| 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) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | ||||
| 2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | ||||
| 3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | ||||
| 4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | ||||
| 5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | ||||
| 6) Internalization and dissemination of professional ethical standards. | ||||
| 7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | ||||
| 8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | ||||
| 9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | ||||
| 10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | ||||
| 11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | ||||
| 12) Ability to acquire knowledge independently, and to plan one’s own learning. | ||||
| 13) Demonstration of advanced competence in the clarity and composition of written work and presentations. |
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | N | |
| 2) | Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | N | |
| 3) | Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | H | Exam,HW,Participation |
| 4) | Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | N | |
| 5) | Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | N | |
| 6) | Internalization and dissemination of professional ethical standards. | N | |
| 7) | Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | N | |
| 8) | Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | N | |
| 9) | Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | S | Participation |
| 10) | Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | S | HW,Participation |
| 11) | Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | N | |
| 12) | Ability to acquire knowledge independently, and to plan one’s own learning. | S | Exam,HW |
| 13) | Demonstration of advanced competence in the clarity and composition of written work and presentations. | H | Exam,HW |
| Prepared by and Date | MÜGE GÜLTEKİN ERZİN , February 2020 |
| Course Coordinator | UTKU KOÇ |
| Semester | Spring |
| Name of Instructor | Öğr. Gör. MÜGE GÜLTEKİN ERZİN |
| 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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| 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 | ||||||