Process parameter optimization for fly ash brick by Taguchi method

Saurabh Anand (PGDM)Institute for Future Education, Entrepreneurship and Leadership – iFEEL, Lonavala, 410405.

ABSTRACTThis report is on experimental investigation is carried out to optimize the mix proportions of the fly ash brick by Taguchi method of parameter design. The experiments have been designed using an orthogonal array with four factors and three levels each. Cement has been mixed as binding materials and water binder ratio has been considered as one of the control factors. The effects of water/binder ratio, fly ash, coarse sand, and stone dust on the performance characteristic are analysed using mean response data. According to result water/binder ratio of 0.4, fly ash of 39%, coarse sand of 24%, and stone dust of 30%. The mean value of optimal strength is predicted as 166.22 kg.cm–2.

1. Introduction

Profile of the assumed Company

Company which is assumed is in manufacturing of fly ash brick. Here it has the process for compressive strength of fly ash brick where there are no. of factors which are responsible for the manufacturing of fly ash brick and giving it durability/stability.

Literature Review

Taguchi is a statistical method developed by Genichi Taguchi which is useful to improve quality of manufactured goods.Taguchi is used to develop designs for studying variations in the process. It includes innovations and specific loss function.

Problem StatementTo find the combination for setting up the binding ratio and increasing the compressive strength of fly ash brick.

2. Design of Experiment

It is a systematic method to determine the relationship between factors which affects a strength as well as the durability of fly ash brick.Also we have calculated signal to noise ratio on the basis of ANOVA.In this paper we have used 6 step methodology for deploying robust Taguchi design in process optimization of brewing process using Minitab software

3. Methodology Selected for Solving Above Problem

Methodology for deploying robust Taguchi approach for process optimization (6 step methodology)

Identification of control factors and their levels that are to be optimized

Identification of the controllable and noise factors that are influencing the above identified performance characteristics and determination of levels and values for all identified controllable and noise factors

Developing Design of Experiment (DOE) with the help of Minitab software

Conducting the experiments as per design analysing the results produced as per designed experiment for the compressive strength of brick specimens and posting the values in Minitab worksheet

Prediction of the expected results for optimal settings with the help of Minitab

Validation of optimal setting by conformation of trails.

4. General Linear Model

Inner Array Outer Array

Serial No. Controllable Factors

LevelsCompressive

strength of brick (abv) (%)

1 2 3 R1 R21 A 0.40 0.42 0.45 2 B 35 37 39 3 C 20 22 24 4 D 28 30 32

Analysis Of Variance

Source DF Adj SS Adj MS F-Value P-ValueA 2 395.11 197.56 5.03 0.034B 2 61.44 30.72 0.78 0.486C 2 448.78 224.39 5.71 0.025D 2 6328.11 3164.06 80.56 0.000

Error 9 353.50 39.28

Total 17 7586.94

Here the ANOVA result shows that the p-value which can be seen is 0.000, 0.025 and 0.034 which is below the significance level and is considered as good factor to be taken into consideration which are Water/binder ratio, Fly ash % and Stone dust%.

5. Analysis, Results and Discussion

Testing Machine has been used to measure the compressive strength of brick specimens. Three readings are recorded for each experimental condition. Data from a designed experiment are used to analyse the mean objective/response function. In Taguchi technique, the variation of the response is also examined using an appropriately chosen S/N ratio. Broadly speaking, the S/N ratio is the ratio of the mean (signal) to the standard deviation (noise).

6. Implications

The above 6 step methodology which is used in this paper can be used for any manufacturing processes of the fly ash brick industry. The results are highly specific to this industry but the methodology is generic and can be used in the manufacturing process.

References

1. Chang PK, Hou WM. A study on the hydration properties of high performance slag concrete analysed by SRA. Cement and Concrete Research 2003; 33(2):183–189.

2. Chang PK, Peng YN, Hwang CL. A design consideration for durability of high performance concrete. Cement and Concrete Composites 2001; 23(4–5):375–380.

3. Smith LA. The design of fly ash concretes. In: Proceedings Institute of Civil Engineering; 1967. p. 770–789.

Appendix

Table 1 – Factor and Factor Levels

Inner Array Outer Array

Serial No. Controllable Factors

LevelsCompressive

strength of brick (abv) (%)

1 2 3 R1 R21 A 0.40 0.42 0.45 2 B 35 37 39 3 C 20 22 24 4 D 28 30 32

Controllable and Noise Factors and Factor Levels

Inner Array Outer Array (abv)

Serial No. A B C D Noise R1 R2

1 0.40 35 20 28 113 1172 0.42 37 22 30 113 1003 0.45 39 24 32 113 1104 0.40 35 20 28 123 1175 0.42 37 22 30 117 1336 0.45 39 24 32 133 1477 0.40 35 20 28 163 1638 0.42 37 22 30 143 1479 0.45 39 24 32 163 160

Optimal setting is arrived after considering main effect plots and delta values

0.450.420.40

160

150

140

130

120

110

393735 242220 323028

Water/binder ratio

Mea

n of

Mea

ns

Fly ash % coarse sand % Stone dust%

Main Effects Plot for MeansData Means

The graph shows at maximum measure where Water/binder ratio is to be taken at 0.45, Fly ash% at 39, Coarse Sand % at 20 and Stone dust% at 30.