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  Course Description
Course Name : Statistical Quality Control

Course Code : İSB322

Course Type : Optional

Level of Course : First Cycle

Year of Study : 3

Course Semester : Spring (16 Weeks)

ECTS : 6

Name of Lecturer(s) : Assoc.Prof.Dr. MAHMUDE REVAN ÖZKALE

Learning Outcomes of the Course : Use basic statistical techniques such as check sheet, histogram, pareto chart, cause and effect diagram, defect concentration diagram, scatter diagram
Explain the basics of statistical control charts
Distinguish between quantitative and qualitative control charts
Explain the importance of cumulative sum (CUSUM), exponentially weighted moving average (EWMA) and the moving average (MA) control charts
Interpret the control charts
Distinguish between process adequacy indices
Explain the role of acceptance sampling in quality control studies
Use statistical package programs for plotting control charts
Estimate the parameters of the process

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : None

Recommended Optional Programme Components : None

Aim(s) of Course : To determine whether the products derived after the completion of the production or during the production are at the desired quality and to apply the statistical techniques in order to provide the desired quality

Course Contents : Introduction to the concept of quality, control charts for variables and attributes, cumulative sum, exponentially weighted moving average and moving average control charts, process capability analysis, acceptance sampling

Language of Instruction : Turkish

Work Place : Faculty of Arts and Sciences Annex Classrooms


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Quality, history and basic concepts Source reading Lecture
2 Statistical quality control methods Source reading Lecture
3 Selection of control charts and control limits Source reading Lecture
4 x_bar and R control charts Source reading Lecture, problem-solving, using statistical package program
5 x_bar and S control charts Source reading Lecture, problem-solving, using statistical package program
6 p and np control charts Source reading Lecture, problem-solving, using statistical package program
7 c and u control charts Source reading Lecture, problem-solving, using statistical package program
8 mid-term exam Review the topics discussed in the lecture notes and sources Written exam
9 Cumulative control (CUSUM) charts Source reading Lecture, problem-solving, using statistical package program
10 Exponentially weighted moving average (EWMA) control charts Source reading Lecture, problem-solving, using statistical package program
11 Moving average (MA) control charts Source reading Lecture, problem-solving, using statistical package program
12 Process Capability Analysis Source reading Lecture, problem-solving
13 Process Capability Analysis Source reading Lecture, problem-solving
14 Acceptance Sampling Source reading Lecture, problem-solving
15 Acceptance Sampling Source reading Lecture, problem-solving
16/17 Final exam Review the topics discussed in the lecture notes and sources Written exam


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  1. Montgomery, D. C. (2009), Introduction to Statistical Quality Control. John Wiley & Sons 2. Bircan, H., Özcan, S. (2003), Excel Uygulamalı Kalite Kontrol. Yargı Yayınevi
Required Course Material(s)  Grant E. L., Leavenworth R. S. (1996). Statistical Quality Control (McGraw-Hill Series in Industrial Engineering and Management), McGraw-Hill; 7th edition.


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 80
    Homeworks/Projects/Others 1 20
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 Utilize computer systems and softwares 0
2 Apply the statistical analyze methods 4
3 Make statistical inference(estimation, hypothesis tests etc.) 2
4 Generate solutions for the problems in other disciplines by using statistical techniques 4
5 Discover the visual, database and web programming techniques and posses the ability of writing programme 0
6 Construct a model and analyze it by using statistical packages 5
7 Distinguish the difference between the statistical methods 4
8 Be aware of the interaction between the disciplines related to statistics 3
9 Make oral and visual presentation for the results of statistical methods 4
10 Have capability on effective and productive work in a group and individually 1
11 Develop scientific and ethical values in the fields of statistics-and scientific data collection 4
12 Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics 2
13 Emphasize the importance of Statistics in life 5
14 Define basic principles and concepts in the field of Law and Economics 0
15 Produce numeric and statistical solutions in order to overcome the problems 4
16 Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 3
17 Use proper methods and techniques to gather and/or to arrange the data 5
18 Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs 0
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 3 42
    Out of Class Study (Preliminary Work, Practice) 14 3 42
Assesment Related Works
    Homeworks, Projects, Others 1 20 20
    Mid-term Exams (Written, Oral, etc.) 1 15 15
    Final Exam 1 25 25
Total Workload: 144
Total Workload / 25 (h): 5.76
ECTS Credit: 6