Optimization of Autoclave Reactors to Improve Bearing Life Using the Taguchi Method and the Response Surface Methodology

Author:

Fariz Farghani1,Patel Brijesh1ORCID,Chiu Hsien-Cheng1,Pan Shih-Jie2,Chen Cheng-Liang2,Lee Hao-Yeh3ORCID,Lin Po Ting14

Affiliation:

1. Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

2. Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan

3. Department of Chemical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

4. Intelligent Manufacturing Innovation Center (IMIC), National Taiwan University of Science and Technology, Taipei 10607, Taiwan

Abstract

Plastic pervasiveness in daily life has increased in tandem with population growth. Ethylene–vinyl acetate (EVA) is emerging as a popular compound for manufacturing plastic, which is obtained from ethylene and vinyl acetate synthesis. EVA is produced using autoclave reactors, which often encounter bearing damage under specific operating conditions. This research aims to optimize the parameters in autoclave reactors to enhance bearing life. The study focuses on two crucial factors: the number of impellers and the temperature, with bearing life as the response variable. Simulations using finite-element analysis were conducted to obtain the fatigue life of bearings and validated using real-time company data stating the damage of bearings within 80 days. The optimization process employed the Taguchi method (TM) and the response surface methodology (RSM). A comparison of these techniques revealed that temperature had the most significant influence on the response. Interestingly, both methods yielded the same optimal parameters: seven impellers and a temperature of 150 °C. The simulation results using these optimized parameters demonstrated a noteworthy 3.095% increase in bearing life compared to the initial design. The RSM outperformed the Taguchi method in accurately predicting response values with minimum prediction error under optimal conditions.

Funder

National Science and Technology Council (NSTC), Taiwan

Intelligent Manufacturing Innovation Center

Publisher

MDPI AG

Subject

General Engineering

Reference27 articles.

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5. Heinonen, M. (2023, January 20). LDPE Reactor Mixer Bearing Faults. Brüel & Kjær Vibro Megazine. Available online: https://www.bkvibro.com/wp-content/uploads/2020/12/LDPE_REACTOR_MIXER_BEARING_FAULTS_en_ext.pdf.

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