IEN-434, Quality Systems I

2001 Catalog Data: IEN-434, Quality Systems I: Quality Assurance

Credits: (4-0-4) 

Course Description: This course covers the basics of modern methods of quality control and improvement that are used in the manufacturing and service industries. It includes quality philosophy and fundamentals, statistical methods of quality improvement, concept of variation and its reduction, statistical process control, acceptance sampling, designed experiments in quality improvement, and quality in the service sector. Deming’s quality concepts will also be discussed.

Prerequisites: IEN-332, Engineering Statistics II; or MATH-408, Probability and Statistics; or MATH-226, Management Statistics I

Co-requisites: None

Textbook: Introduction to Statistical Quality Control, by Douglas Montgomery, Fourth Edition, John Wiley and Sons, Inc.

References: Class handouts

Course Learning Objectives:

Upon completion of this course, the students should have the ability to:

• Define, recall and use the concept of statistical thinking. [IE PEO’s 1,3]

• Explain and apply the new quality philosophy. [ IE PEO’s 1,2,3]

• Relate variation reduction to process improvement. [IE PEO’s 1,3]

• Recognize the role of process control in process improvement. [IE PEO’s 1,2,3]

• Describe and apply the important concepts in Statistical Process Control (SPC). [IE PEO’s 1,2,3]

• Use the appropriate statistical methods to display and interpret quality data. [IE PEO’s 3,4]

• Apply appropriate tools for quality improvement. [IE PEO’s 3,4,5]

• Understand the basic TQM concepts. [IE PEO’s 1,2,3,4,5]

Prerequisites by Topics:

• Basic probability concepts 

• Descriptive statistics 

• Basic inferential statistics 

• Proficient in using MINITAB

Topics Covered:

• Quality philosophies, fundamentals and continuous improvement 

• Basic probability, statistical methods in quality improvement 

• Problem solving using simple quality tools

• Stabilizing and improving a process with control charts

• Quality improvement with designed experiments

• Acceptance sampling

• Deming’s 14 points for management

• Quality Function Deployment (QFD) and its applications

• Total Quality Management (TQM)

• Quality systems and systems integration

Class Schedule: 4 hours per week

Computer Usage: Statistical package MINITAB will be used throughout this course.

Laboratory Projects: None

Contribution to Meeting Professional Component: Required course

Relationship to Professional Component: 4 credit hours of engineering science

Prepared by: Tony Lin                                                                            Date: February 8, 2001