Ultra-high precision diamond turning of advanced contact lens polymers
- Authors: Liman, Muhammad Mukhtar
- Date: 2020
- Subjects: Contact lenses , Electrostatic lenses Lenses -- Design and construction
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10948/46108 , vital:39496
- Description: Contact lens polymer-based materials are extensively used in the optical industry owing to their excellent corrosion resistance, the possibility of mass production and their ability to be processed without external lubrication. Owing to the fast growth in optical industries, contact lens (CL) requires high accuracy and a high surface quality. The demand for high-accuracy and minimal surface roughness drives the development of ultra-high precision machining technology with regard to single point diamond turning (SPDT). Ultra-high precision diamond turning is an advanced manufacturing technique employed in the machining of CLs owing to its capability of producing high optical surfaces with complex shapes and nanometric accuracy. Yet, even with the advances in ultra-high precision machining (UHPM), it is not continuously easy to achieve a highquality surface finish during polymers machining as the adhesion of the tool chip around the tool dictates the presence of electrostatic charges. The electrostatic charges encountered by a cutting tool when turning advanced CLs are important as they reflect the quality and condition of the tool, machine, fixture, and sometimes even the finished surface, which is responsible for tool wear and poor surface quality. This study investigates the role of cutting parameters, namely cutting speed, feed rate and depth of cut on surface roughness (Ra), electrostatic charge (ESC) and material removal rate (MRR), which determines machine economics and the quality of machining contact lens polymers. The experiments were mainly conducted on two different advanced polymeric materials: polymethyl methacrylate (PMMA) and Optimum Extreme (Roflufocon E) CLs. Experimentation was carried out on the Nanoform 250 ultra-grind turning machine with a monocrystalline diamond-cutting tool for machining the PMMA and Roflufocon E CL polymers, covering a wide range of machining parameters. Before conducting the experiments, a design of experiment was conducted according to the response surface methodology (RSM) that is based on the Box-Behnken Design (BBD). In addition, the research study focused on the determination of the optimum cutting conditions leading to minimum Ra and ESC as well as maximum productivity in the SPDT of the PMMA and Roflufocon E CL polymers, using a monocrystalline diamondcutting tool. The optimization was based on RSM together with the desirability function approach. In addition, a mathematical model was developed for Ra, ESC and MRR using a RSM regression analysis for PMMA and Roflufocon E CL polymers by means of Design Expert software. RSM allowed for the optimization of the cutting conditions for minimal Ra and ESC as well as maximal MRR, which provides an effective knowledge base for process parameters to enhance process performance in the SPDT of CL polymers. Furthermore, this study also deals with the development of Ra, ESC and MRR prediction models for the diamond turning of PMMA and Roflufocon E CL polymers, using the fuzzy logic based artificial intelligence (AI) method. The fuzzy logic model has been developed in terms of machining parameters for the prediction of Ra, ESC and MRR. To judge the accuracy and ability of the fuzzy logic model, an average percentage error was used. The comparative evaluation of experiments and the fuzzy logic approach suggested that the obtained average errors of Ra, ESC and MRR using the fuzzy logic system were in agreement with the experimental results. Hence, the developed fuzzy logic rules can be effectively utilized to predict the ESC, Ra and MRR of PMMA and Roflufocon E CL polymers in automated optical manufacturing environments for high accuracy and a reduction of computational cost. Moreover, owing to the brittle nature of optical polymers, the Roflufocon E CL polymer requires ductile-mode machining for improved surface quality. Molecular Dynamics (MD) simulation methods are thus applied to investigate the atomistic reaction at the tool/workpiece surface to clearly study and observe conditions occurring at nanometric scale in polymer machining. This research study is particularly concerned with the comparative analysis of experiments and a MD study of the Roflufocon E optical polymer nano cutting approach to the atomistic visualization of the plastic material flow at the tool/workpiece interface during cutting. The simulated MD acting force, machine stresses, and the temperature at the cutting region were evaluated to access the accuracy of the model. Hence, the nanomachining simulations were found to have a correlation to the experimental machining results.
- Full Text:
- Date Issued: 2020
- Authors: Liman, Muhammad Mukhtar
- Date: 2020
- Subjects: Contact lenses , Electrostatic lenses Lenses -- Design and construction
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10948/46108 , vital:39496
- Description: Contact lens polymer-based materials are extensively used in the optical industry owing to their excellent corrosion resistance, the possibility of mass production and their ability to be processed without external lubrication. Owing to the fast growth in optical industries, contact lens (CL) requires high accuracy and a high surface quality. The demand for high-accuracy and minimal surface roughness drives the development of ultra-high precision machining technology with regard to single point diamond turning (SPDT). Ultra-high precision diamond turning is an advanced manufacturing technique employed in the machining of CLs owing to its capability of producing high optical surfaces with complex shapes and nanometric accuracy. Yet, even with the advances in ultra-high precision machining (UHPM), it is not continuously easy to achieve a highquality surface finish during polymers machining as the adhesion of the tool chip around the tool dictates the presence of electrostatic charges. The electrostatic charges encountered by a cutting tool when turning advanced CLs are important as they reflect the quality and condition of the tool, machine, fixture, and sometimes even the finished surface, which is responsible for tool wear and poor surface quality. This study investigates the role of cutting parameters, namely cutting speed, feed rate and depth of cut on surface roughness (Ra), electrostatic charge (ESC) and material removal rate (MRR), which determines machine economics and the quality of machining contact lens polymers. The experiments were mainly conducted on two different advanced polymeric materials: polymethyl methacrylate (PMMA) and Optimum Extreme (Roflufocon E) CLs. Experimentation was carried out on the Nanoform 250 ultra-grind turning machine with a monocrystalline diamond-cutting tool for machining the PMMA and Roflufocon E CL polymers, covering a wide range of machining parameters. Before conducting the experiments, a design of experiment was conducted according to the response surface methodology (RSM) that is based on the Box-Behnken Design (BBD). In addition, the research study focused on the determination of the optimum cutting conditions leading to minimum Ra and ESC as well as maximum productivity in the SPDT of the PMMA and Roflufocon E CL polymers, using a monocrystalline diamondcutting tool. The optimization was based on RSM together with the desirability function approach. In addition, a mathematical model was developed for Ra, ESC and MRR using a RSM regression analysis for PMMA and Roflufocon E CL polymers by means of Design Expert software. RSM allowed for the optimization of the cutting conditions for minimal Ra and ESC as well as maximal MRR, which provides an effective knowledge base for process parameters to enhance process performance in the SPDT of CL polymers. Furthermore, this study also deals with the development of Ra, ESC and MRR prediction models for the diamond turning of PMMA and Roflufocon E CL polymers, using the fuzzy logic based artificial intelligence (AI) method. The fuzzy logic model has been developed in terms of machining parameters for the prediction of Ra, ESC and MRR. To judge the accuracy and ability of the fuzzy logic model, an average percentage error was used. The comparative evaluation of experiments and the fuzzy logic approach suggested that the obtained average errors of Ra, ESC and MRR using the fuzzy logic system were in agreement with the experimental results. Hence, the developed fuzzy logic rules can be effectively utilized to predict the ESC, Ra and MRR of PMMA and Roflufocon E CL polymers in automated optical manufacturing environments for high accuracy and a reduction of computational cost. Moreover, owing to the brittle nature of optical polymers, the Roflufocon E CL polymer requires ductile-mode machining for improved surface quality. Molecular Dynamics (MD) simulation methods are thus applied to investigate the atomistic reaction at the tool/workpiece surface to clearly study and observe conditions occurring at nanometric scale in polymer machining. This research study is particularly concerned with the comparative analysis of experiments and a MD study of the Roflufocon E optical polymer nano cutting approach to the atomistic visualization of the plastic material flow at the tool/workpiece interface during cutting. The simulated MD acting force, machine stresses, and the temperature at the cutting region were evaluated to access the accuracy of the model. Hence, the nanomachining simulations were found to have a correlation to the experimental machining results.
- Full Text:
- Date Issued: 2020
Diamond turning of contact lens polymers
- Authors: Liman, Muhammad Mukhtar
- Date: 2017
- Subjects: Diamond turning Contact lenses , Electrostatic lenses Lenses -- Design and construction Neural networks (Computer science)
- Language: English
- Type: Thesis , Masters , MEng
- Identifier: http://hdl.handle.net/10948/19223 , vital:28789
- Description: Contact lens production requires high accuracy and good surface integrity. Surface roughness is generally used to measure the index quality of a turning process. It has been an important response because it has direct influence toward the part performance and the production cost. Hence, choosing optimal cutting parameters will not only improve the quality measure but also the productivity. In this study, an ONSI-56 (Onsifocon A) contact lens buttons were used to investigate the triboelectric phenomena and the effects of turning parameters on surface finish of the lens materials. ONSI-56 specimens are machined by Precitech Nanoform Ultra-grind 250 precision machine and the roughness values of the diamond turned surfaces are measured by Taylor Hopson PGI Profilometer. Electrostatics values were measured using electrostatic voltmeter. An artificial neural network (ANN) and response surface (RS) model were developed to predict surface roughness and electrostatic discharge (ESD) on the turned ONSI-56. In the development of predictive models, turning parameters of cutting speed, feed rate and depth of cut were considered as model variables. The required data for predictive models were obtained by conducting a series of turning test and measuring the surface roughness and ESD data. Good agreement is observed between the predictive models results and the experimental measurements. The ANN and RSM models for ONSI-56 are compared with each other using mean absolute percentage error (MAPE) for accuracy and computational cost.
- Full Text:
- Date Issued: 2017
- Authors: Liman, Muhammad Mukhtar
- Date: 2017
- Subjects: Diamond turning Contact lenses , Electrostatic lenses Lenses -- Design and construction Neural networks (Computer science)
- Language: English
- Type: Thesis , Masters , MEng
- Identifier: http://hdl.handle.net/10948/19223 , vital:28789
- Description: Contact lens production requires high accuracy and good surface integrity. Surface roughness is generally used to measure the index quality of a turning process. It has been an important response because it has direct influence toward the part performance and the production cost. Hence, choosing optimal cutting parameters will not only improve the quality measure but also the productivity. In this study, an ONSI-56 (Onsifocon A) contact lens buttons were used to investigate the triboelectric phenomena and the effects of turning parameters on surface finish of the lens materials. ONSI-56 specimens are machined by Precitech Nanoform Ultra-grind 250 precision machine and the roughness values of the diamond turned surfaces are measured by Taylor Hopson PGI Profilometer. Electrostatics values were measured using electrostatic voltmeter. An artificial neural network (ANN) and response surface (RS) model were developed to predict surface roughness and electrostatic discharge (ESD) on the turned ONSI-56. In the development of predictive models, turning parameters of cutting speed, feed rate and depth of cut were considered as model variables. The required data for predictive models were obtained by conducting a series of turning test and measuring the surface roughness and ESD data. Good agreement is observed between the predictive models results and the experimental measurements. The ANN and RSM models for ONSI-56 are compared with each other using mean absolute percentage error (MAPE) for accuracy and computational cost.
- Full Text:
- Date Issued: 2017
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