EASTERN MEDITERRANEAN UNIVERSITY Department of Industrial Engineering IENG484/MANE484 Quality Engineering Fall 2014-2015 COURSE OUTLINE Course Code Course Title Credit Value Pre-requisites IEN484/MANE484 Quality Engineering (4, 1) 4 Prepared by Asst.Prof. Dr. Emine Atasoylu Course Level Course Type ECTS Value Co-requisites 4th year Department Core 8 IENG385, MATH322 Semester and academic year Fall 2014 - 2015 Course Web Link : http://www.ie.emu.edu.tr/ go to lecturers-Emine Atasoylu-IENG484 Course Schedule : Monday 14:30-16:20 (IE-D101); Wednesday 8:30-10:20 (IE-D101); Friday: 8:30 IELAB2 Name (group) e-mail Office Telephone Emine Atasoylu, Asst.Prof. Dr. [email protected] C103 2815 Instructor Mazyar Ghadiri Nejad, MSc. [email protected] IE-B208 1592 Assistant(s) Seyed Mahdi Shavarani, MSc. [email protected] IE-B107 2808 COURSE DESCRIPTION The purpose of the course is to make an introduction and lay the foundations of modern methods of statistical quality control and improvements that are used in the manufacturing and service industries. The course also introduces basics of experimental design in determining quality products and reliability models. The students will first be introduced to some of the philosophies of quality control experts and their impact on quality. After a quick review of normal probability distribution, a few graphical methods used to monitor quality improvement will be given. Control charts for variables and attributes will be given with examples. Acceptance sampling plans for variables and attributes are to follow. Principles of design of experiments along with Taguchi method will be presented. Finally reliability of systems like series, parallel, series – parallel and parallel – series systems and their design will be discussed. COURSE OBJECTIVES (CO): 1. To help students understand the history and philosophies of statistical quality control (SO h, i, j). 2. To introduce the students to modern methods of statistical quality control (SQC) including the construction of control charts used to control variable and attribute characteristics (SO a, b, c, e & k). 3. To teach the development of acceptance sampling plans for finished goods (SO a, b, c, e & k). 4. To introduce basic concepts of quality standards, lean methodology, six sigma and reliability of systems used in manufacturing industries (SO a, b, e & k). 5. To train the students to use the above ideas in real life situations (SO a, b, c, d, e, g, h, i, j & k). 6. To use computer software packages for SQC and improvement (SO b, e, & k). COURSE LEARNING OUTCOMES On successful completion of this course, all students would have developed knowledge and understanding of:  Basic concepts of quality, lean, six sigma and reliability in industries, (CO 1, 2 &4),  Basic philosophies of quality by statistical quality control experts (CO 1),  Various control charts to maintain statistical process control (CO 2),  Acceptance or rejection of finished products using acceptance sampling plans (CO 3),  Analyzing case studies. (CO 2, 3, 4 & 5) On successful completion of the course, all students will have developed their skills in:  The definition of quality in different applications, (CO1)  The statistical tools that are used to improve manufacturing processes, (CO 2, 3&4)  Methods to inspect incoming lots of finished goods, (CO 3)  Selecting appropriate control charts for various process characteristics under different environments, (CO2)  Interpretation of the control charts developed, (CO 2)  Application of software tools in process control (CO 6) On successful completion of the course, all students will have developed their appreciation of and respect for values and attitudes regarding the issue of:  Importance of statistical process control in industries (CO 1, 2, 3, 4 & 5),  Importance of acceptance sampling procedures in vendor selection (CO1, 2, & 3),  Importance of modern process control software (CO 6),  Reliability methods in improving product quality (CO 4). TEXTBOOK/S Fundamentals of Quality Control and Improvement, Amitava Mitra, 3rd Edition, Wiley, 2011. Quality Improvement, Dale H. Besterfield, 9th Edition, Prentice Hall, 2012 RECOMMENDED READING Fundamentals of Quality Control and Improvement, Amitava Mitra, 2 nd Edition, Prentice Hall, 1998. Statistical Process Control and Quality Improvement, Gerald M.Smith, Prentice Hall 5th Edition, 2004. Mastering Process Control, Tim Stanpenhurst, Elsevier 2005 Statistical Quality Design and Control, DeVor, Chang and Sutherland, 2nd Edition, Prentice Hall, 2007 Quality, Donna C.S. Summers, 5th edition, Prentice Hall, 2010 Introduction to Statistical Quality Control, Douglas C. Montgomery, 6th Edition, Wiley, 2009 COURSE SCHEDULE Week Topics Course outline. Learning objectives. Useful references. Weekly schedule. Homework’s, assignments, exams and expectations of instructor. 1 Evolution of quality control. Philosophies of quality by statistical quality control experts-Deming’s 14 points. Quality improvement tools: FMEA, QFD, ISO9000, ISO14000, TPM, quality by design, products liability, IT. 2 Lean Enterprise, benefits, lean fundamentals: types of waste, categories of waste, workplace organization, concepts of flow, inventory control, visual management, kaizen, value stream. 3 Six Sigma: statistical aspects, improvement methodology DMAIC Review of normal distribution. 4 Graphical methods for quality improvement. 5 Statistical Process control using control charts Control charts for variables: mean and range, mean and standard deviation.. 6 Control charts for variables: mean and moving range. 7 Process capability, 6σ, Cp,Cr,Cpk. MIDTERM EXAMs 8-9 Control Charts for attributes: p-chart for a) constant and b) variable sample size. 10 Control Charts for attributes: np-, c-, u- and U-charts. 11 Acceptance Sampling: fundamental concepts, advantages and disadvantages of sampling, types of sampling plans, random sample selection 12 Consumer producer relationship, producer’s risk, consumer’s risk, AQL, LQL, Comparing sampling plans: OC curves, AOQ, ASN, ATI. Acceptance Sampling: design of single and double sampling plans. 13 Sampling plans for variables. Reliability: definition, system reliability, determining reliability in a) a series system b) a parallel system 14 Class Schedule Tutorial Schedule 4 hours of lecture per week by the course instructor ------- Laboratory Schedule 2 hrs of Lab per week with course assistants. SPSS, Minitab and Excel software packages will be used. (The Lab schedule will be announced on the course web site) Presentation ------- GRADING POLICY:  Laboratory 10%  Quizzes & Project Assignments 20%  Interim exam I 20%  Interim exam II 20%  Final exam 30% Note that the instructor reserves the right to modify the grading policy in case she finds it necessary. METHOD OF ASSESSMENT All examinations will be closed book/closed notes type, based on lectures, discussions, textbook and assigned work, tables will be provided. To enter a formal examination, a student has to present her/his EMU student identification card to the invigilator. Quizzes: There will be quizzes designed to test familiarity and basic understanding of various topics. There will be no quiz make-ups. (Quizzes can take place any time during lectures) Interim Exams: The first interim exam will be held in the week (midterm week) designated by the university administration. The date of the second interim exam will be announced later in class. Both will cover all of the material up to the date of examination. Final Exam: The final exam will cover the whole course material. In form it will be a longer version of the midterm exam. Make-up Exams: Make-up examinations will only be offered to students who provided adequate documentation for the reason of their absence within four working days at the latest after the examination date. University regulations apply for graduation make-ups. RELATIONSHIP OF COURSE TO STUDENT OUTCOMES Level of Contribution Student Outcomes Moderate High NO (a) an ability to apply knowledge of mathematics, science and engineering    (b) an ability to design and conduct experiments, as well as to analyze and interpret data    (c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability    (d) an ability to function on multi-disciplinary teams    (e) an ability to identify, formulate, and solve engineering problems    (f) an understanding of professional and ethical responsibility    (g) an ability to communicate effectively    (h) the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context    (i) a recognition of the need for, and an ability to engage in life-long learning    (j) a knowledge of contemporary issues    (k) an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice    CONTRIBUTION OF COURSE TO MEETING THE REQUIREMENTS OF ABET CRITERION 5 Mathematics and Basic Sciences : 0 % Engineering Science : 50 % Engineering Design : 50 % General Education : 0 % ATTENDANCE Attendance will be taken every lecture hour. Note that university regulations allow the instructor to give a grade of NG to a student whose absenteeism is more than 25% of the total lecture hours or who do not complete sufficient work. ACADEMIC HONESTY - PLAGIARISM Cheating is copying from others or providing information, written or oral, to others. Plagiarism is copying without acknowledgement from other people’s work. According to university by laws cheating and plagiarism are serious offences punishable with disciplinary action ranging from simple failure from the exam or project, to more serious action (letter of official warning suspension from the university for up to one semester). Disciplinary action is written in student records and may appear in student transcripts. PLEASE KEEP THIS COURSE OUTLINE FOR FUTURE REFERENCE AS IT CONTAINS IMPORTANT INFORMATION