Information Package / Course Catalogue
| Computer Engineering | |||||
| Bachelor | Length of the Programme: 4 | Number of Credits: 240 | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF: Level 6 |
Ders Genel Tanıtım Bilgileri
| School/Faculty/Institute | Faculty of Engineering | ||||
| Course Code | IE 302 | ||||
| Course Title in English | Quality Engineering | ||||
| Course Title in Turkish | Kalite Mühendisliği | ||||
| Language of Instruction | EN | ||||
| Type of Course | Flipped Classroom,Lecture | ||||
| Level of Course | Intermediate | ||||
| Semester | Spring | ||||
| Contact Hours per Week |
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| Estimated Student Workload | 133 hours per semester | ||||
| Number of Credits | 5 ECTS | ||||
| Grading Mode | Standard Letter Grade | ||||
| Pre-requisites |
MATH 222 - Probability and Statistics for Engineering II | MATH 228 - Probability and Statistics for Engineering II |
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| Expected Prior Knowledge | Basic probability and statistics knowledge | ||||
| Co-requisites | None | ||||
| Registration Restrictions | - | ||||
| Overall Educational Objective | To learn statistical methods/problem solving techniques to improve product/service quality | ||||
| Course Description | This course covers the fundamental methods of quality engineering that are needed in today’s industry applications. The emphasis is on the statistical tools of quality engineering systems. Moreover, the course discusses quality excellence models, cost models, quality audit programs and quality information systems. | ||||
| Course Description in Turkish | Bu ders günümüz üretim ve servis sektöründe gerekli olan temel kalite mühendisliği metotlarını kapsamaktadır. Kalite mühendisliği sistemlerinin istatistiksel araçları üzerine odaklanmaktadır. Ayrıca kalite mükemmellik modelleri, maliyet modelleri, kalite denetleme programları ve kalite bilgi sistemleri konularını içermektedir. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) understand the major concepts of quality and key customer needs to improve product and service quality continuously; 2) use the statistical process control methodology for monitoring and improving the production and service processes; 3) perform process capability and measurement system capability studies; 4) understand how to design and analyze engineering experiments. |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 |
|---|---|---|---|---|
| 1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | ||||
| 2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | ||||
| 3) An ability to communicate effectively with a range of audiences | ||||
| 4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ||||
| 5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ||||
| 6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | ||||
| 7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. |
Relation to Program Outcomes and Competences
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | H | Exam,HW,Lab |
| 2) | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | N | |
| 3) | An ability to communicate effectively with a range of audiences | N | |
| 4) | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | N | |
| 5) | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | N | |
| 6) | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | H | Exam,HW,Lab |
| 7) | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. | N |
| Prepared by and Date | MÜGE GÜLTEKİN ERZİN , February 2020 |
| Course Coordinator | UTKU KOÇ |
| Semester | Spring |
| Name of Instructor | Öğr. Gör. MÜGE GÜLTEKİN ERZİN |
Course Contents
| Week | Subject |
| 1) | General Introduction to Quality Improvement |
| 2) | Probability Distributions |
| 3) | Measurement System Analysis |
| 4) | Capability Analysis |
| 5) | Process Analysis (VSM, Muda) |
| 6) | Data Analysis (Hypothesis Testing, Regression) |
| 7) | Data Analysis (Hypothesis Testing, Regression) |
| 8) | Design of Experiments |
| 9) | Design of Experiments |
| 10) | Risk Analysis (FMEA) |
| 11) | Control Charts |
| 12) | Control Charts |
| 13) | Acceptance Sampling |
| 14) | Acceptance Sampling |
| 15) | Final Exam/Project/Presentation Period |
| 16) | Final Exam/Project/Presentation Period |
| Required/Recommended Readings | Montgomery, Douglas C., Statistical Quality Control: A Modern Introduction, John Wiley & Sons, Inc, Seventh Edition, 2014 | ||||||||||||||||||
| Teaching Methods | Lectures/contact hours using “flipped classroom” as an active learning technique/implement the methods learned in class at a computer lab | ||||||||||||||||||
| Homework and Projects | There will be homework. | ||||||||||||||||||
| Laboratory Work | Yes (to implement methods learned in class) | ||||||||||||||||||
| Computer Use | Yes – Minitab Software | ||||||||||||||||||
| Other Activities | - | ||||||||||||||||||
| Assessment Methods |
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| Course Administration |
gultekinm@mef.edu.tr - Attendance: Attendance is taken, but not graded. Students can attend only the sections they are registered to. You are responsible for the announcements made in class and in labs. (You may miss some of the quizzes and graded lab activities if you do not attend classes regularly.) Exam/Quiz/Homework/Lab Grading Appeals: Every effort will be made to ensure that grading is as objective and fair as possible. If you believe that there is an error in grading, please make an appointment with me within one week after the announcement of the grades. However, be advised that your grade could increase or decrease based on the second grading. Quizzes and Lab Work: No lab reports will be accepted or no make-up will be given for a missed lab. Lab works are to be done as a group and most of it cannot be reproduced outside the lab. No make-up will be given for a missed quiz. 10% bonus will be given to compensate for the missed quizzes and lab work. Missing a quiz or lab work: No make-up will be given since one of the worst quiz grades will be excluded in the calculation of the total grade. Homework: Not all homework will be graded. The lowest homework grade will not be included in the calculation of the final grade. Missing a homework: No make-up will be given since one of the worst homework grades will be excluded in the calculation of the total grade. Midterm: There will be one Midterm Exam. Missing a midterm: You are expected to be present without exception and to plan any travel around these dates accordingly. Medical emergencies are of course excluded if accompanied by a doctor’s note. A note indicating that you were seen at the health center the day of the exam is not sufficient documentation of a medically excused absence from an exam. The note must say that you were medically unable to take the exam. If you fail to take the exam on the assigned day and do not have a valid excuse, you will be given a zero (0) on the exam. Employment interviews, employer events, weddings, vacations, etc. are not excused absences. Provided that proper documents of excuse are presented for absence in the midterm, a make-up will be given as soon as possible. It is the student's responsibility to contact the instructor in at most 3 days after the regular exam date, if they need to take a make-up. Final: There will be one Final Exam. Missing a final: Faculty regulations. Eligibility to enter the final exam: Students are required to achieve 25% success rate as the average of the midterm exam, quizzes, homework and labs in order to enter the final exam. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations (http://students.mef.edu.tr/tr/lisans-ve-onlisans-yonetmeligi#) |
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ECTS Student Workload Estimation
| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 1 | 3 | 1 | 70 | ||
| Laboratory | 5 | 1 | 1 | 1 | 15 | ||
| Homework Assignments | 5 | 1 | 1 | 10 | |||
| Midterm(s) | 1 | 14 | 2 | 16 | |||
| Final Examination | 1 | 20 | 2 | 22 | |||
| Total Workload | 133 | ||||||
| Total Workload/25 | 5.3 | ||||||
| ECTS | 5 | ||||||