapter 5 |
| 11 | SPC - Attributer Control charts (p, np, c, u) | Chapter 6 |
| 12 | Process and Measurement Systems Capability | Chapter 7 |
| 13 | Process and Measurement Systems Capability | Chapter 8 |
| 14 | Reliability and Life Modeling | Chapter 13 |
| 15 | Exam review | Chapter 1-8 |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| IE307.1 | Course | Monday 15:00 - 17:50 | B F2.16 | - | - |
| IE307.2 | Tutorial | Tuesday 16:00 - 17:50 | A F1.23 | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Tuesday | 15:00 - 17:00 | A F1.15 | |
| Wednesday | 16:00 - 17:00 | A F1.15 | |
| Friday | 15:00 - 17:00 | A F1.15 |
Assessment Methods and Criteria
Assessment Components
Final - open book
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Midterm - open book
AI: Not AllowedAlignment with Learning Outcomes : 1 2
Homework
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lecture Hours
45 hours ⏳ (15 week × 3 h)
Tutorials
20 hours ⏳ (10 week × 2 h)
Midterm
35 hours ⏳ (5 week × 7 h)
Final
48 hours ⏳ (6 week × 8 h)
Homework
2 hours ⏳ (2 week × 1 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [IE307] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Apr 04, 2026 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| IE307 | Quality and Reliability Engineering | 3 | 2 | 6 | ||||||
| Prerequisite | Junior Standing | It is a prerequisite to | - | |||||||
| Lecturer | Benjamin Duraković | Office Hours / Room / Phone | Tuesday: 15:00-17:00 Wednesday: 16:00-17:00 Friday: 15:00-17:00 |
|||||||
| bdurakovic@ius.edu.ba | ||||||||||
| Assistant | Muhamed Bisić | Assistant E-mail | mbisic@ius.edu.ba | |||||||
| Course Objectives | •Introduce analyses of quality concepts •Develop skills to analyse quality culture in companies •Provide basic knowledge of quality and reliability in engineering |
|||||||||
| Textbook | 1) Montgomery, Dougles C.; Statistical Quality Control, Wiley, 2009, Asia | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Lecture discussion and review questions; Short reports and homework assignments; Student presentation and discussions; Problem solving. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | General Introduction | Chapter 1 | ||||||||
| Week 2 | Modern quality management | Chapter 1, 2 | ||||||||
| Week 3 | Quality Control and Improvement | Chapter 3 | ||||||||
| Week 4 | Statistical Inference in Quality Control | Chapter 4 | ||||||||
| Week 5 | Statistical Inference in Quality Control | Chapter 4 | ||||||||
| Week 6 | Regression in quality | Chapter 4 | ||||||||
| Week 7 | Regression in quality | Chapter 4 | ||||||||
| Week 8 | SPC Methods | Chapter 5 | ||||||||
| Week 9 | Midterm | Ch. 1 – 4 | ||||||||
| Week 10 | SPC - Variables Control charts (x̅R, x̅s, s2) | Chapter 5 | ||||||||
| Week 11 | SPC - Attributer Control charts (p, np, c, u) | Chapter 6 | ||||||||
| Week 12 | Process and Measurement Systems Capability | Chapter 7 | ||||||||
| Week 13 | Process and Measurement Systems Capability | Chapter 8 | ||||||||
| Week 14 | Reliability and Life Modeling | Chapter 13 | ||||||||
| Week 15 | Exam review | Chapter 1-8 | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final - open book | 1 | 40 | 1,2,3 | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm - open book | 1 | 40 | 1,2 | Not Allowed | |
| Homework | 5 | 20 | 1,2,3 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture Hours | 3 | 15 | 45 | Tutorials | 2 | 10 | 20 | |||
| Midterm | 7 | 5 | 35 | Final | 8 | 6 | 48 | |||
| Homework | 1 | 2 | 2 | |||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 01/04/2026 | |||||||||