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Course Description Course Name : Statistical Methods For Quality Course Code : ENM416 Course Type : Compulsory Level of Course : First Cycle Year of Study : 4 Course Semester : Spring (16 Weeks) ECTS : 7 Name of Lecturer(s) : Prof.Dr. RIZVAN EROL Learning Outcomes of the Course : He/she uses Statistical Process Control(SPC) methods for process monitoring and improvement. He/she selects and applies an appropriate control chart type for a selected process or product quality characteristics. He/she analyzes capability of a process or a measurement system. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The main objective of this course is to study statistical methods and tools for quality control, quality engineering and process improvement. Course Contents : 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. Language of Instruction : Turkish Work Place : industrial engineering classrooms and labs   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Quality improvement methods reading the related textbook chapter lecturing, discussion 2 Modeling process quality -review of basic statistical topics review of basic statistical methods ecturing, discussion 3 Modeling process quality -random distributions reading the related textbook chapter ecturing, discussion 4 Statistical inference for assessing process quality reading the related textbook chapter ecturing, discussion 5 Statistical inference for assessing process quality reading the related textbook chapter ecturing, discussion 6 Basics of Statistical Process Control(SPC) reading the related textbook chapter ecturing, discussion 7 Control charts for variables - foundations reading the related textbook chapter ecturing, discussion 8 Control charts for variables - X, R and s charts reading the related textbook chapter ecturing, discussion 9 Midterm Exam preparation for the exam written exam 10 Control charts for attributes - foundations reading the related textbook chapter ecturing, discussion 11 Control charts for attributes - np, p, c and u charts reading the related textbook chapter ecturing, discussion 12 Process and measurement capability analysis reading the related textbook chapter ecturing, discussion 13 Acceptance sampling plans - foundations reading the related textbook chapter ecturing, discussion 14 Acceptance sampling plans - single, double and continuous sapling plans reading the related textbook chapter ecturing, discussion 15 Project presentations preparation for the presentation project presentations 16/17 Final Exam preparation for the exam written exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  MONTGOMERY, D. C., 2008, Introduction To Statistical Quality Control (6th edition), John Wiley& Sons, Inc.  MONTGOMERY, D. C, 2010, JENNINGS, C. L, PFUND, M. E., Managing, Controlling, and Improving Quality, John Wiley& Sons, Inc. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 75     Homeworks/Projects/Others 5 25 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 Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions. 4 2 Has sufficient background on topics related to mathematics, physical sciences and industrial engineering. 3 3 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. 3 4 Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems . 4 5 Gains ability to choose and apply methods and tools for industrial engineering applications. 3 6 Can access information and to search/use databases and other sources for information gathering. 3 7 Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team. 3 8 Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously. 2 9 Can use computer software in industrial engineering along with information and communication technologies. 2 10 Can use oral and written communication efficiently. 2 11 Has a conscious understanding of professional and ethical responsibilities. 2 12 Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession. 0 13 Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice. 2 14 Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering. 3 * 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 4 56     Out of Class Study (Preliminary Work, Practice) 3 9 27 Assesment Related Works     Homeworks, Projects, Others 5 10 50     Mid-term Exams (Written, Oral, etc.) 1 15 15     Final Exam 1 15 15 Total Workload: 163 Total Workload / 25 (h): 6.52 ECTS Credit: 7