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All Journal Journal of Industrial Engineering and Halal Industries
Nguyen Huu Tho
Ho Chi Minh City University of Food Industry
Religion Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering

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SIMULATION OF FLUID FLOW THROUGH A STAINLESS STEEL GLOBE VALVE USING ENGINEERING FLUID DYNAMICS Nguyen Huu Tho
Journal of Industrial Engineering and Halal Industries Vol. 2 No. 1 (2021): Journal of Industrial Engineering and Halal Industries (JIEHIS)
Publisher : Industrial Engineering Department, Faculty of Science and Engineering, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiehis.2658

Abstract

Globe valves are often used in many practical application of industry with the aim of controlling the fluid flow through the valve. Valve design ensuring an operation capacity plays an important role for engineers. This paper presents the design and simulation of fluid flow through the globe valve using CAD/CAE tools such as Autodesk CFD. Besides, design of experiment technique Box-Behnken is used to integrate the CFD simulation to identify the optimal design parameters of the globe valve. These parameters are inlet pressure, orifice diameter, and outlet clearance. The results showed that the optimal parameters are appropriate to improve the valve design to ensure the maximum fluid flow rate.
APPLICATION OF BOX-BEHNKEN, ANN, AND ANFIS TECHNIQUES FOR IDENTIFICATION OF THE OPTIMUM PROCESSING PARAMETERS FOR FDM 3D PRINTING PARTS Nguyen Huu Tho
Journal of Industrial Engineering and Halal Industries Vol. 3 No. 1 (2022): Journal of Industrial Engineering and Halal Industries (JIEHIS)
Publisher : Industrial Engineering Department, Faculty of Science and Engineering, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiehis.3468

Abstract

Fused Deposition Modeling, among the various 3D printing approaches, is becoming more and more popular because of its capacity to produce complicated parts quickly. The tensile strength of parts printed with polylactic acid (PLA) showed a significant variation of many factors such as printing speed, printing temperature, printing angle and infill pattern. This study presented an experimental investigation of collecting data with four input factors namely printing speed, printing temperature, printing angle and infill pattern with the tensile strength response. The research methodology of the RSM Box-Behnken DOE method, ANN (Artificial neural network), and ANFIS (Adaptive neuro-fuzzy inference systems) has been used to determine the optimum process 3D printing parameters. The obtained results based on RSM, ANN and ANFIS methods are used to predict the tensile strength of 3D printed FDM details. The best tensile value is 7,03303 MPa corresponding to print speed of 30,0003 mm/s, printing temperature of 211,594℃, printing angle of 90° with Honeycomb” infill printing pattern. Moreover, the results also highlighted that ANFIS is potential approach for forecasting the tensile strength of 3D printing parts more competitively.
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