Taguchi's method is an engineering design optimization approach that enhances product quality while reducing costs and engineering resources by making performance insensitive to variations. It emphasizes concepts like the Taguchi loss function and the philosophy of off-line quality control to minimize variation during the design phase. The method's applications extend to the Indian industry, aligning with ISO 9000 standards to foster competitive quality manufacturing.

1. Taguchi's Method
Submitted by
Chandrmouli Singh
MBA(AB) II Year

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
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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
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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
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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
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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
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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
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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
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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]
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10.  Nominal the best
Square of mean
n = 10 Log10 ---------------------------Variance
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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
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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
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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
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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
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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.
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16. Thank you...
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