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An ANN-Based Method to Predict Surface Roughness in Turning Operations

  • Research Article - Mechanical Engineering
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Abstract

In recent years, there has been a growing interest for the prediction of machining characteristics (such as surface roughness and tool wear) during machining. Several machining parameters such as cutting speed and cutting depth are known to affect the surface characteristics. Various methods are used to investigate the relative contribution of these parameters on the surface characteristics. Therefore, selecting a set of parameters according to the relative contributions is important in the prediction of the surface characteristics effectively. In this paper, a new alternative parameter selection method based on artificial neural networks is suggested. Within this scope, forward and stepwise selection methods are proposed. A statistical hypothesis test is used as an elimination criterion. The suggested methods are used to predict the surface roughness in turning operations effectively. Successful results were obtained in the prediction of surface roughness by using these methods.

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Abbreviations

K :

Tool stiffness coefficient (N/m)

CD:

Cutting depth (mm)

OL:

Tool overhang length (mm)

S :

Tool damping ratio (%)

SRA:

Side rake angle (\(^{\circ }\))

ECA:

End cutting angle (\(^{\circ }\))

NR:

The number of revolutions per minute (rpm)

WD:

Workpiece diameter (mm)

BRA:

Back rake angle (\(^{\circ }\))

IH:

Insert hardness (HV)

SCA:

Side clearance angle (\(^{\circ }\))

AA:

Approach angle (\(^{\circ }\))

WH:

Workpiece hardness (HV)

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Authors and Affiliations

  1. Department of Industrial Engineering, Eskişehir Osmangazi University, Meşelik, Eskişehir, Turkey

    R. Aykut Arapoğlu

  2. Department of Mechanical Engineering, Eskişehir Osmangazi University, Meşelik, Eskişehir, Turkey

    Mehmet Alper Sofuoğlu & Sezan Orak

Authors
  1. R. Aykut Arapoğlu
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  2. Mehmet Alper Sofuoğlu
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  3. Sezan Orak
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Correspondence to Mehmet Alper Sofuoğlu.

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Arapoğlu, R.A., Sofuoğlu, M.A. & Orak, S. An ANN-Based Method to Predict Surface Roughness in Turning Operations. Arab J Sci Eng 42, 1929–1940 (2017). https://doi.org/10.1007/s13369-016-2385-y

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  • DOI: https://doi.org/10.1007/s13369-016-2385-y

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