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研究生: Farghani Fariz
Farghani Fariz
論文名稱: 使用田口法和響應曲面法優化高壓釜反 應器以提高軸承壽命
Optimization of Autoclave Reactor to Improve Bearing Life Using Taguchi Method and Response Surface Methodology
指導教授: 林柏廷
Po Ting Lin
口試委員: 李豪業
Hao-Yeh Lee
陳誠亮
Cheng-Liang Chen
學位類別: 碩士
Master
系所名稱: 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年: 2023
畢業學年度: 111
語文別: 英文
論文頁數: 130
中文關鍵詞: Bearing LifeEthylene Vinyl AcetateOptimizationResponse Surface MethodologyTaguchi Method
外文關鍵詞: Bearing Life, Ethylene Vinyl Acetate, Optimization, Response Surface Methodology, Taguchi Method
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  • Plastic is common in daily life. The need for plastic keeps rising along with population growth. Ethylene vinyl acetate, or EVA, is one of the most used plastic. EVA is obtained from the synthesis of ethylene with vinyl acetate. One of the tools commonly used to produce EVA is the autoclave reactor. The autoclave reactor is a vessel that works at a temperature of 150-230 °C and a pressure of 1000-3000 atm. A common problem that often occurs in autoclave reactors is bearing damage. This research uses optimization methods to increase bearing life. This study chose two parameters, namely the number of impellers, temperature, and used bearing life as a response. Experiments in this study used Ansys software for simulation, which was validated using data from the company. Then the experimental results were optimized using the Taguchi method and Response Surface Methodology (RSM) assisted by Minitab software. These two methods are compared to find out which method gives better performance. The study results show that the two methods have similarities in that the parameter that significantly influences the response is temperature. Both methods also get the same optimal parameters, namely when: the number of impeller is 7, and the temperature is 150 °C. Simulation results using optimal parameters obtained an increase in bearing life of 3.095% compared to the initial design. The difference between the two methods is that RSM provides more detailed information about the effect of the relationship between factors and factor squared on responses. RSM is more accurate in predicting the response value under optimal conditions with a prediction error of 0.009%, while the Taguchi method has an error prediction value of 0.4208%.


    Plastic is common in daily life. The need for plastic keeps rising along with population growth. Ethylene vinyl acetate, or EVA, is one of the most used plastic. EVA is obtained from the synthesis of ethylene with vinyl acetate. One of the tools commonly used to produce EVA is the autoclave reactor. The autoclave reactor is a vessel that works at a temperature of 150-230 °C and a pressure of 1000-3000 atm. A common problem that often occurs in autoclave reactors is bearing damage. This research uses optimization methods to increase bearing life. This study chose two parameters, namely the number of impellers, temperature, and used bearing life as a response. Experiments in this study used Ansys software for simulation, which was validated using data from the company. Then the experimental results were optimized using the Taguchi method and Response Surface Methodology (RSM) assisted by Minitab software. These two methods are compared to find out which method gives better performance. The study results show that the two methods have similarities in that the parameter that significantly influences the response is temperature. Both methods also get the same optimal parameters, namely when: the number of impeller is 7, and the temperature is 150 °C. Simulation results using optimal parameters obtained an increase in bearing life of 3.095% compared to the initial design. The difference between the two methods is that RSM provides more detailed information about the effect of the relationship between factors and factor squared on responses. RSM is more accurate in predicting the response value under optimal conditions with a prediction error of 0.009%, while the Taguchi method has an error prediction value of 0.4208%.

    Table of Contents Table of Contents .................................................................................................................. ii Nomenclature ....................................................................................................................... vi Table of Tables .................................................................................................................. viii Table of Figures .................................................................................................................... x 1. Introduction ....................................................................................................................... 1 1.1. Introduction to Optimization in EVA Autoclave Reactor ................................................ 1 1.2. Research Development of Optimization in EVA Autoclave Reactor ............................... 5 1.2.1. Literature Reviews ............................................................................................. 5 1.2.2. Summary ............................................................................................................ 9 1.3. Scope of the Present Study ........................................................................................... 10 2. Theoretical Background .................................................................................................. 11 2.1. Ethylene Vinyl Acetate (EVA) ..................................................................................... 11 2.2. EVA Autoclave Reactor System ................................................................................... 15 2.2.1. Introduction to EVA Autoclave Reactor ........................................................... 15 2.2.2. Introduction to Blade Types in EVA Autoclave Reactor ................................... 17 2.3. Bearing......................................................................................................................... 21 iii 2.3.1. Introduction of Bearings ................................................................................... 21 2.3.2. Bearing Life ..................................................................................................... 24 2.4. Design of Experiments by Taguchi ............................................................................... 26 2.4.1. Steps of Design of Experiments ........................................................................ 27 2.4.2. Design of Experiments using Orthogonal Arrays .............................................. 28 2.4.3. Signal to Noise Ratio (S/N Ratio) ..................................................................... 32 2.5. Response Surface Methodology .................................................................................... 37 3. Methodology ................................................................................................................... 41 3.1. Flowchart of Research .................................................................................................. 41 3.2. Geometry on Autoclave Reactor ................................................................................... 42 3.3. Design of Experiment ................................................................................................... 47 3.3.1. Selection of Responses ..................................................................................... 48 3.3.2. DOE for Taguchi Method ................................................................................. 50 3.3.4. DOE for RSM .................................................................................................. 53 3.4. Simulation .................................................................................................................... 54 3.4.1. Boundary Condition Solid ................................................................................ 57 3.4.2. Boundary Condition Fluid ................................................................................ 58 iv 3.4.3. Fatigue Life Calculation on Ansys .................................................................... 60 3.5. Taguchi Method and Response Surface Methodology ................................................... 66 3.5.1. Defining Problems and Objectives .................................................................... 69 4. Result and Discussion ..................................................................................................... 71 4.1. Simulation Results........................................................................................................ 71 4.2. Optimization using the Taguchi method ....................................................................... 73 4.2.1. Result Data ....................................................................................................... 73 4.2.2. Analyze Taguchi .............................................................................................. 74 4.2.3. Predict Taguchi Result ...................................................................................... 76 4.3. Optimization using Response Surface Method (RSM) .................................................. 78 4.3.1. Result Data ....................................................................................................... 78 4.3.2. Analyze Response Surface ................................................................................ 79 4.2.3. Response Optimizer.......................................................................................... 84 4.4. Validation for Optimization Method. ............................................................................ 85 4.6. Validation for Optimal Design ...................................................................................... 86 5. Conclusion ...................................................................................................................... 88 Reference ............................................................................................................................ 90 v Appendix 1. Boundary Conditions for Simulation ............................................................... 94 Appendix 2. Taguchi Method and RSM process using Minitab ......................................... 102 Appendix 3. How to do a simulation ................................................................................. 113

    M. Roser, H. Ritchie, E. Ortiz-Ospina, and L. J. O. w. i. d. Rodés-Guirao, "World population
    growth," 2013.
    [2] G. Fiorenza, V. Sharma, G. J. E. c. Braccio, and management, "Techno-economic evaluation of
    a solar powered water desalination plant," vol. 44, no. 14, pp. 2217-2240, 2003.
    [3] W. W. Lau et al., "Evaluating scenarios toward zero plastic pollution," vol. 369, no. 6510, pp.
    1455-1461, 2020.
    [4] H. Knuuttila, A. Lehtinen, and A. J. L. T. P. o. P. Nummila-Pakarinen, "Advanced polyethylene
    technologies—controlled material properties," pp. 13-28, 2004.
    [5] I. L. Chien, T. W. Kan, and B.-S. Chen, "Dynamic simulation and operation of a high pressure
    ethylene-vinyl acetate (EVA) copolymerization autoclave reactor," Computers & Chemical
    Engineering, vol. 31, no. 3, pp. 233-245, 2007.
    [6] Y. Lee et al., "Multicompartment Model of an Ethylene–Vinyl Acetate Autoclave Reactor: A
    Combined Computational Fluid Dynamics and Polymerization Kinetics Model," Industrial &
    Engineering Chemistry Research, vol. 58, no. 36, pp. 16459-16471, 2019.
    [7] G. Sivalingam, N. J. Soni, and S. M. J. T. C. J. o. C. E. Vakil, "Detection of decomposition for high
    pressure ethylene/vinyl acetate copolymerization in autoclave reactor using principal
    component analysis on heat balance model," vol. 93, no. 6, pp. 1063-1075, 2015.
    [8] D. You, D. Feron, and G. Turluer, "Experimental simulation of low rate primary coolant leaks.
    For the case of vessel head penetrations affected by through wall cracking," 2002.
    [9] V. Kumar, "Multivariate statistical monitoring of a high-pressure LDPE and EVA copolymer
    industrial process," 2002.
    [10] E. Turman and P. J. C. E. S. Wayne Strasser, "CFD modeling of LDPE autoclave reactor to reduce
    ethylene decomposition: Part 2 identifying and reducing contiguous hot spots," vol. 257, p.
    117722, 2022.
    [11] M. Heinonen, "LDPE REACTOR MIXER BEARING FAULTS," vol. Brüel & Kjær Vibro Megazine,
    2013.
    [12] M. H. Albdery and I. Szabó, "A-Review-Of-Fault-Diagnosis-Techniques-Of-Rolling-Element-
    Bearings-For-Rotating-Machinery.pdf," INTERNATIONAL JOURNAL OF SCIENTIFIC &
    TECHNOLOGY RESEARCH VOLUME 10, 2021.
    [13] K. Li and Q. Wang, "Study on signal recognition and diagnosis for spacecraft based on deep
    learning method," in 2015 Prognostics and System Health Management Conference (PHM),
    2015, pp. 1-5: IEEE.
    [14] A. Nabhan, N. Ghazaly, A. Samy, M. J. T. J. o. E. Mousa, Sciences, and Technology, "Bearing
    fault detection techniques-a review," vol. 3, no. 2, pp. 1-18, 2015.
    91
    [15] N. Jammu, P. J. I. J. o. E. S. Kankar, and Technology, "A review on prognosis of rolling element
    bearings," vol. 3, no. 10, pp. 7497-7503, 2011.
    [16] C. Hamzaçebi, P. Li, P. Pereira, and H. Navas, "Taguchi Method as a Robust Design Tool," in
    Quality Control-Intelligent Manufacturing, Robust Design and Charts: IntechOpen, 2020.
    [17] R. H. Myers, D. C. Montgomery, and C. M. Anderson-Cook, Response surface methodology:
    process and product optimization using designed experiments. John Wiley & Sons, 2016.
    [18] A. Brandolin, C. Sarmoria, A. Lótpez‐Rodríguez, K. S. Whiteley, B. J. P. E. Del Amo Fernández,
    and Science, "Prediction of molecular weight distributions by probability generating functions.
    Application to industrial autoclave reactors for high pressure polymerization of ethylene and
    ethylene‐vinyl acetate," vol. 41, no. 8, pp. 1413-1426, 2001.
    [19] Y. Wang, C. Liu, S. Wang, and H. J. K. J. o. C. E. Dong, "Investigation on flow characteristic and
    reaction process inside an EVA autoclave reactor using CFD modeling combined with
    polymerization kinetics," pp. 1-12, 2022.
    [20] I. Torotwa and C. J. D. Ji, "A study of the mixing performance of different impeller designs in
    stirred vessels using computational fluid dynamics," vol. 2, no. 1, p. 10, 2018.
    [21] P. Pladis, V. Kanellopoulos, A. Baltsas, and C. Kiparissides, "Dynamic Modeling and
    Optimization of Flash Separators for Highly-Viscous Polymerization Processes," in Computer
    Aided Chemical Engineering, vol. 29: Elsevier, 2011, pp. 723-727.
    [22] A. M. J. I. E. I. M. Henderson, "Ethylene-vinyl acetate (EVA) copolymers: a general review," vol.
    9, no. 1, pp. 30-38, 1993.
    [23] J. Tian, W. Yu, and C. J. P. Zhou, "The preparation and rheology characterization of long chain
    branching polypropylene," vol. 47, no. 23, pp. 7962-7969, 2006.
    [24] L. Wang, B. Li, M. Yang, C. Chen, Y. J. J. o. c. Liu, and i. science, "Effect of Ni cations and
    microwave hydrothermal treatment on the related properties of layered double hydroxide–
    ethylene vinyl acetate copolymer composites," vol. 356, no. 2, pp. 519-525, 2011.
    [25] X. M. Shi, J. Zhang, J. Jin, and S. J. Chen, "Non-isothermal crystallization and melting of
    ethylene-vinyl acetate copolymers with different vinyl acetate contents," Express Polymer
    Letters, vol. 2, no. 9, pp. 623-629, 2008.
    [26] A. K. Maurya, A. Mishra, and N. Mishra, "Nanoengineered polymeric biomaterials for drug
    delivery system," in Nanoengineered Biomaterials for Advanced Drug Delivery: Elsevier, 2020,
    pp. 109-143.
    [27] S. Jiang, K. Wang, H. Zhang, Y. Ding, and Q. Yu, "Encapsulation of PV Modules Using Ethylene
    Vinyl Acetate Copolymer as the Encapsulant," Macromolecular Reaction Engineering, vol. 9,
    no. 5, pp. 522-529, 2015.
    [28] A. Charki, "Accelerated degradation testing of a photovoltaic module," Journal of Photonics
    for Energy, vol. 3, no. 1, 2013.
    [29] P. M. J. B. e. p. Doran, "Mixing," pp. 255-332, 2013.
    92
    [30] V. J. I. J. o. S. Srinivasan and Technology, "Analysis of dynamic load characteristics on
    hydrostatic bearing with variable viscosity and temperature using simulation technique," vol.
    6, no. 6, pp. 4797-4803, 2013.
    [31] R. Rubini, U. J. M. s. Meneghetti, and s. processing, "Application of the envelope and wavelet
    transform analyses for the diagnosis of incipient faults in ball bearings," vol. 15, no. 2, pp. 287-
    302, 2001.
    [32] V. Patel, N. Tandon, and R. J. M. Pandey, "Defect detection in deep groove ball bearing in
    presence of external vibration using envelope analysis and Duffing oscillator," vol. 45, no. 5,
    pp. 960-970, 2012.
    [33] A. Choudhury and N. J. T. i. Tandon, "Application of acoustic emission technique for the
    detection of defects in rolling element bearings," vol. 33, no. 1, pp. 39-45, 2000.
    [34] S. Al-Dossary, R. R. Hamzah, and D. J. A. a. Mba, "Observations of changes in acoustic emission
    waveform for varying seeded defect sizes in a rolling element bearing," vol. 70, no. 1, pp. 58-
    81, 2009.
    [35] D. Salome, "Estimating Remaining Useful Lifetime of Bearings Using Raw Vibration
    Measurements," 2019.
    [36] R. Sidar, P. K. Sen, G. J. I. J. o. S. R. E. Sahu, and Technology, "Review of vibration based fault
    diagnosis in rolling element bearing and vibration analysis techniques," vol. 4, no. 10, pp. 998-
    1003, 2015.
    [37] P. Gupta and M. J. M. T. P. Pradhan, "Fault detection analysis in rolling element bearing: A
    review," vol. 4, no. 2, pp. 2085-2094, 2017.
    [38] F. Camci, K. Medjaher, N. Zerhouni, P. J. Q. Nectoux, and r. e. international, "Feature
    evaluation for effective bearing prognostics," vol. 29, no. 4, pp. 477-486, 2013.
    [39] Y. J. Kim and P. J. J. J. o. C. f. C. Heffernan, "Fatigue behavior of externally strengthened
    concrete beams with fiber-reinforced polymers: State of the art," vol. 12, no. 3, pp. 246-256,
    2008.
    [40] "Bearing life – Calculating the basic fatigue life expectancy of rolling bearings," vol. A
    PUBLICATION OF NSK EUROPE.
    [41] M. DouglasC, "Design and analysis of experiments. Douglas C. Montgomery," ed: Wiley,
    London, 2009.
    [42] Y. Li, J.-I. Choi, Y. Choic, and J. J. E. A. o. C. F. M. Kim, "A simple and efficient outflow boundary
    condition for the incompressible Navier–Stokes equations," vol. 11, no. 1, pp. 69-85, 2017.
    [43] U. Lertxundi et al., "CFD simulations of radioembolization: a proof-of-concept study on the
    impact of the hepatic artery tree truncation," vol. 9, no. 8, p. 839, 2021.
    [44] L. Gyurik, A. Egedy, J. Zou, N. Miskolczi, Z. Ulbert, and H. J. J. o. t. E. I. Yang, "Hydrodynamic
    modelling of a two-stage biomass gasification reactor," vol. 92, no. 3, pp. 403-412, 2019.
    93
    [45] A. Sudhamshu et al., "Numerical study of effect of pitch angle on performance characteristics
    of a HAWT," vol. 19, no. 1, pp. 632-641, 2016.
    [46] I. Jenish, M. Appadurai, and E. F. I. J. I. J. S. M. S. Raj, "CFD Analysis of modified rushton turbine
    impeller," vol. 4, pp. 8-13, 2021.
    [47] R. Zadghaffari, J. Moghaddas, J. J. C. Revstedt, and c. engineering, "A mixing study in a double-
    Rushton stirred tank," vol. 33, no. 7, pp. 1240-1246, 2009.
    [48] I. T. Hassan and C. W. J. A. J. Robinson, "Stirred‐tank mechanical power requirement and gas
    holdup in aerated aqueous phases," vol. 23, no. 1, pp. 48-56, 1977.

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