Lecture X. History of Six Sigma. Introduction to Six Sigma
Introduction to Six Sigma
History of Six Sigma
CEO of Motorola in early 1980’s posed the challenge to achieve a tenfold reduction in product failure...
6σ Process Spread Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
5
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
6
1
Conceptual Formulation of 6-sigma
Conceptual Formulation of 6-sigma
Process capability (non-centered process)
Process capability (non-centered process)
Specification Spread Cp = 1.0 Cpk < 1.0 LSL
USL
6σ Process Spread Quality Engineering & Management
Dr. Steve Johnson
7
University of Arkansas
Conceptual Formulation of 6-sigma
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
8
Conceptual Formulation of 6-sigma
Process capability (6 sigma) Specification Spread
(±
Specification Limit
6 σ)
LSL
USL
6σ
±1σ ±2σ ±3σ ±4σ ±5σ ±6σ
Percent Conformance
Nonconformance Rate (ppm)
Process Capability (C,)
68.7
317300
0.33
95.45
485500
0.67 1.00
99.73
2700
99.9937
63
1.33
99.999943
0.57
1.67
99.9999998
0.002
2.00
Assumes normal distribution in tails – “unlikely”
Process Spread Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
9
Conceptual Formulation of 6-sigma
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
10
Conceptual Formulation of 6-sigma
Process capability
Definition of “defect” in six-sigma is very broad “any product, service or process variation which prevents meeting the needs of the customer and/or which adds cost, whether or not it is detected.”
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
11
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
12
2
DMAIC Model
DMAIC Model
D - Define
M - Measure
benchmark voice of the customer voice of the business quality function deployment process flow mapping Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
basic statistics cause/effect matrix process capability failure mode/effects analysis 13
DMAIC Model
Quality Engineering & Management
Dr. Steve Johnson
I - Improve
cause-effect diagrams
design of experiments
failure mode/effects analysis statistical inference control charts capability analysis
modeling tolerancing robust design
Dr. Steve Johnson
University of Arkansas
15
DMAIC Model
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
16
Phases of six-sigma
1st Phase – Management Commitment
C - Control control charts
training on principles and tools to senior management
intensive communications with customers, suppliers and employees
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
19
Phases of six-sigma
Dr. Steve Johnson
University of Arkansas
20
Phases of six-sigma
4th Phase – DMS
5th Phase – Business Improvement
developing monitoring systems
Quality Engineering & Management
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
the current key processes are mapped and problems identifies
21
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
22
23
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
24
Phases of six-sigma
6th Phase – Conducting 6-sigma Projects improve the processes and validate them by simulations and statistical methods determine proper documentation systems
Quality Engineering & Management
Dr. Steve Johnson
University of Arkansas
4
Design for Six-Sigma
Limitations to 6-sigma
“Mind limitations”
Quality function deployment - QFD matrix
fear time pressure resistance to change lack of trust poor communication
