STA 4664, Section 82823
Statistical Quality Control
Fall, 2009
M W  1:30 - 2:45, Building 10, Room 1319

Course Title:  Statistical Quality Control

Prerequisite:  A course in statistics at the level of Introductory Business Statistics or permission of the instructor (based on equivalent work-experience-based knowledge) is required.  No previous knowledge of SAS is required.

TextIntroduction to Statistical Quality Control, 6th Edition, D. C. Montgomery.
Instructor:  Jim Gleaton

Office No:  14/2717

Phone No:  620-3727

E-mail:  jgleaton@unf.edu  Web page:  www.unf.edu/~jgleaton

Office hrs:  Monday, 10:00 - 12:00; Tuesday, 1:30 - 3:30; Wednesday, 10:00 - 12:00; Thursday, 1:30 - 3:30

Phone No., Department of Mathematics and Statistics:  620-2653

Attendance:  Not required, but I suspect that there is a strong positive correlation between days present and high grades.  DO NOT MISS AN EXAM (except under uncontrollable circumstances and then contact me prior to the exam time).

Homework:  Suggested problems will be posted on the web page.  I can discuss these periodically during class sessions.  I do not collect homework.  Some answers are in the back of the book.

Grading:  On a scale of 0 - 100 for all graded items.  Generally, A = 92 to 100; A- = 90 to 91.9; B+ = 88 to 89.9; B = 82 to 87.9; B- = 80 to 81;
C+ = 78 to 79.9; C = 72 to77.9; C- = 70 to 71.9; D = 60 to 69.9; F = below 60.

Missed Assignments and Lateness:  You must have an excellent excuse with written documentation for not taking the midterm or final on the assigned day or for a delay in submitting your project.

Testing:  There will be a midterm on Wednesday, Oct. 7 and a final exam on Dec. 7.  Each is worth 40% of your grade.  A write-up of a take-home project requiring topic selection, data collection and analysis (with some done via a QC computer package) and discussion will be worth 20% of your grade.  I will devote some class time to computer instruction. 

Tip for Succeeding in College:  For every hour you spend in the classroom, you should spend at least 2 hours outside of class (preferably the same day) studying the course material.

Details of the course:
Chapter 1.  Introduction (All sections):  The Meaning of Quality and Quality Improvement; Brief History of Quality Methodology; Statistical Methods for Quality Control and Improvement; Total Quality Management (quality philosophy, links between quality and productivity, quality costs, legal aspects of implementing quality improvement).

Chapter 3.  Modeling Process Quality (all sections):  Frequency distribution and histogram, numerical and graphical descriptive statistics, some important discrete and continuous probability models, some useful approximations.

Chapter4.  Inferences About Process Quality (all sections):  Sampling distributions, estimation and confidence interval for process parameter(s), hypothesis testingon process parameter(s), and power analysis.

Chapter 5.  Methods and Philosophy of Statistical Process Control.  Chance and assignable causes, Statistical basis of the control charts (basic principles, choices of control limits, sample size and sampling frequency, rational subgroups, analysis of pattern on control charts, warning limits, ARL, sensitizing rules for control charts); Deming's Magnificent Seven, Implementing SPC, an application of SPC, nonmanufacturing application of SPC.

Chapter 6.  Control Charts for Variables (all sections):  Control charts for X-bar and R (statistical basis, development and use, estimating process capability, interpretation, effect of non-normality on the chart, the OC function, average run length), Control charts for X-bar and S, control charts for individual measurements, applications of variables control charts.

Chapter 7.  Control Charts for Attributes (all sections):  Control chart for fraction nonconforming (OC curve of control chart, variable sample size, nonmanufacturing application, the OC function and ARL calculation), Control charts for nonconformities or defects, Choices between attribute and variable control charts, guideline for implementing control charts.

Chapter 8.  Process and Measurement System Capability Analysis (PCA) (sections 7.2, 7.3, 7.4, 7.8):  PCA analysis using a histogram or a probability plot, process-capability ratios, confidence interval for process-capability ratio, PCA using a control chart, estimating natural tolerance limits of a process.

Chapter 9.  Cumulative-Sum (CUSUM) & Exponentially Weighted Moving Average (EWMA) Control Charts (all sections):  CUSUM control chart (basic principles of the chart for monitoring the process mean, tabular or algorithmic CUSUM, recommendations for CUSUM design, the standardized CUSUM, rational subgroups, improving the responsiveness of the CUSUM for large shifts, designing a V-Mask, designing CUSUM based on ARL, one-sided CUSUM), EWMA control chart (EWMA control chart for monitoring process mean, design of an EWMA control chart, rational subgroups), the Moving Average control chart.

Chapter 15.  Lot-By-Lot Acceptance Sampling for Attributes (all sections):  The acceptance sampling problem, single sampling plan for attributes double, multiple, and sequential sampling, military standard 105E, the Dodge-Roming sampling plans (AOQL and LTPD plans).
Last day of classes: December 4 (Friday)

Final Exam: Monday, Dec. 7, 1:00 pm – 2:50 pm 

Important Dates: 

September 7 - Labor Day (no classes)
November 6 - Last day to withdraw

November 11 - Veterans Day

November 26 – 27 – Thanksgiving Holiday (no classes)