Introduction To Quality Control JRH 2020

IET 302 Industrial Quality Control
Introduction to Quality Control
Dr. John Hubbard

Industrial Engineering Technology
University of Southern Mississippi (USM)
IET 302 Industrial Quality Control

Definitions of Quality
• Philip Crosby (1979) defined quality as “Conformance to

requirements, not as goodness or elegance.”
• Juran stated that quality is “meeting or exceeding
customer expectations.”
• Deming (1986) stated that a good quality product should
meet the present and future expectations of customers
IET 302 Industrial Quality Control 1

• Garvin (1984) highlighted that quality has eight dimensions:
Performance, Feature, Reliability, Conformance, Durability,
Serviceability, Aesthetic, Perceived quality.
Performance: Primary operating characteristics of a product
Example: The quality of the picture and sound are the main
performance of television.
Feature: Characteristics that supplement basic product
performances
Example: USB are supplemental to the basic operating
characteristics.

Reliability: Probability of a product success within a specific period of
time.
Example: With the probability of 98%, Honda Accord does not fail
within the first 5 years of use.
Conformance: Degree to which a product’s design & operating
characteristics meet pre-established standards.
Example: Samsung TV can precisely meet all the customer needs.
Durability: Measure of product life: Amount of time of use one
obtains from a product before it physically deteriorates.
Example: The length of time that a Samsung TV performs before a

replacement becomes necessary.

Serviceability: The promptness, courtesy, proficiency and ease in
repair when the product breaks down and is sent for repairs.
Example: Send repair requests easily online.
Aesthetics: The look, feel, sound, taste or smell of a product.
Example: the Samsung TV looks smart, clear picture and also
attractive.
Perceived quality: Relates to the customer’s subjective opinion of
the product’s or company’s reputation.
Example: iphone 6 plus perceived to me to be high quality cell
phone.

Cost of quality
The quality costs are the total of the cost incurred by a) investing in
the prevention of non-conformances to requirements;
b) appraising a product or service for conformance to
requirements; and c) failure to meet requirements.
Prevention costs: The costs of all activities specifically designed to

prevent poor quality in products or services. Examples are the
costs of new product review, quality planning, supplier capability
surveys, quality improvement team meetings, quality education
and training.

Cost of quality
Appraisal costs: The costs associated with measuring, evaluating or auditing
products or services to assure conformance to quality standards and performance
requirements. These include the costs of incoming and source inspection/test of
purchased material, in process and final inspection/test, product, process, or service
audits, calibration of measuring and test equipment.
Failure cost: The costs resulting from products or services not conforming to
requirements or customer/user needs. Failure costs are divided into internal and
external failure cost categories.
a.Internal failure costs: Failure costs occurring prior to delivery or shipment of the
product, or the furnishing of a service, to the customer. Examples are the costs of
scrap, rework, re-inspection, retesting.
b.External failure costs: Failure costs occurring after delivery or shipment of the
product, and during or after furnishing of a service, to the customer. Examples
are the costs of processing customer complaints, customer returns, warranty
claims.

Statistical Quality Control
• Statistical Quality Control (SQC) is the use of statistical methods

in the monitoring and maintaining of the quality of products and
services.
The objective of SQC is to minimize the variability of process.
Taguchi (Japanese Professor) stated that high variability in

production process of a product can leads to poor quality of
product. In a simple word, less variability results in higher quality.
Controllable variables
…
Input Output (response variable)
Uncontrollable variables

Source of variations
• Controllable and uncontrollable variables can cause to the variation of

production process
Controllable variables: those variables that we have control on their changes such
as raw materials, and skill of labors
Uncontrollable variables: those variables that we don’t have any control on them
such as machinery depreciation, environmental changes (temperature, humidity,
etc.)
• Why do we use Statistical Quality Control (SQC)?
1. To identify the controllable variables

2. To control variations origin from controllable variables.

Coil spring example
 Coil spring is an important element of suspension systems in vehicles.

 Coil springs are generally made of following manufacturing process:
1) Hot winding: Ticker wire or bar stock can be coiled into springs if the
metal is heated to make it flexible.
2) Hardening: To relieve the stress and allow the steel to maintain its
characteristic resilience
3) Grinding: is used to flat ends of spring
4) Shot peening: Is used to strengthens the steel to resist metal fatigue.
5) Coating: To prevent corrosion the entire surface of the spring is
protected by painting

Coil spring example
•Common failures during manufacturing process of coil spring
are:
 Raw material defect
 Surface imperfection
 Improper heat treatment
• Various testing devices are used to check completed springs for
compliance with specifications.
Geometrical characteristics of coil spring:
p: Coil’s pitch
: Coil’s outer diameter
L : Overall spring length
D: Mid diameter of the spring
Example: the allowable specification range of coil’s

Pitch (p) is 32 0.003 mm

Coil spring example
Controllable variables
…
Input Output (response variable)
Uncontrollable variables
Skilled operates, calibrated CNC machine

Operator …
Bar stock (raw Coil spring

material)
CNC machine
CNC machine depreciation

What is Six sigma ()
• A term used in statistics to represent standard deviation from mean value,

an indicator of the degree of variation in a set of a process.
• Six Sigma seeks to improve the quality of the output of a process by

identifying and removing the causes of defects and
minimizing variability in manufacturing and business process.
• Sigma measure how far a given process deviates from perfection. Higher
sigma capability, better performance.
• Six sigma is a measure of quality. If you achieved 6 sigma, then your

product’s quality is very good.
• Six sigma is a statistical concept that measures a process in terms of

defects – at six sigma level, there are 3.4 defects per 1 million
opportunities.

Six Sigma
Please watch this video !

Sigma levels
Sigma Level ( Process Defects per Million

Capability) Opportunities
2 308,537
3 66,807
4 6,210
5 233
6 3.4

What is DMAIC? (Define, Measure, Analyze, Improve, Control)
• DMIAC is a basic component of six sigma methodology- a way to

improve work processes by eliminating defects.
• A quality tool which focus on change management style.
Five Phases of Six Sigma are:

Define specific goals to achieve outcomes, consistent with customers
demand
Measure reduction of defects
Analyze problems, cause and effects must be considered
Improve the process by systematically reducing variation and eliminating
defects
Control process to minimize defects

Seven Tools of Statistical Process Control (SPC)
• Seven tools are graphical techniques that are helpful in troubleshooting

issues related to quality.
1) Check Sheet is used to easily collect data. Decision-making and actions

are taken from the data.

Pareto chart
2) Pareto chart is used to identify and quantify the source of problems. The
idea is that 80% of problems usually stem from 20% of the causes.
Example of paint defects from an automotive assembly plant:

Cause and Effect diagram
Cause-and-Effect Diagram (Fishbone Diagram) is used to figure out any

possible causes of a problem. After the major causes are known, we can
solve the problem accurately.

Cause and Effect diagram

Histogram
Histogram is simply a column chart which presents number of

occurrence of the characteristics most often in the range of numbers.

Scatter diagram
Scatter Diagram is a graphical tool that plots many data points and
shows a pattern of correlation between two variables.
A positive correlation between machinery depreciation and number of defects.
# of defective items
Age of machinery
Age of machinery

Scatter diagram
A negative correlation between time spent on training operators and

number of defects.
Time spent on training operators

Time spent on training
operators

Scatter diagram
No relationship between level of noises and number of defect

items- no correlation.
Noise level

Flow chart & Control charts
Flow Chart shows the process step by step and can sometimes

identify an unnecessary procedure.
Flow charts are used to identify an unnecessary procedure.
Control Chart provides control limits which are generally three

standard deviations above and below average, whether or not our
process is in control.

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IET 302 Industrial Quality Control

Introduction to Quality Control

Dr. John Hubbard

IET 302 Industrial Quality Control

• Philip Crosby (1979) defined quality as “Conformance to

IET 302 Industrial Quality Control 1

IET 302 Industrial Quality Control 2

Example: The length of time that a Samsung TV performs before a

IET 302 Industrial Quality Control 3

IET 302 Industrial Quality Control 4

Prevention costs: The costs of all activities specifically designed to

IET 302 Industrial Quality Control 5

IET 302 Industrial Quality Control 6

• Statistical Quality Control (SQC) is the use of statistical methods

Taguchi (Japanese Professor) stated that high variability in

Input Output (response variable)

IET 302 Industrial Quality Control 7

• Controllable and uncontrollable variables can cause to the variation of

• Why do we use Statistical Quality Control (SQC)?

1. To identify the controllable variables

IET 302 Industrial Quality Control 8

 Coil spring is an important element of suspension systems in vehicles.

IET 302 Industrial Quality Control 10

Geometrical characteristics of coil spring:

Example: the allowable specification range of coil’s

IET 302 Industrial Quality Control 11

Input Output (response variable)

Skilled operates, calibrated CNC machine

Bar stock (raw Coil spring

IET 302 Industrial Quality Control 12

• A term used in statistics to represent standard deviation from mean value,

• Six Sigma seeks to improve the quality of the output of a process by

• Six sigma is a measure of quality. If you achieved 6 sigma, then your

• Six sigma is a statistical concept that measures a process in terms of

IET 302 Industrial Quality Control 13

Please watch this video !

IET 302 Industrial Quality Control 14

Sigma Level ( Process Defects per Million

IET 302 Industrial Quality Control 15

• DMIAC is a basic component of six sigma methodology- a way to

Five Phases of Six Sigma are:

IET 302 Industrial Quality Control 16

• Seven tools are graphical techniques that are helpful in troubleshooting

1) Check Sheet is used to easily collect data. Decision-making and actions

IET 302 Industrial Quality Control 17

Example of paint defects from an automotive assembly plant:

IET 302 Industrial Quality Control 18

Cause-and-Effect Diagram (Fishbone Diagram) is used to figure out any

IET 302 Industrial Quality Control 19

IET 302 Industrial Quality Control 20

Histogram is simply a column chart which presents number of

IET 302 Industrial Quality Control 21

IET 302 Industrial Quality Control 22

A negative correlation between time spent on training operators and

Time spent on training operators

IET 302 Industrial Quality Control 23

No relationship between level of noises and number of defect

IET 302 Industrial Quality Control 24