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Statistics 361
Quality Improvement
for Industry
Spring 2003
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Scott D
Grimshaw
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Associate
Professor, Statistics Department
210
TMCB
801-422-6251
grimshaw@byu.edu
Office
Hours: MWF 1-1:50 pm or by appt.
Course
Lectures: MWF 10-10:50, 11-11:50 am
in 254 TMCB
Lab:
TTh 9,10,12 (depending on section) in 244 TMCB
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Announcements
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Final
Exam 11:00-12:50 June 18
Exam
2 Grading Details Below
Term
Paper Due Friday 13 June
Open
Lab MWF 8-10, 12-2
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Objectives
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Course
Description:
Statistics
361 will introduce topics in applied statistics that are useful in
engineering and quality improvement. The course begins with a brief
discussion of modern quality management philosophies and TQM (Total Quality
Management) followed by an introduction to statistical methods that will be
useful to engineers for implementing these quality philosophies. The course
will cover an introduction to probability theory, basic descriptive
statistics and statistical inference that provide provide background. Next,
the methods of characterizing and improving processes through the design
and analysis of experiments are discussed. Finally methods of monitoring
industrial processes through the application of statistical process control
(SPC) for reducing variation will be presented.
Prerequisite:
MATH
112 or 119
Course
Goals:
The
purpose of Stat 361 is to teach Engineers the modern quality philosophy
that has revolutionized the job of product design and manufacturing and
drastically improved the quality of manufactured products over the past 55
years. Along with teaching the philosophy of quality we also present two
practical and usable tools the engineer can use to implement this
philosophy.
- The first tool taught to
students in Stat 361 is the Deming PLAN-DO-CHECK-ACT cycle for solving
system problems and eliminating common causes for variation which
represent 95% of the problems in industry. What data should be
collected, and how is it to be analyzed and interpreted to aid in
decision making concerning industrial process improvements? A key tool
here are statistical experimental designs. Students are taught
specifically how to set up two-level factorial experiments, analyze
the data and interpret the data and communicate the results in
writing. This is done the hands on experiments, and writing
assignments.
- The second tool is the
Shewhart Control Charts that is based on the normal distribution. It
can be used by hourly workers in manufacturing along with engineers
and managers to recognize the difference between assignable causes for
product variation (responsibility of the local operator) and common
causes responsibility of management. In addition to learning to read
signals from the chart students are taught how to recognize specific
types of assignable causes. Students will learn to appreciate the role
of variation in data, and learn to make educated decisions in the face
of uncertainty caused by such variation.
- In order to understand
Shewhart control charts and the analysis and graphical presentation
and interpretation of data from designed experiments, students are be
introduced to background material in descriptive statistics,
probability theory and statistical inference.
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Course
Materials
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Textbook:
Modern Statistics for Engineering and
Quality Improvement, by Lawson
and Erjavec, Duxbury Press 2001.
Chapter 1:
Pareto Charts
Chapter 2:
Shewhart
Deming
Six Sigma
Baldrige
Award
Example
of Control Charts
Example of
Experimental Design
Chapter
6:
OC Curves
Chapter 7
Chapter 8
Chapter 9
Chapter
10:
Regression
Diagnostics
Chapter
16:
Variance
Component Estimation
Chapter
17:
Process Capability
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Grading
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15%
Homework
5% Quizzes
25%
Midterm Exam 1 (Grading
Details)
25%
Midterm Exam 2 (Grading
Details)
10%
Term Paper
20% Final Exam
(11:00-12:50 June 18)
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Tentative
Lecture Schedule, Reading and Homework Assignments
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Date
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Topic
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Book Sections
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Homework Assignment
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30
April
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Scientific Method and QC
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Chapt. 1 & 2.1-2.3
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1.1, 1.3, 1.4, 1.6, 2.2, 2.4 ,2.8
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2
May
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Demings' 14 Points
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2.4-2.6
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2.6
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5
May
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Probability & R.V.'s
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3.1-3.4
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3.1, 3.2, 3.3, 3.5, 3.6, 3.7
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7
May
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Expected Values
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3.5-3.8
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3.8, 3.9, 3.15
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9
May
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Data Analysis
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4.1-4.5
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4.1, 4.2 a-c, 4.3
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12
May
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Statistical Inference
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6.1-6.4
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6.1 a,c, 6.6
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14
May
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Enum & Analytic
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6.4-6.5
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6.2, 6.3, 6.5
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16
May
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Review
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19
May
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Exam 1
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21
May
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Experimental Strategies
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Chapter 7
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7.1, 7.2, 7.4
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23
May
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2-Level Factorials
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8.1-8.8
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8.1 a-b, 8.2
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26
May
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Holiday
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28
May
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Unreplicated 2k
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8.9, Chapt 5, 8.10, 8.11, 8.13
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5.3, 8.7
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30
May
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Additional Tools
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9.1-9.3
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9.1, 9.2
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2
June
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Linear Regression, Additivity of Variance
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10.1-10.3, 16.1
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10.1, 16.1
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4
June
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Review
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6
June
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Exam 2
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9
June
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Var Comp, Theory CC
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16.2, 17.1-17.3
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16.7 b, 17.2 a-b
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11
June
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Variable Control Charts
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17.4-17.5.3
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17.2 c-d, 17.3 a, 17.5
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13
June
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Attribute CC
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17.5.4-17.6.4
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17.7, 17.8, 17.9
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16
June
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Capability & Review
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17.7, 17.8
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17.3, 17.11
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The homework
assignments listed on the schedule below will be due at 5:00 PM the class
period following the date of the assignment. For example the assignment
listed for Wednesday 30 April will be due Friday 2 May by 5:00PM. Homework
is turned in by dropping it in the mail slot outside room 244. Assignments will be checked off and
returned in the following Lab period. To receive credit, you must include
your name and lab section number on your assignment. Detailed homework
solutions will be posted on the web. Late homework assignments will receive
half credit.
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Homework
Solutions
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Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter
6 (1) (2,3,5,6)
Chapter 7
Chapter 8
Chapter 9
Chapter
16 (1)
(7b)
Chapter 17
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Tentative
Lab Schedule
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Week
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Lab Activity
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29 April
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Helicopters
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1 May
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Bead Manufacturing
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6 May
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Excel Probability Calculations I
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8 May
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Excel Probability Calculations II
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13 May
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Paper Clip Data Collection
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15 May
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Excel Descriptive Statistics
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20 May
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Catapult Data Collection
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22 May
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Catapult Analysis I
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27 May
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Catapult Analysis II
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29 May
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Help On Term Paper Reports
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3 June
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Regression on Excel
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5 June
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Measure Parts
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10 June
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Control Charts on Excel
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12 June
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Review Exams
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Lab
Handouts
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Excel
Probability Calculations:
Binomial
Poisson
Exponential
Normal
Paper Clip
Data Collection
Excel
Descriptive Statistics
Catapult
Data Collection, Analysis, and Report
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Term
Paper
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Term
Paper will consist of memo style report of one set of data collected from a
23 experiment performed in the lab. Detailed descriptions of the
required format are provided in the Catapult Lab Handout above.
Term
Paper is Due Friday 13 June.
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Data
Sets
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Table 17.2
Chemical Assay Data
Table 17.4
Thrust Washer Thickness Data
Table 17.5
pH of Chemical Solution Data
Table
17.11 Circuit Board Assembly Errors
Table
17.12 Radiator Leaks
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Class
Examples and Code
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Other
Stuff
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Preventing
Sexual Harassment
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Title
IX of the Education Amendments of 1972 prohibits sex discrimination against
any participant in an educational program or activity that receives federal
funds. The act is intended to eliminate sex discrimination in education.
Title IX covers discrimination in programs, admission, activities, and
student-to-student sexual harassment. BYU’s policy against sexual
harassment extends not only to employees of the university but to students.
If you encounter unlawful sexual harassment or gender based discrimination,
please talk to your professor; contact the campus EEO office at 422-5895;
or contact the Honor Code Office (422-2847).
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In Case
of Emergency
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Please
follow instructor’s instructions:
- If there is an evacuation
alarm exit the classroom in an orderly fashion and exit the Talmage
Building and gather in the
west parking lot.
- After all students have
evacuated the building you should then report to your BYU ward
assembly area. (If you do not know where this is, contact your
Bishop.)
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Students
with Disabilities
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Please
let me know if you have any disability that could potentially affect your
success in the course. I am highly confident that arrangements or
modifications can be made. The BYU Services for Students with Disabilities
Office (422-2767) is available to coordinate such matters.
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Complaints
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I
have done my best to design a course that will accomplish course objectives
while recognizing the workload of a three credit hour class. If you have
any concerns regarding any aspect of this course (content, workload,
evaluation, etc), please come and discuss these matters with me. If we
cannot come to a mutually agreeable solution, I will direct you to my
superiors.
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