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Predicting surface quality of γ-TiAl produced by additive manufacturing process using response surface method

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Abstract

Electron beam melting (EBM) has been found to be a promising technology for producing complex shaped parts from gamma titanium aluminide alloys (γ-TiAl). The parts produced by this process are projected to have dimensions very close to the desired final shapes. However, the surface roughness of the parts produced by EBM is excessively rough. In many applications, it is necessary to improve the quality of manufactured parts using a convenient post process. This paper determines process parameters of end milling when it is used as a post process for the parts produced by EBM. Design of experiments has been used to study the effect of the selected input parameters of end milling (spindle speed, feed rate, depth of cut and coolant type) on the surface roughness of γ-TiAl parts. Response surface methodology is used to develop a predictive model for surface roughness. Effects of the selected milling process are investigated. This paper also optimizes the selected process parameters to minimize the value of the obtained surface roughness.

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Authors and Affiliations

  1. FARCAMT Chair, Advanced Manufacturing Institute, King Saud University, Riyadh, Saudi Arabia

    Abdulrahman Al-Ahmari, Mohammad Ashfaq & Basem Abdo

  2. Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia

    Abdulrahman Al-Ahmari, Abdullah Alfaify, Abdulrahman Alomar & Abdelnaser Dawud

Authors
  1. Abdulrahman Al-Ahmari
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  2. Mohammad Ashfaq
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  3. Abdullah Alfaify
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  4. Basem Abdo
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  5. Abdulrahman Alomar
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  6. Abdelnaser Dawud
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Correspondence to Abdulrahman Al-Ahmari.

Additional information

Abdulrahman Al-Ahmari is a dean of advanced manufacturing institute and professor of Industrial Engineering at King Saud University, Riyadh, Saudi Arabia. He received a Ph.D. in Manufacturing Systems Engineering from the University of Sheffield in 1998. Professor Al-Ahmari has published papers in leading journals of Industrial and Manufacturing Engineering. He led a number of funded projects from different organizations in Saudi Arabia. His research interests are advanced manufacturing technologies, Petri nets, analysis and design of manufacturing systems; Computer Integrated Manufacturing (CIM); optimization of manufacturing operations; FMS and cellular manufacturing systems and applications of DSS in manufacturing.

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Al-Ahmari, A., Ashfaq, M., Alfaify, A. et al. Predicting surface quality of γ-TiAl produced by additive manufacturing process using response surface method. J Mech Sci Technol 30, 345–352 (2016). https://doi.org/10.1007/s12206-015-1239-y

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  • DOI: https://doi.org/10.1007/s12206-015-1239-y

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