Ise 426 Statistical Quality Control


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ISE 426 STATISTICAL QUALITY CONTROL

Instructor:

Prof. Qiang Huang Epstein Department of Industrial & Systems Engineering

Office:

GER 241

Office hours: MW: 4:30pm-5:30pm

Other time by appointment

Tel:

(213) 740-2433

Class Schedule: Lecture: MW 2:00pm-3:20pm, KAP146 Website: blackboard.usc.edu Smart Phone App: Bb MobileLearn E-mail: [email protected]

TA: Ye Wang, Office: GER 236; Office hours: TBD

PREREQUISITE: ISE 225 Engineering Statistics I (or equivalent)

REQUIRED TEXT: TEXT Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery,
2013, John Wiley & Sons, Inc., New York. References
Engineering Statistics by Douglas C. Montgomery, George C. Runger, and Norma F. Hubele, John Wiley & Sons, Inc., New York. Applied Statistics and Probability for Engineers Second Edition by Douglas C. Montgomery and George C. Runger, 1999, John Wiley & Sons, Inc., New York.

COURSE OBJECTIVES This course will present the theory and methods of quality monitoring including process capability, control charts, acceptance sampling, quality engineering, and quality design. The objectives include
• To understand the basic concepts of quality monitoring. • To understand the statistical underpinnings of quality monitoring. • To learn various available statistical tools of quality monitoring. • To learn the statistical and economical design issues associated with the
monitoring tools. • To demonstrate the ability to design and implement these tools.

SEMESTER CALENDAR August 25, first day of class September 1, Labor Day Wednesday, October 8, Midterm Exam November 26-29: Thanksgiving December 5, last day of class Friday, December 12th, Final Exam, 2:00-4:00pm

ISE 426 Statistical Quality Control –Fall 2014

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Instructor: Prof. Qiang Huang, Ph.D.

1.

TENTATIVE COURSE SCHEDULE

Week Date

1

Lecture

Topics Introduction to the course / Chapter 1: Quality Improvement in the Modern Business Environment and Introduction to Statistical Computing with R
Chapter 2: DMAIC Process

Lecture 2

Chapter 3: Modeling Process Quality and R Chapter 4: Inferences about Process Quality and R (HW#1)

3

Lecture

Chapter 5: Methods and Philosophy of Statistical Process Control

4 Lecture

Chapter 6: Control Charts for Variables

5,6 Lecture
7,8,9 Lecture Lecture
10,11,12

Chapters 6 (HW#2)

Proposal presentation

Lab Use Excel to plot control charts in Ch6

Chapter 7: Control Charts for Attributes (HW#3) Midterm Exam

Lab Use Excel to plot control charts in Ch7

Chapter 8: Process and Measurement System Capability Analysis (HW#4)

Lab Use Excel to Process Capability in Ch8

13,14

Chapter 9: Cumulative Sum and Exponentially Weighted Lecture Moving Average Control Charts (HW#5)
Lab Use Excel to plot control charts in Ch9

14

Lecture

15

Lab Lecture

Chapters 15: Acceptance Sampling for Attributes (HW#6) Use Excel to solve problem in sampling
Chapter 15 Final Exam Review and Q&A Final project presentation

2.

COURSE GRADING

Homework sets

= 30%

Exams

= 60% (Midterm Exam: 30%, Final Exam: 30%)

Project

= 10% (Due on Monday, November 25)

Total = 100%

Grading scale:

A: [95, 100]; A-: [90, 95); B+: [85, 90); B: [80, 85); B-: [75, 80);

C+: [70, 75]; C: [65, 70); C-: [60, 65); D: [50, 60); F: <50 PROJECT will be due on Monday, November 25.

3.

CLASS PROJECT

Please form a team of three or four. In the final project report, all team members should sign and

state that they contribute to their project roughly equally. Every member will receive the same

grade on the project.

All reports should be typewritten and printed out for handing in. The report should not exceed 8 pages. (12 point, double space, Appendix does not count to 8 pages.) The report must have a

ISE 426 Statistical Quality Control –Fall 2014

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Instructor: Prof. Qiang Huang, Ph.D.

professional appearance. Clarity and thoroughness of the analysis, and good use of the English language, including grammar, spelling and punctuation, are considered in grading the project.

Final project report includes project objective, problem statement, solutions, conclusions, and appendix if needed. The report should describe the background, any assumptions made, the analysis used to analyze the data, and the appropriate results. Explanation, interpretation, and justifications are required. Computer output should be included in an appendix and the description of the outcome/results included in the text of the report.

Sample Class Projects:

Example 1: IPod Nano Nike Plus System Capability Analysis: The team used IPod Nano to measure the distance and time of runs and analyze the capability (repeatability and reproducibility) of the device’s pedometer.

Example 2: Heart Failure Discharge Rate Analysis for Medicare Patients: The team collected data on the discharge rate of Medicare patients with heat failure in US. They aims to test the hypothesis whether there is a statistically significant decrease in discharge rate and which states does this have the impact on.

Example 3: Monitoring energy use: The team aims to monitor and analyze the energy usage for an industrial pump at a Pulp and Paper plant. By monitoring baseline energy usage, the team will determine whether the pump is within nameplate specifications and then decide if energy-saving component is needed.

4.

CLASS POLICIES

• Grading is purely based on the merit of your work. Request of credit or higher grade for

other reasons will NOT be considered.

• Assigned homework will be collected in class. Homework is due one week after it is

assigned. No late homework will be accepted.

• Cellphones are not allowed during exams.

• Exams can be taken on or before the scheduled exam dates with justifiable reasons.

• Exams will be closed book, closed notes. One 8 ½ x 11 formula sheet can be used. Be

sure to bring your calculator. There will be ABSOLUTELY NO SHARING among

students of books, formula sheets, or calculators.

• If you believe there was an error in the grading of an exam or homework, then you can

submit the entire exam to the TA requesting a regrade. This must be done within one

week from the date the exam was returned. The entire exam will be regraded, so that you

may gain, or lose, points by resubmitting.

• Students are responsible for all information conveyed during class and on Blackboard. It

is the student’s responsibility to make sure they are receiving their official USC email.

• Always bring your textbook to class! Also bring your calculator, notebook, pencils/pens,

eraser, and course syllabus.

5.

COURSE WEBSITE

The course will use Blackboard: blackboard.usc.edu. You can also use smartphone app Bb

MobileLearn to access Blackboard.

6.

SOFTWARE USAGE:

ISE 426 Statistical Quality Control –Fall 2014

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Instructor: Prof. Qiang Huang, Ph.D.

Software is required for control charting in homework and project (not in exams). You can use Excel templates provided in the class to do homework and project.

7.

ACADEMIC INTEGRITY

ISE adheres to the University's policies and procedures governing academic integrity as

described in SCampus. Students are expected to be aware of and to observe the academic

integrity standards described in SCampus. Plagiarism are NOT acceptable.

8.

ACCOMMODATION FOR DISABILITIES

Any student requesting academic accommodations based on a disability is required to register

with Disability Services and Programs (DSP) each semester. A letter of verification for approved

accommodations can be obtained from DSP. Please be sure the letter is delivered to the instructor

as early in the semester as possible. DSP is located in STU 301 and is open 8:30 am - 5:00 pm,

Monday through Friday. The phone number for DSP is (213)740-0776.

ISE 426 Statistical Quality Control –Fall 2014

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Instructor: Prof. Qiang Huang, Ph.D.

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Ise 426 Statistical Quality Control