QUALITY ENGINEERING

1
QUALITY ENGINEERING
Quality engineering robust design In the
West. - separate from development, design and
manufacturing - responsibility of staff
engineers who are not on product development
team - tasks include statistical analysis of
data maintaining servers In Japan. -
responsibility of all engineers and management
2
Chapter Objectives

• Basically understand what Quality means
• Gain a sense of the importance of quality in
  business and manufacturing
• Understand that quality can be measured,
  controlled, and improved

3
Dimensions of Quality

• Aesthetics
• Features
• Perceived Quality
• Conformance to standards

• Performance
• Reliability
• Durability
• Serviceability

• Definitions of Quality
• Quality means fitness for use
• - quality of design
• - quality of conformance
• Quality is inversely proportional to
  variability.

4
Dimensions of Quality

• Quality Improvement
• Quality improvement is the reduction of
  variability in processes and products.
• Alternatively, quality improvement is also
  seen as waste reduction.

5
Quality Engineering Terminology

• Quality Characteristics
• Physical - length, weight, voltage, viscosity
• Sensory - taste, appearance, color
• Time Orientation - reliability, durability,
  serviceability

Quality engineering is the set of operational,
managerial, and engineering activities that a
company uses to ensure that the quality
characteristics of a product are at the nominal
or required levels.
6

• Specifications
• Quality characteristics being measured are
  often compared to standards or specifications.
• Nominal or target value
• Upper Specification Limit (USL)
• Lower Specification Limit (LSL)

7
Quality Culture

• customer focus
• worker empowerment, and
• continuous improvement

8
Customer Focus
1. Dont expect all customers to be alike.
9
Customer Focus
1. Dont expect all customers to be alike. 2.
Most large companies realize that they can not
be all things to all people.
10
Customer Focus
1. Dont expect all customers to be alike. 2.
Most large companies realize that they can not
be all things to all people. 3. Respect, even
treasure internal customers.
11
Customer Focus
1. Dont expect all customers to be alike. 2.
Most large companies realize that they can not
be all things to all people. 3. Respect, even
treasure internal customers. 4. The customer
is always right!
12
Customer Focus
1. Dont expect all customers to be alike. 2.
Most large companies realize that they can not
be all things to all people. 3. Respect, even
treasure internal customers. 4. The customer
is always right! 5. Aspire always to be a
preferred supplier.
13
The Customer Supplier Interface
Who are your customers? What do they want? How do
they measure the quality of your products and
services?
14
Who is the customer?
Anyone who receives value in the form of a
product or service.
If you dont have customers - you are out of
business.
15
main man Dr. Genichi Taguchi

• An engineer who has developed an approach
  (Taguchi Methods) involving statistical planned
  experiments to reduce variation
• 1950s applied his approach in Japan
• 1980s introduced his ideas to US

16
What are Taguchis Contributions?

• Quality Engineering Philosophy
• Methodology
• Experiment Design
• Analysis

17
Taguchi focuses mostly on Off-Line Quality Control
Off-Line Quality Control Improving Quality and
Reducing Total Cost in the Design Stage
Total Cost means cost to society so it includes
the cost of problems in manufacturing and the
cost of problems in the field.
18
The Quadratic Loss Function and the Typically
Assumed Loss Function
19
The Design Process is Divided

• System Design
• Choose the sub-systems, mechanisms, form of the
  prototype.
• Parameter Design
• Optimize the design, set up the design so that
  it improves quality and reduces cost
• Tolerance Design
• Study the tradeoffs that must be made and
  determine what tolerances and grades of materials
  are necessary

20
Parameter Design (Robust Design)

• Optimize the settings of the design to minimize
  its sensitivity to noise ROBUSTNESS.
• Taguchi really opened a whole area that
  previously had been talked about only by a few
  very applied people.
• His methodology is heavily dependent on design of
  experiments, but he wanted to look at not just
  the mean but also the variance.

21
Classification of Factors

• Control FactorsDesign factors that are to be set
  at optimal levels to improve quality and reduce
  sensitivity to noise
• Dimensions of parts, type of material, etc
• Noise FactorsFactors that represent the noise
  that is expected in production or in use
• Dimensional variation
• Operating Temperature
• Adjustment Factor Affects the mean but not the
  variance of a response
• Deposition time in silicon wafer fabrication
• Signal Factors Set by the user to communicate
  desires of the user
• Position of the gas pedal

22
Analysis

• Taguchi uses signal to noise ratios as response
  variables.
• e.g.,
• It is often more informative to analyze mean and
  standard deviation separately (sd), rather than
  combine into a signal to noise ratio
• analyze sd in the same manner that we have
  previously analyzed the mean.
• Taguchi analysis techniques are often inefficient

23
We should support Taguchis philosophy of quality
engineering. However, we must rely on simpler,
more efficient methods that are easier to learn
and apply to carry this philosophy into
practiceYou can use the techniques presented
thus far in class to analyze Taguchi Designs.
24
Taguchis method Created quality engineering as
a disciplined engineering process to find best
expression of product design What is
best? Best lowest-cost solution based on
customer needs - to the product design
specification - include manufacturing,
life-cycle costs and losses to society
- Reduce the variation but more importantly make
the system insensitive to
variation Holistic approach to minimizing cost
and maximizing quality High quality products
minimize costs by performing consistently
25
High-quality system insensitive to
variation whilst maintaining target
values Signal-to-noise again! Costing of a
design equally important as actual design To
define system quality in terms of control of
insensitivity to variability Focal point
must be signal-to-noise ratios
26
Quality defined using performance
measures i.e. random variables Random variables
have a target value and scatter
signal noise Primary aim to
reduce noise whilst increasing the signal -
defined as robustness i.e. make the signal as
immune as possible to unforseen aspects of
system changes
27
NOISE Noise factor anything that causes a
characteristic to deviate from the target
value Examples high power transmission lines
on AM radio signal water in petrol wear on a
punch press die impurity on a hard disk
drive etc 3 types External noise sources of
variability outside the product Unit-to-unit
noise variability within a product Deteoration
noise ageing of a product when with customer
28
Nature of noise

• External factors
• Electromagnetic interference
• Temperature and humidity
• Input voltage variations
• Unit-to-Unit noise factors
• Resistance of electrical resistors
• Amount of lubricant used
• Dimensional variation due to machining
• Deterioration noise factors
• Total current passed through a car battery
• Wear of brake pads
• Weathering of paint on a house

29
Noise ? reliability problem ? failure of
product Early life failure normal design life
failure end of life failure Exponential?
Failure during Normal design Life should
be rare
30
Robustness - Sensitivity of the design to
noise - minimize variability maximize
robustness A product or process is said to be
robust when it is insensitive to the effects of
sources of variability, even though the sources
themselves have not been eliminated
31
Quality Many definitions! Must be defined by the
customer but also satisfy robust design
considerations 2 Major issues a products
features (S) a products conformance to
these features (N)
1 parameter, 2 designs Which is best?
Robust design mechanism for changing trend A to
trend B
32
Measurement of quality Taguchi loss of quality
? cost to society i.e. off-target The further
away from The target The more cost incurred -
Supplier and customer
33
Cost-based design Unit manufacturing cost
costs directly associated with production e.g.
material, labour etc. very backward and
retrogressive Life-cycle cost costs due to
operation of product e.g. consumables and
repair Quality loss cost e.g. less tangible
costs lost profit due to malfunction (customer
loss) return, recall, lawsuits (server
loss) pollution, injury, transportation
(society loss)
34
Different loss costs

• Losses to customer
• Time and effort to work around minor repairs
• Rental costs to replace a machine being repaired
• Nonwarranty service costs service contract
  costs
• Losses to manufacturer
• Inspection, scrap, and rework
• Warranty costs
• Lost sales and customers
• Lawsuits
• Losses to society
• Pollution and waste
• Injury, loss of life
• Disruption of communications and transportation

35
Robust design in product commercialization
Quality engineering offline or online
36
Offline quality engineering during
development and design
37
Online quality engineering taking place during
actual production Statistical process
control - identify random variation v.
assignable variation Static S/N optimization -
e.g. reduce noise whilst maintaining
signal define an optimal S/N ratio Loss-functio
n-based process control - Taguchi approach
equating variation to cost Most effective method
EXPERIMENTAL DESIGN!