ENM458 Statistical Quality Assurance Techniques

4 ECTS - 3-0 Duration (T+A)- 8. Semester- 3 National Credit

Information

Unit FACULTY OF ENGINEERING
INDUSTRIAL ENGINEERING PR.
Code ENM458
Name Statistical Quality Assurance Techniques
Term 2017-2018 Academic Year
Semester 8. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 4 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Belirsiz
Type Normal
Label C Compulsory
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. RIZVAN EROL
Course Instructor Prof. Dr. RIZVAN EROL (Bahar) (A Group) (Ins. in Charge)


Course Goal / Objective

The main objective of this course is to study statistical methods and tools for quality control, quality engineering and process improvement.

Course Content

Definition of quality and quality improvement, historical developments, basic statistical quality improvement methods, managerial aspects, description of variability, control charts for variables, control charts for attributes, non-conforming ratio charts, control charts for defect counts, selection criteria between the charts, process capability ratios, measurement capability, acceptance sampling, single, double and continuous sampling plans, Dodge-Romig plans.

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 He/she uses Statistical Process Control(SPC) methods for process monitoring and improvement.
LO02 He/she selects and applies an appropriate control chart type for a selected process or product quality characteristics.
LO03 He/she analyzes capability of a process or a measurement system.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 - Has sufficient background on topics related to mathematics, physical sciences and industrial engineering.
PLO02 - Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods.
PLO03 - Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems .
PLO04 - Gains ability to choose and apply methods and tools for industrial engineering applications.
PLO05 - Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions.
PLO06 - Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team.
PLO07 - Can access information and to search/use databases and other sources for information gathering.
PLO08 - Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously.
PLO09 - Can use computer software in industrial engineering along with information and communication technologies.
PLO10 - Can use oral and written communication efficiently.
PLO11 - Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession.
PLO12 - Has a conscious understanding of professional and ethical responsibilities.
PLO13 - Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice.
PLO14 - Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering.


Week Plan

Week Topic Preparation Methods
1 Quality improvement methods Reading lecture notes and references about the subject
2 Modeling process quality -review of basic statistical topics temel istatistik bilgisinin gözden geçirilmesi
3 Modeling process quality -random distributions Reading lecture notes and references about the subject
4 Statistical inference for assessing process quality Reading lecture notes and references about the subject
5 Statistical inference for assessing process quality Reading lecture notes and references about the subject
6 Basics of Statistical Process Control(SPC) Reading lecture notes and references about the subject
7 Control charts for variables - foundations Reading lecture notes and references about the subject
8 Control charts for variables - X, R and s charts Reading lecture notes and references about the subject
9 Midterm Exam Study for midterm exam
10 Control charts for attributes - foundations Reading lecture notes and references about the subject
11 Control charts for attributes - np, p, c and u charts Reading lecture notes and references about the subject
12 Process and measurement capability analysis Reading lecture notes and references about the subject
13 Acceptance sampling plans - foundations Reading lecture notes and references about the subject
14 Acceptance sampling plans - single, double and continuous sapling plans Reading lecture notes and references about the subject
15 Project presentations prepare the presentation
16 Final Exam Study for final exam
17 Final Exam Study for final exam


Assessment (Exam) Methods and Criteria

Assessment Type Midterm / Year Impact End of Term / End of Year Impact
1. Midterm Exam 100 40
General Assessment
Midterm / Year Total 100 40
1. Final Exam - 60
Grand Total - 100

Update Time: 22.08.2017 10:51