COURSE UNIT TITLE

: QUALITY MANAGEMENT IN NANOSCIENCE AND ENGINEERING -II

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
NNE 5044 QUALITY MANAGEMENT IN NANOSCIENCE AND ENGINEERING -II ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR MEHMET ÇAKMAKÇI

Offered to

Nanoscience and Nanoengineering
Nanoscience and Nanoengineering
Nanoscience and Nanoengineering

Course Objective

To be able to develop and design a process that can meet customer expectations by using statistical process control techniques in nanoscience and nanoengineering.

Learning Outcomes of the Course Unit

1   To collect and analyze data in nanotechnological production process
2   Define process performance indicators in the nanotechnological production process
3   Measure process performance and adequacy in the nanotechnological production process
4   To be able to design experiments in nanotechnological production process
5   To evaluate the measurement process in the nanotechnological production process

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Quality improvement of nanotechnology in the production process
2 Quality improvement of nanotechnology in the production process
3 Introduction to six sigma methodology, a quick overview of quality development tools In the course applications, Excel and / or Minitab program will be used.
4 Planning a process development project In the course applications, Excel and / or Minitab program will be used.
5 Description: Data collection, data and scale types, data presentation In the course applications, Excel and / or Minitab program will be used.
6 Measuring the performance of the current process: Measuring In the course applications, Excel and / or Minitab program will be used.
7 Analysis of process data: Analysis, Hypothesis testing In the course applications, Excel and / or Minitab program will be used.
8 Process development, process design In the course applications, Excel and / or Minitab program will be used.
9 Development: Experimental design and ANOVA In the course applications, Excel and / or Minitab program will be used.
10 Development: Experimental design and Factorial Design In the course applications, Excel and / or Minitab program will be used.
11 Development: Experimental design and Taguchi Design In the course applications, Excel and / or Minitab program will be used.
12 Control and validation of the developed process In the course applications, Excel and / or Minitab program will be used.
13 Project presentations In the course applications, Excel and / or Minitab program will be used.
14 Project presentations In the course applications, Excel and / or Minitab program will be used.

Recomended or Required Reading

Textbook(s):
- Montgomery, Douglas C. Introduction to Statistical Quality Control, 6th Edition, John Wiley & Sons, Inc. New Yoruk, USA 2009
- Osanna, Peter H., Durakbasa, M. Numan, Basic Nanotechnology and Nanometrology, ISBN 3-901888-30-4, Vienna University of Technology,(2011).

Supplementary Book(s):
-Jye-Chyi Lu, Shuen-Lin Jeng, Kaıbo Wang, A Review of Statistical Methods for Quality Improvement and Control in Nanotechnology, Journal of Quality Technology, Vol. 41, No. 2, (2009).
-Leslie Pendrill, Olena Flys, Kai Dirscherl and Gert Roebben, European Consultation on Metrological Traceability, Standards and Dissemination of Metrology in Industrial Nanotechnology, CO-NANOMET EU FP7 CSA-CA 218764, Task 4.3, (2010).
-J.-C. Lu, Quality, Statistics and Reliability in Nanotechnology, Georgia Institute of Technology, Industrial & Systems Engineering, Atlanta. Retrieved from
http://chm.pse.umass.edu/NMSworkshop/protected/LuSlides.pdf.

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. All class members are expected to attend and both the lecture and take part in the discussion sessions. Besides the taught lecture, group presentations are to be prepared by the groups assigned for that week and presented to open a discussion session.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 PRJ PROJECT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.35 + PRJ * 0.15 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.35 + PRJ * 0.15 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

There will be minimum 2 projects, averaged out grades for which will be 15 % of the overall success of the students. mid-term examinations will be averaged and affect the grade by 35 %. Final exam will be 50 % of the resulting grade.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

mehmet.cakmakci@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Preparations before/after weekly lectures 12 3 36
Preparation for midterm exam 1 20 20
Preparation for final exam 1 30 30
Preparing assignments 2 22 44
Preparing presentations 1 30 30
Final 1 2 2
Midterm 1 2 2
0
TOTAL WORKLOAD (hours) 200

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7
LO.15544454
LO.25454555
LO.34555445
LO.44455445
LO.55554545

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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