**2. Taguchi approach**

Design of Experiments (DOE) is powerful statistical technique presented by R. A. Fisher in England during the 1920s to study the impact of numerous factors at the same time. In his initial applications, Fisher needed to discover how much rain, water, fertilizer, sunshine, etc. are expected to deliver the best yield. Since that time, much improvement of the system has occurred in the scholarly condition yet helped create numerous applications on the generation floor [3]. In late 1940s Dr. Genechi Taguchi of Electronic Control Laboratory in Japan, carried out significant research with DOE techniques. He spent extensive exertion to make this trial procedure easier to use and to improve the quality of manufactured products. Dr. Taguchi's standardized version of DOE, popularly known as the Taguchi method or Taguchi approach, was introduced in the USA in the early 1980s. Today it is one of best optimization techniques used by manufacturing industry. The DOE using the Taguchi approach can monetarily satisfy the needs of problem-solving and product/ process design in optimization projects. By learning and applying this procedure, specialists, researchers, and scientists can essentially decrease the time required for exploratory examinations [4].

#### **2.1 Orthogonal array**

The orthogonal array is selected as per standard orthogonal given in **Table 1**. This technique was first given by Sir R. A. Fisher, in the 1920s [5]. The method is popularly known as the factorial DOE. A full factorial design results may involve a large number of experiments. A full factorial experiment as shown in **Table 2**.

#### **2.2 Nomenclature array**

Orthogonal array is defined as: Lx (Ny) Where, L = Latin square x = number of rows N = number of levels y = number of columns (factors) Degrees of freedom associated with the OA = x – 1 Some of the standard orthogonal arrays are listed in **Table 3**.

• Level 1 and 2 in the matrix represent the low and high level of a factor respectively.

• Any pair of columns has only four combinations [1, 1], [1, 2], [2, 1], and [2, 2]

**Experiment no. A B C** 1 111 2 112 3 121 4 122 5 211 6 212 7 221 8 222

**Orthogonal array Number of rows Maximum no. of factor Maximum no. of columns at these**

*Application of Taguchi Method in Optimization of Pulsed TIG Welding Process Parameter*

*DOI: http://dx.doi.org/10.5772/intechopen.93974*

L4 4 3 3 ——— L8 8 7 7 ——— L9 9 4 — 4 — — L12 12 11 11 ——— L16 16 15 15 ——— L'16 16 5 — — 5 — L18 18 8 1 7 — — L25 25 6 ——— 6 L27 27 13 1 13 — — L32 32 31 31 ——— L'32 32 10 1 — 9 — L36 36 23 11 12 — — L'36 36 16 3 13 — — L50 50 12 1 — — 11 L54 54 26 1 25 — — L64 64 63 63 ——— L'64 64 21 — — 21 — L81 81 40 — 40 — —

**levels 2 345**

Taguchi method stresses the necessity of studying the response variable using the signal-to-noise ratio, resulting to decrease the effect of quality characteristic

indicating that the pair of columns are orthogonal.

**2.3 Signal to noise ratio**

*Full factorial experiments table.*

**Table 1.**

**Table 2.**

**167**

*Standard orthogonal.*

• Each column of the matrix has an equal number of 1 and 2.


*Application of Taguchi Method in Optimization of Pulsed TIG Welding Process Parameter DOI: http://dx.doi.org/10.5772/intechopen.93974*

#### **Table 1.** *Standard orthogonal.*

has occurred in the scholarly condition yet helped create numerous applications on the generation floor [3]. In late 1940s Dr. Genechi Taguchi of Electronic Control Laboratory in Japan, carried out significant research with DOE techniques. He spent extensive exertion to make this trial procedure easier to use and to improve the quality of manufactured products. Dr. Taguchi's standardized version of DOE, popularly known as the Taguchi method or Taguchi approach, was introduced in the USA in the early 1980s. Today it is one of best optimization techniques used by manufacturing industry. The DOE using the Taguchi approach can monetarily satisfy the needs of problem-solving and product/process design in optimization projects. By learning and applying this procedure, specialists, researchers, and scientists can essentially decrease the time required for exploratory examinations [4].

*Quality Control - Intelligent Manufacturing, Robust Design and Charts*

Design of Experiments (DOE) is powerful statistical technique presented by R. A. Fisher in England during the 1920s to study the impact of numerous factors at the same time. In his initial applications, Fisher needed to discover how much rain, water, fertilizer, sunshine, etc. are expected to deliver the best yield. Since that time, much improvement of the system has occurred in the scholarly condition yet helped create numerous applications on the generation floor [3]. In late 1940s Dr. Genechi Taguchi of Electronic Control Laboratory in Japan, carried out significant research with DOE techniques. He spent extensive exertion to make this trial procedure easier to use and to improve the quality of manufactured products. Dr. Taguchi's standardized version of DOE, popularly known as the Taguchi method or Taguchi approach, was introduced in the USA in the early 1980s. Today it is one of best optimization techniques used by manufacturing industry. The DOE using the Taguchi approach can monetarily satisfy the needs of problem-solving and product/ process design in optimization projects. By learning and applying this procedure, specialists, researchers, and scientists can essentially decrease the time required for

The orthogonal array is selected as per standard orthogonal given in **Table 1**. This technique was first given by Sir R. A. Fisher, in the 1920s [5]. The method is popularly known as the factorial DOE. A full factorial design results may involve a large number of experiments. A full factorial experiment as shown in **Table 2**.

**2. Taguchi approach**

exploratory examinations [4].

**2.1 Orthogonal array**

**2.2 Nomenclature array**

respectively.

**166**

Where, L = Latin square x = number of rows N = number of levels

Orthogonal array is defined as: Lx (Ny)

Degrees of freedom associated with the OA = x – 1

Some of the standard orthogonal arrays are listed in **Table 3**.

• Each column of the matrix has an equal number of 1 and 2.

• Level 1 and 2 in the matrix represent the low and high level of a factor

y = number of columns (factors)


#### **Table 2.** *Full factorial experiments table.*

• Any pair of columns has only four combinations [1, 1], [1, 2], [2, 1], and [2, 2] indicating that the pair of columns are orthogonal.
