• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Learning outcomes

Upon successful completion of this course, students will be able to:

1. Define basic concepts in statistical process control.

   Contribution to Program Outcomes

   1. Apply knowledge in a specialized area of chemical engineering and food technologies disciplines,
   2. Formulate and solve advanced engineering problems
   3. Work effectively in multi-disciplinary research teams
   4. Acquire scientific knowledge
   5. Design and conduct research projects independently
   6. Develop an awareness of continuous learning in relation with modern technology
   7. Find out new methods to improve his/her knowledge.
   8. Effectively express his/her research ideas and findings both orally and in writing
   9. Defend research outcomes at seminars and conferences.
   10. Write progress reports clearly on the basis of published documents, thesis, etc
   11. Demonstrate professional and ethical responsibility.

   Method of assessment

   1. Written exam
2. Gain how to draw and interpret process control charts.

   Contribution to Program Outcomes

   1. Apply knowledge in a specialized area of chemical engineering and food technologies disciplines,
   2. Formulate and solve advanced engineering problems
   3. Work effectively in multi-disciplinary research teams
   4. Acquire scientific knowledge
   5. Design and conduct research projects independently
   6. Develop an awareness of continuous learning in relation with modern technology
   7. Find out new methods to improve his/her knowledge.
   8. Effectively express his/her research ideas and findings both orally and in writing
   9. Defend research outcomes at seminars and conferences.
   10. Write progress reports clearly on the basis of published documents, thesis, etc
   11. Demonstrate professional and ethical responsibility.

   Method of assessment

   1. Written exam
   2. Homework assignment
3. Demonstrate an ability of performing process capability analysis and sampling.

   Contribution to Program Outcomes

   1. Apply knowledge in a specialized area of chemical engineering and food technologies disciplines,
   2. Formulate and solve advanced engineering problems
   3. Work effectively in multi-disciplinary research teams
   4. Acquire scientific knowledge
   5. Design and conduct research projects independently
   6. Develop an awareness of continuous learning in relation with modern technology
   7. Find out new methods to improve his/her knowledge.
   8. Effectively express his/her research ideas and findings both orally and in writing
   9. Defend research outcomes at seminars and conferences.
   10. Write progress reports clearly on the basis of published documents, thesis, etc
   11. Demonstrate professional and ethical responsibility.

   Method of assessment

   1. Homework assignment

Contents
Week 1:	Introduction to statistical process control
Week 2:	Basic concepts in statistical process control
Week 3:	Basic concepts in statistical process control (continued)
Week 4:	Problem solving techniques
Week 5:	Statistics review
Week 6:	Statistics review
Week 7:	MIDTERM EXAM
Week 8:	Construction of control charts for variables
Week 9:	Construction of control charts for variables (continued)
Week 10:	Construction of control charts for attributes
Week 11:	Construction of control charts for attributes (continued)
Week 12:	Interpretation of control charts
Week 13:	Process capability analysis
Week 14:	Sampling methods
Week 15*:	General review
Week 16*:	FINAL EXAM
Textbooks and materials:	1. Ders notları./Lecture notes. 2. Douglas C. Montgomery, 2005. Introduction to Statistical Quality Control. 5th ed. John Wiley and Sons, USA.
Recommended readings:	1. Leonard A. Doty, 1991. Statistical Process Control. Second edition. Industrial Press Inc., NY, USA. 2. Eugene L. Grant and Richard S. Leavenworth, 1980. Statistical Quality Control. 5th ed. McGraw-Hill, USA.
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:	8	30
Other in-term studies:		0
Project:		0
Homework:	2-6-10-14	30
Quiz:		0
Final exam:	16	40
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	3	14
Own studies outside class:	4	14
Practice, Recitation:	0	0
Homework:	6	10
Term project:	0	0
Term project presentation:	0	0
Quiz:	0	0
Own study for mid-term exam:	10	1
Mid-term:	2	1
Personal studies for final exam:	15	1
Final exam:	3	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)