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Taguchi's Method

Submitted by
Chandrmouli Singh
MBA(AB) II Year
Flow of Presentation
 Introduction
 Principles contribution
 Categories of threat optimisation
 8 steps in Taguchi's methodology
 Taguchi's method and Indian Environment
 Taguchi's method and ISO 9000

12/12/13

IABM Bikaner

2
Introduction
 Taguchi Method is a new engineering design optimisation
methodology that improves the quality of existing products and
processes and simultaneously reduces their costs very rapidly, with
minimum engineering resources and development man-hours


The Taguchi Method achieves this by making the product or
process performance "insensitive" to variations in factors such as
materials, manufacturing equipment, workmanship and operating
conditions. Taguchi method makes the product or process robust and
therefore is also called as ROBUST DESIGN

12/12/13

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3
Priciple Contribution
Taguchi's principle contributions to statistics are
 Taguchi loss-function
 The philosophy of off-line quality control
 Innovations in the design of experiments

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Contd...
4
Taguchi loss-function
 Adopted R A Fishers's methodology to improve mean outcome of
process
 Excessive variation lay at the root of poor manufactured quality
 Invovled cost to society with cost of quality
 Industrial experiments seek to maximise an appropriate signal to
noise ratio representing the magnitude of the mean of a process as
compared to its variation

12/12/13

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Contd...
5
The philosophy of off-line quality control
The best opportunity to eliminate variation is during design of a
product and its manufacturing process
 System design
Design at the conceptual level involving creativity and innovation
 Parameter design
Nominal values of the various dimensions and design parameters
need to be set
 Tolerance design
Understanding of the effect that the various parameters have on
performance, resources can be focused on reducing and controlling
variation in the critical few dimensions
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Contd...
6
Innovations in the design of experiments
 Outer arrays
An orthogonal array that seeks deliberately to emulate the sources of
variation that a product would encounter in reality
An example of judgement sampling
Alternative approach is Chunk variable by Ellis R. Ott
 Management of interactions
 Analysis of experiments
Novel applications of the analysis of variance and minute analysis

12/12/13

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7
Categories of threat optimisation
Static Problems
A process to be optimized has several control factors which directly
decide the target or desired value of the output
The optimization then involves determining the best control factor
levels so that the output is at the the target value

P diagram

12/12/13

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Contd...
8
Batch Process Optimization
 Smaller the better
n = -10 Log10 [ mean of sum of squares of measured data]
when there is difference between measured and ideal value
n = -10 Log10 [ mean of sum of squares of {measured - ideal} ]
 Larger the better
n = -10 Log10 [mean of sum squares of reciprocal of measured data]

12/12/13

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Contd...
9
 Nominal the best
Square of mean
n = 10 Log10 ---------------------------Variance

12/12/13

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10
Dynamic Problem
If the product to be optimized has a signal input that directly decides
the output, the optimization involves determining the best control
factor levels so that the "input signal / output" ratio is closest to the
desired relationship

P diagram

12/12/13

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Contd...
11
Technological Development
 Sensitivity (Slope)
Case I: Larger the better
n = 10 Log10 [square of slope or beta of the I/O characteristics]
Case II: Smaller the better
n = -10 Log10 [square of slope or beta of the I/O characteristics]
 Linearity (Larger the better)
Square of slope or beta
n = 10 Log10 ------------------------------------Variance
12/12/13

IABM Bikaner

12
8 steps in Taguchi's method
Identify the main
function, side
effects, and
failure mode

Identify the noise
factors, testing
conditions, and
quality
characteristics

Identify the
objective function
to be optimized

Conduct the
matrix experiment

Select the
orthogonal array
matrix experiment

Identify the
control factors
and their levels

Analyze the data,
predict the
optimum levels
and performance

Perform the
verification
experiment and
plan the future
action

12/12/13

IABM Bikaner

13
Taguchi's method and Indian Environment
 The liberal economic policy of globalisation
 Large multinationals are purchasing hefty equity stakes in large
Indian companies
 Revamping and restructuring them to suit their own product ranges
 Producing world class quality products at globally competitive
prices
 Indian industry desperately requires Product Design to optimise the
existing products and processes
 The industry could reduce their costs drastically through product
(process) design optimisation

12/12/13

IABM Bikaner

14
Taguchi's method and ISO 9000
 The ISO-9000 aims at improving the capability of an organisation as
a whole to manufacture products to specified technical specification
and quality standards and to deliver them to the customer on time.
 Taguchi Method deals the product design itself, through product
and process design optimisation it improves product quality and
reduces costs drastically
 Taguchi Method and ISO-9000 thus complement each other.

12/12/13

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15
Thank you...

12/12/13

IABM Bikaner

16

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Taguchi method

  • 2. Flow of Presentation  Introduction  Principles contribution  Categories of threat optimisation  8 steps in Taguchi's methodology  Taguchi's method and Indian Environment  Taguchi's method and ISO 9000 12/12/13 IABM Bikaner 2
  • 3. Introduction  Taguchi Method is a new engineering design optimisation methodology that improves the quality of existing products and processes and simultaneously reduces their costs very rapidly, with minimum engineering resources and development man-hours  The Taguchi Method achieves this by making the product or process performance "insensitive" to variations in factors such as materials, manufacturing equipment, workmanship and operating conditions. Taguchi method makes the product or process robust and therefore is also called as ROBUST DESIGN 12/12/13 IABM Bikaner 3
  • 4. Priciple Contribution Taguchi's principle contributions to statistics are  Taguchi loss-function  The philosophy of off-line quality control  Innovations in the design of experiments 12/12/13 IABM Bikaner Contd... 4
  • 5. Taguchi loss-function  Adopted R A Fishers's methodology to improve mean outcome of process  Excessive variation lay at the root of poor manufactured quality  Invovled cost to society with cost of quality  Industrial experiments seek to maximise an appropriate signal to noise ratio representing the magnitude of the mean of a process as compared to its variation 12/12/13 IABM Bikaner Contd... 5
  • 6. The philosophy of off-line quality control The best opportunity to eliminate variation is during design of a product and its manufacturing process  System design Design at the conceptual level involving creativity and innovation  Parameter design Nominal values of the various dimensions and design parameters need to be set  Tolerance design Understanding of the effect that the various parameters have on performance, resources can be focused on reducing and controlling variation in the critical few dimensions 12/12/13 IABM Bikaner Contd... 6
  • 7. Innovations in the design of experiments  Outer arrays An orthogonal array that seeks deliberately to emulate the sources of variation that a product would encounter in reality An example of judgement sampling Alternative approach is Chunk variable by Ellis R. Ott  Management of interactions  Analysis of experiments Novel applications of the analysis of variance and minute analysis 12/12/13 IABM Bikaner 7
  • 8. Categories of threat optimisation Static Problems A process to be optimized has several control factors which directly decide the target or desired value of the output The optimization then involves determining the best control factor levels so that the output is at the the target value P diagram 12/12/13 IABM Bikaner Contd... 8
  • 9. Batch Process Optimization  Smaller the better n = -10 Log10 [ mean of sum of squares of measured data] when there is difference between measured and ideal value n = -10 Log10 [ mean of sum of squares of {measured - ideal} ]  Larger the better n = -10 Log10 [mean of sum squares of reciprocal of measured data] 12/12/13 IABM Bikaner Contd... 9
  • 10.  Nominal the best Square of mean n = 10 Log10 ---------------------------Variance 12/12/13 IABM Bikaner 10
  • 11. Dynamic Problem If the product to be optimized has a signal input that directly decides the output, the optimization involves determining the best control factor levels so that the "input signal / output" ratio is closest to the desired relationship P diagram 12/12/13 IABM Bikaner Contd... 11
  • 12. Technological Development  Sensitivity (Slope) Case I: Larger the better n = 10 Log10 [square of slope or beta of the I/O characteristics] Case II: Smaller the better n = -10 Log10 [square of slope or beta of the I/O characteristics]  Linearity (Larger the better) Square of slope or beta n = 10 Log10 ------------------------------------Variance 12/12/13 IABM Bikaner 12
  • 13. 8 steps in Taguchi's method Identify the main function, side effects, and failure mode Identify the noise factors, testing conditions, and quality characteristics Identify the objective function to be optimized Conduct the matrix experiment Select the orthogonal array matrix experiment Identify the control factors and their levels Analyze the data, predict the optimum levels and performance Perform the verification experiment and plan the future action 12/12/13 IABM Bikaner 13
  • 14. Taguchi's method and Indian Environment  The liberal economic policy of globalisation  Large multinationals are purchasing hefty equity stakes in large Indian companies  Revamping and restructuring them to suit their own product ranges  Producing world class quality products at globally competitive prices  Indian industry desperately requires Product Design to optimise the existing products and processes  The industry could reduce their costs drastically through product (process) design optimisation 12/12/13 IABM Bikaner 14
  • 15. Taguchi's method and ISO 9000  The ISO-9000 aims at improving the capability of an organisation as a whole to manufacture products to specified technical specification and quality standards and to deliver them to the customer on time.  Taguchi Method deals the product design itself, through product and process design optimisation it improves product quality and reduces costs drastically  Taguchi Method and ISO-9000 thus complement each other. 12/12/13 IABM Bikaner 15