Modeling and multiresponse optimization of cutting parameters in SPDT of a rigid contact lens polymer using RSM and desirability function

  • Muhammad Mukhtar LimanEmail author
  • Khaled Abou-El-Hossein


Amidst different conventional contact lens manufacturing techniques, single-point diamond turning (SPDT) is one of the recently developed ultra-high precision machining techniques employed in the fabrication of advanced contact lenses due to its capability of producing high optical surfaces of complex shapes and nanometric accuracy. SPDT is regarded as an effective process for the generation of high-quality functional surfaces in optical industries. However, despite advances in the ultra-high precision machining, it is not always easy to achieve a high-quality surface finish with maximum productivity. Machining parameters, namely cutting speed, feed rate, and depth of cut, play the lead role in determining the machine economics and quality of machining. The present study focuses on the determination of the optimum cutting conditions leading to minimum surface roughness as well as electrostatic charge and maximum productivity, in SPDT of the polymethyl methacrylate (PMMA) contact lens polymer using monocrystalline diamond cutting tool. The optimization is based on the response surface methodology (RSM) together with the desirability function approach. In addition, a mathematical model is developed for surface roughness (Ra), electrostatic charge (ESC), and material removal rate (MRR) using RSM regression analysis for a rigid contact lens polymer by the Design-Expert software. RSM allowed the optimization of the cutting conditions for minimal surface roughness, electrostatic charge, and maximal material removal rate which provides an effective knowledge base for process parameters, to make its enhancement of process performance in SPDT of contact lens polymer.


PMMA contact lens polymer Electrostatic charge Material removal rate Single-point diamond turning Response surface methodology Surface roughness and optimization 


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Funding information

We would like to acknowledge the support of the National Research Foundation (NRF) of South Africa and the Research Capacity Development, Nelson Mandela University for the financial support.


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© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Mechatronics Engineering DepartmentNelson Mandela UniversityPort ElizabethSouth Africa

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