Taguchi method

1. Signal to Noise Ratio
and Quality
Characteristics
Submitted By
Amit Sharma(2356103)
Narinder Pal (2356104)
Submitted to –: Prof. Jagtar Singh
Session- 2023-25

3. Introduction
Taguchi method :-
1) A new engineering design optimization methodology that improves the quality of existing products and
processes
2) A basis for determining the functional relationship between controllable product or service design
factors and the outcomes of a process.

4. Signal-noise ratio
 The signal is what you are measuring ie. the result of the presence of your
analysis.
 Signal is desirable value and noise is undesirable value.
 Noise is a extraneous information that can interfere with or alter the signal
 Noise may be thermal ,environmental ,chemical and instrumental.
 Noise cannot be completely eliminated but hopefully reduced.
 Noise are the factors which cause variability in performance of a system or
process, but cannot be controlled during production or product use.
 However you can control or simulate noise factors during experimentation.

5. Signal to Noise ratio
 Control factors (signals) are those design and process parameters that can be controlled.
 Noise factors cannot be controlled during production of product; controlled during experiment
 to get the desired result (higher S/N ratio) identify optimal control factors that not only increase the
Quality but also reduce Noise
 Product with this goal (higher S/N ratio) will deliver
more consistent performance even in extreme conditions

6. Categories of threat
optimization
Taguchi Method treats optimization problems in two categories:
 Static problem
• Dynamic problem

7. Static problem (batch process optimized-:
There are 3 Signal-to-Noise ratios of common interest for optimization of Static problems;
 Smaller – the – best : n = -10log10 [mean of sum of squares of measured data]
This is usually the chosen S/N ratio for all undesirable characteristics like " defects " etc. for which the
ideal value is zero.
 Larger- the – better: n = -10log10 [ mean of sum squares of reciprocal of measured data]
This case has been converted to SMALLER-THE-BETTER by taking the reciprocals of measured data
 Nominal- the- best: n =10 log10 Square of mean/variance
This case arises when a specified value is MOST desired, meaning that neither a smaller nor a larger value
is desirable
e.g. most parts in mechanical fittings have dimensions which are nominal-the-best type

8. Types of S/N ratios(contd.)
 Lower the better:-the desired value (the target) is zero. these problems are
characterized by the absence of scaling factor(eg. surface roughness
,pollution, tyre wear , etc.).
 The S/N ratio is given by-::
 Where n is the no. of replication.

9. Types of S/N ratio (contd.)
 Larger the better:-the ideal target value of this type quality characteristic is
(as large as possible)quality characteristic like strength values, fuel efficiency
etc. are the example of this type. The S/N ratio is given by-:

10. Types of S/N ratios (contd.)-:
 Nominal the best-:in these problems, the quality characteristic is continuous and non
negative. its target value is non zero and finite .we can adjust factor to move mean to
target in these type of problems.

11. S/N RATIOS FOR DYNAMIC
PROBLEMS
Types of Dynamic Problems:
 Continuous - Continuous type ( C - C )
 Continuous - Digital type ( C - D )
 Digital - Continuous type ( D - C )
 Digital - Digital type ( D - D )

12. Continuous to continuous type (c-c)
 Both signal factor and quality characteristics take
positive or negative values.
 When signal m = 0, Quality
characteristic = 0,
 Ideal function y = m
 Scaling factor exists to adjust slope (proportionality constant)
between y and m.

13. Continuous – digital type
(c-d)
 temperature controller
 input temperature setting - continuous
 output of heating unit - ' on ' or ' off
 divide into two separate problems
one for ' on ' function other
for ' off ' function
 each one continuous - continuous type or nominal
- the - best type problem

14. Digital to continuous type(d-c)
 digital to analog converter
 conversion to ' 0 ' and ' 1 ‘
 divide into two separate problems one for '
0 ' function
other for ' 1 ' function
 each one continuous - continuous type or nominal
- the - best type problem

15. How do we make S/N better-:
 It may be practical to reduce the variation in the system.
 Have defined procedures to reduce imprecision.
 Reduce influences as much as possible.
 Reduce measurement error.
 Make factor level as precise as much as possible.

16. Quality Characteristics
 The quality characteristic is the response that is measured at each
combination of control factors & noise factors.
 The S/N ratio acts as a summary statistic for the effects of the noise factors
on the quality characteristic.
 It is calculated from the sample values (data) obtained at compounded noise
factor combinations.
 In parameter design, the most important job of the engineer is to select an
effective characteristic to measure as data.

17. Choosing the Quality Characteristic
 The suitable Quality
Characteristics are:
 Force
 Acceleration
 Distance
 Pressure
 Velocity
 Time
 The indirect Characteristics which
may be avoided are:
 Yield
 Number of defects
 Faults
 Reliability
 Voids
 Appearance
 Pass/fail

18. Guidelines for the selection of Quality
Characteristic
 Identify the ideal function for the product/process.
 Characteristics should be energy related.
 Select characteristics that are continuous variables & are measurable through
instrumentation/transducers.
 Characteristics should have an absolute zero.
 Select characteristics that relate to additive effects of the control factors
(non-interactive, also referred to as monotonic).
 Select characteristics that are complete (cover all dimensions of the ideal
function) →A complete response provides all the information required to
describe the ideal function.
 Characteristics should be fundamental (basic to functionality)

19. Key Quality Characteristics
 In the Taguchi Method, there are several key quality characteristics, often referred to
as "Loss Functions," that play a central role in the optimization process. These
quality characteristics are as follows:
1. Signal-to-Noise Ratio (SNR): SNR is a critical quality characteristic in the Taguchi
Method. It's used to measure the variation in the output relative to the desired target
or nominal value and the noise or variation in the output. The goal is to maximize
the SNR because a higher SNR indicates better quality and less sensitivity to
variations.
2. Smaller-the-Better (Minimize) Quality Characteristic: This quality characteristic
represents situations where you want to minimize the response variable. Examples
might include reducing defects, minimizing weight, or minimizing processing time.
3. Larger-the-Better (Maximize) Quality Characteristic: In cases where you want to
maximize the response variable for better quality, you use the "Larger-the-Better"
characteristic. For instance, in applications like yield in manufacturing, higher values
are desirable.

20. Key Quality Characteristics (cont..)
4. Nominal-the-Best Quality Characteristic: This quality characteristic is used when you
want to achieve a response variable that is as close as possible to a target value.
It's often used when the quality criterion is centered around a nominal or target
value.
5. Smaller-the-Worse Quality Characteristic: In some situations, a lower value of a
response variable indicates better quality, but you also want to avoid extreme values
in the undesirable direction. This characteristic is used for situations where a low
value is still better than an extremely low value.
6. Larger-the-Worse Quality Characteristic: Similar to the "Smaller-the-Worse"
characteristic, this is used when a higher value of the response variable is
undesirable, but you want to avoid extremely high values.
 In the Taguchi Method, the goal is to optimize the selected quality characteristics by
adjusting the controllable factors or inputs, often referred to as control parameters or
factors, to minimize the impact of noise and achieve robustness. Experiments,
called Taguchi experiments or design of experiments (DOE), are designed and
conducted to determine the settings of the control parameters that will yield the best
performance in terms of the chosen quality characteristics.

21. Conclusion-
1) S/N ratio is also one more contribution of Taguchi.
2) Thermal noise can only be eliminated if temperature is absolute zero.
3) Environmental noise can be eliminated by certain methods as explained.
4) Nominal method is best suited when a specific value is most desired.
5) Smaller the better is used for undesirable values such as defects, automobile
emission , corrosion etc.
6) Larger is better used when largest value is desired such as weld strength ,
gasoline mileage.
7) Taguchi strongly recommended this approach for multiple runs.
8) Selection of the Quality Characteristic is critical step in Taguchi’s Method for
optimisation and shall be conducted carefully to make the research
successful.