pp 1–19 | Cite as

Statistical Modeling and Surface Texture Study of Polished Silicon Wafer Si (100) using Chemically Assisted Double Disk Magnetic Abrasive Finishing

  • Kheelraj Pandey
  • Utkarsh Pandey
  • Pulak M. Pandey
Original Paper


The present paper aims to analyze the surface finish of polished silicon wafer by chemically etching with potassium hydroxide (KOH) and mechanical polishing by Double Disk Magnetic Abrasive Finishing (DDMAF) process. The study is emphasized to study the effect of process parameters i.e. polishing speed, working gap, abrasive mesh number and percentage weight of KOH on the surface roughness (Ra). Response surface methodology (RSM) has been used to plan the experiments and Analysis of variance (ANOVA) has been used to analyze the impact of each process parameter on surface roughness. Regression equation for surface roughness in terms of significant process parameters has been developed to determine the surface roughness of polished silicon wafer. The equation has been further optimized using optimizer available with Minitab 17 and Genetic Algorithm (GA) tool box available with MatLab 16, to obtain the optimum process parameters and to prefigure the minimum surface roughness. The confirmatory experiment was carried out at optimum parameters and the prefigured results were found to be closely matched with the experimental findings. The communication further vocalizes the study of surface integrity for the unpolished sample to polished sample at optimum parameter using SEM and AFM images.


Chemical mechanical polishing (CMP) Double disk magnetic abrasive finishing (DDMAF) Response surface methodology (RSM) Flexible magnetic abrasive brush (FMAB) Surface roughness Optimization Response optimizer Genetic algorithm (GA) 



adjusted mean squares


adjusted sum of squares


degree of freedom


surface roughness of polished silicon wafer (nm)


sum of squares


t-distribution value


error variance


Polishing speed (rpm)


Working gap (mm)


Abrasive mesh number of Al2O3


Concentration of potassium hydroxide (KOH)


level of confidence interval


Coefficient of multiple determination


Precision of the surface roughness model (nm)


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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Mechanical Engineering DepartmentIndian Institute of Technology, DelhiNew DelhiIndia
  2. 2.Research Associate, Mechanical Engineering DepartmentIndian Institute of Technology, DelhiNew DelhiIndia

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