Distributed Parallel Performance of Compression Molding Model for Some Characteristics Identification of Tire Tread Block
Norma Alias1, Roziha Darwis2, Noorazura Shahira Yusniman3, Nuraini Hashim4
1Norma Alias*, Center for Sustainable Nanomaterials, Ibnu Sina Institute for Scientific and Industrial Research, Universiti Teknologi Malaysia.
2Roziha Darwis, Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia.
3Noorazura Shahira Yusniman, Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Johor Bahru, Johor, Malaysia.
4Nuraini Hashim, Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Johor Bahru, Johor, Malaysia.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 4886-4892 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1935109119/2019©BEIESP | DOI: 10.35940/ijeat.A1935.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A control process based on the mathematical modeling of phase change simulations was used to address process limitations of tire tread manufacturing process. The objective of this model was to predict and monitor expected characteristic identifications respect to space and time. This paper proposes a high-performance control process for visualizing the temperature behavior of a compression molding process using pressure, density, elasticity, crack propagation, volume, space, and time during tire tread block manufacturing operations. The control process modeling of tire tread blocks at the liquid-solid interface enabled the use of large sparse computations for solving the real time molding process of a Rubber Compression Molding Machine (RCMM) LWB VRE 1000 type at the Malaysia Rubber Board Research Center (LGM). The modeling simulation emphasized parallel algorithms, domain decomposition, and parallel processing techniques on Distributed Parallel Computer Architecture (DPCS). This study identified alternative numerical methods and their parallelization by comparing numerical analysis and parallel performance indicators using tables, graphs, and multidimensional visualizations. The multidimensional visualization of characteristics using the high-performance control process model accurately illustrated the heating and cooling profile of the compression molding process.
Keywords: Compression molding, control process model, temperature behavior, elasticity, and high-performance analysis