Chapter 4. Full Factorial Design
- Factorial design versus one-factor-at-a-time
- 2k full factorial design
- Unreplicated experiments
- Normal plot and half normal plot
1
Two Experiment Strategies
One-factor-at-a-time
Factorial design
2
One-factor-at-a-
Chapter 6. Second Order Designs
- Check for curvature
- Central composite design (CCD)
- Steepest ascent/descent
- Canonical analysis
Check for curvature
Recall the Three Phases of Experimental Investigation
Phase Zero:
Screening
Experiment
Phase One:
Pr
Chapter 3. Data Analysis
- Natural variable versus coded variable
- How to estimate the unknown parameters
- ANalysis Of VAriance (ANOVA)
1
Recap
(1) model structure
We have studied:
(2) experimental principles
(3) assessment of measurement device
We will
Chapter 2. Principles of DOE, Pairwise
Comparison Design, Empirical Modeling,
Gauge R&R
- Introduction to design of experiments
- Principles of experimental design
- Pairwise comparison design
- What is a empirical modeling?
- Three types of model structu
Chapter 1. Introduction
- Quality and quality control methods
- Review of basic statistics
1
- What is quality?
- Why is quality improvement important?
- Quality control techniques
2
Quality Improvement
3
Quality and Variability
target value
74 mm
actual
SEEM 4062: Homework #4
(Due 14 Apr, 2015; No late submissions accepted)
Question 1. [6 pts]
Design a 8-run experiment to study the effect of the following four factors on the strength of alloyed
steel: %Chromium (0.1 or 1), %Nickel (2 or 5), %Molybdenum (
SEEM 4062 Quality Engineering II
Sem B 2014-15
Dr. Matthias Tan
1
About the Course
SEEM 4062 Quality Engineering II
Instructor: Dr. Matthias Tan
Email: [email protected], Room: P6610
TA: HAN Mei, WANG Mingliang
HAN Mei [[email protected]]
WANG Mingl
SEEM 4062: Homework #3
(Due 24 March, 2015)
Show all your calculation steps in your answers to the questions below.
Question 1. [10 pts]
The yield of a chemical process is thought to be related to the amount of a certain catalyst ( )and the
reaction tempe
SEEM 4062: Homework #1
(Due 10 Feb, 2015)
Question 1. [6 pts] Consider data from a pairwise comparison design: Why would the use of the twopopulation t-test for testing :
against :
give higher type II error compared to the use
0 against :
0? Explain your
SEEM 4062: Homework #2
(Due 3 Mar, 2015)
Question 1. [10 pts]
Experiment in Lab session 3 (Lab sheet 513). Attach your data sheet.
(1.1) Write down a model for the data.
(1.2) Calculate the repeatability of the caliper you used.
(1.3) Calculate the reprod
2016
Group member:
Yongru Wang 54571705
Huang yi 54637970
Huany Peng Lei 54472520
Leung Wai Shing 54347523
HanMengying 54654314
LIU Peilu 54737316
Julianna Kar Yan 54525621
Background
01
About the company
Go pro, Inc., a technology company
founded by Nic
Form 2B
City University of Hong Kong
Information on a Course
offered by Department of SEEM
with effect from Semester A in 2014/2015
Part I
Course Title: Technological Innovation and Entrepreneurship
Course Code: SEEM6012
Course Duration: One Semester
No.
Quality Engineering I
Tutorial 2
Basic seven tools
Control Charts for Variables
Problem 2.1
Each observation in the following set of data represent the
weight of 15 candy bars in grams recorded on a candy
production line. The lower and upper specification
SPC
Calculations for Control Limits
UCL-Upper Control Limit
LCL-Lower Control Limit
CL -Center Line
-Sample Size
n
7 -Average of Measurements
=x -Average of Averages
R -Range
R -Average of Ranges
PCR-ProcessCapabilityRatio
Deviation
6 -p1sses5 Standard
No
Quality Engineering I
Tutorial 3
Control Charts for Attributes
Tutorial 3.1
Determine the trial central line and control
limits for a p chart using the following data,
which are for the payment of dental insurance
claims. Plot the values on graph paper an
Quality Engineering I
Tutorial 3
Acceptance sampling
Review
Tutorial 3.1.
A type of items produces are checked at an
inspection station with n=90 and c=3
sampling plan
If AQL=0.03, what is the value of the
producers risk ?
If LTPD=0.08, what is the value
Tutorial 5
Intro to Design of Experiment
Question 5.1
Given the following data, test whether there is significant difference
between treatment M1-M5.
M1(y1i)
M2(y2i) M3(y3i) M4(y4i)
M5(y5i)
1.02
1.06
0.99
0.99
1.05
0.99
1.02
1
0.94
1.02
0.99
1.05
0.94
0.9
Quality Engineering I
Tutorial 3
Acceptance sampling
Tutorial 3.1.
A type of items produces are checked at an
inspection station with n=90 and c=3
sampling plan
If AQL=0.03, what is the value of the
producers risk ?
If LTPD=0.08, what is the value of the
Quality Engineering I
Tutorial 1
Basic Statistics
Tutorial 1.1
Diameters of bolts are normally distributed
withP 2.02 in. and V 0.02 in. If the specifications
for the diameter are at 2.0 r0.06 in., find:
a.
The proportion of diameters below the lower spec
5.
Control Charts for Variables
Although control chart is sometimes considered as one of the basic quality control
techniques, it is undoubtedly the most important statistical technique in quality
engineering and it has attracted attention from quality pr
7.
Process Capability Analysis
In practice, we want to know whether the products meet the engineering requirement. A
question that is commonly asked is that whether the distribution of individual
measurements will fit between the specification limits. We
SEEM3062 Quality Engineering I
Introduction To
Design of Experiments
Design and Analysis of
Experiments
Introduction
Statistical comparisons (Z, t test)
Analysis of variance (ANOVA)
Factorial design
Taguchi methods
Experimental Design
A designed experimen
3.
Basic Seven QC Tools
In this part, we introduce the basic seven tools, or the Ichikawa seven tools as they are
first summarized in the book by the late Japanese Professor Ichikawa. These techniques
are applicable to most engineering processes and serve
Quality Engineering I (SEEM3062)
[email protected]
Basics of Quality Engineering
Jan 2015
Prepared by
Professor Xie Min
Dept of Systems Engineering and Engineering Management
City University of Hong Kong
E-mail: [email protected]
1
2
Quality Engineering
SEEM3062 Quality Engineering I
Introduction to
Acceptance Sampling
Acceptance Sampling
Lot of size N
(M defective items)
A product lot is received from supplier, we need to
decide whether to reject or accept this lot
Three methods for lot sentencing
Acce
SEEM3062 Quality Engineering I
Introduction to
Process Capability Analysis
Process Capability Analysis
A process can be in statistical control, but at the same
time, it may perform far from the requirements
Specification limits and tolerance exist for mos
Control Charts
for Attributes
Types of chart, uses and interpretations
(with an introduction to discrete distributions)
Control Charts for Attributes
Count data and go-no-go data
# defects in a unit
# defective items in a sample
Easier to collect
Differ
Introduction to Control Charts
For variables and attributes
The Concept of Variation
Variation always exists
They are not avoidable
Some causes serious quality problem
Types of variation
Within-piece variation;
Piece-to-piece variation;
Time-to-time va