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All Journal JMES The International Journal of Mechanical Engineering and Sciences
Dinny Harnany
Institut Teknologi Sepuluh Nopember
Energy Materials Science & Nanotechnology Mechanical Engineering

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Multi-Objective Prediction of Drilling EMS-45 with Finite Element, Backpropagation Neural Network, and Metaheuristic Model Mohammad Khoirul Effendi; Agus Sigit Pramono; Suhardjono Suhardjono; Sampurno Sampurno; Dinny Harnany; Fungky Dyan Pratiwi
JMES: The International Journal of Mechanical Engineering and Sciences Vol 8 No 1 (2024)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v8i1.19269

Abstract

Making holes with the minimum thrust force and torque using a drilling machine is challenging for researchers because of the difficulties in setting input parameter such as the type of drill tool, point of angle, and feeding speed. Therefore, the trial-and-error method to predict optimum input parameters through experiment can be replaced with the Back Propagation Neural Network (BPNN) and metaheuristic method (i.e., genetic algorithm (GA) and Simulated Annealing (SA)) method to reduce costs and time. BPNN can be used to represent the input-output correlation precisely. However, obtaining a model with minimum Mean Squared Error (MSE) requires much data for training, testing, and validation. Since the obtained data from experiments requires expensive costs, combining data from experimental and simulation using ANSYS should considered to reduce the experimental costs. This study was then conducted to answer the research problem using an EMS 45 tool steel as the workpiece, with the three input parameters: type of drill tools (HSS M2 and HSS M35), the points of angle (118 and 134 degrees) and feeding speed rates (0.07 and 0.1 mm/s). The 32 data from experimental and modeling were used to model the correlation between the input and output parameters of the drilling process using BPNN. The BPNN’s network-model with minimum MSE is then used as the objective function to determine the input parameters to obtain the smallest value of thrust force and torque using the hybrid method using GA and SA.
Optimization of 3D Printing Parameter Process for Product Tensile Strength from PLA Materials Using the Taguchi Method I Made Londen Batan; Arleta Listiyana Chandradewi; Arif Wahjudi; Dinny Harnany
JMES: The International Journal of Mechanical Engineering and Sciences Vol 7 No 2 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v7i2.16985

Abstract

Three-dimensional printing or 3D Printing is one of the revolutionary machines in addictive manufacturing techniques to create three-dimensional objects with complex structures. Until now there are many techniques in 3D printing, one of which is Fused Deposition Modeling (FDM), which is currently widely used because of its ease and low operational costs. However, in the printing process, there are important things that must receive attention, namely the process parameters. Because this is what really determines the quality of the printout. In this research, an analysis of the effect of process parameters such as: infill rate, infill pattern, extrusion temperature and layer thickness were carried out on the tensile strength of the printed product. The method used is the Taguchi method with the Orthogonal Array L 9 (3 4) experimental design. Three tensile test specimens were printed for each variation using a Cubic Chiron 3D printer, so a total of 27 specimens were printed. All specimens were tensile tested according to ASTM D638 standard, the results were analysed based on the average value and signal to ratio (SNR) value and their significance by analysis of variance (ANOVA). The results of the analysis show that the infill rate, infill pattern and layer thickness have a significant effect on the tensile strength of the printing results. The optimal value of the tensile strength is 56,876 MPa, occurs in the concentric pattern with an infill rate of 90%, and a layer thickness of 0.2 mm. From the confirmation test, the confidence interval values were obtained from 55,477 MPa to 58,275 MPa, meaning that the optimal predictive value was not significantly different from the confirmation test value.
"Water-In-Salt" Electrolyte For High Temperature Aluminum Ion Battery Application Sylvia Ayu Pradanawati; Dinny Harnany; Faizal Fatah; Nur Layli Amanah Amanah
JMES: The International Journal of Mechanical Engineering and Sciences Vol 7 No 2 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v7i2.18477

Abstract

This study focuses on examining aluminum chloride hexahydrate (AlCl3·6H2O) as an electrolyte salt in an Aluminum Ion Battery. The goal is to assess the effectiveness of AlCl3·6H2O as an electrolyte in an Aluminum Ion Battery, evaluate the battery's performance, and examine the anode and cathode properties of an Aluminum Ion Battery. Laboratory tests and literature analysis are the approaches used. Following cyclic voltammetry testing, it was shown that the water-in-salt electrolyte AlCl3 performed better than the 1M AlCl3 electrolyte. Compared to the 1M AlCl3 electrolyte, the hydrogen evolution reaction in the water-in-salt electrolyte AlCl3 has a smaller potential range. The cyclic voltammetry graph of an aluminum ion battery containing a water-in-salt AlCl3 electrolyte is noticeably smaller than that of an aluminum ion battery with a 1M AlCl3 electrolyte. It has been observed that the water-in-salt AlCl3 electrolyte requires more activation energy compared to the 1M AlCl3 electrolyte. Based on SEM-EDS data, using water-in-salt electrolyte AlCl3 for aluminum ion batteries is better as it does not cause significant defects in the anode and cathode.
The Effect of Rice Husk as Additive in Injection Molding Process Dinny Harnany; I Made Londen Batan; Arif Wahjudi; Sylvia Ayu Pradanawati
JMES: The International Journal of Mechanical Engineering and Sciences Vol 6 No 2 (2022)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v6i2.14182

Abstract

This study investigated the moldability and the mechanical properties of bio-composite with rice husk as natural reinforcement. Natural materials that are abundant in nature can be used as reinforcement for polymer materials. Natural materials as reinforcement in plastic materials were used to obtain alternative materials in an injection molding process. With rice husk, polypropylene, and MAPP, four compositions of bio-composite materials were made and used as raw material injection molding process. The moldability from this material was observed through visualization of the product. The mechanical properties of the materials were observed by the tensile strength and impact test on the injection molding product. The result showed that these materials could be injected to form ASTM D638-03 Type V tensile test and ASTM D256-04 impact test specimens. Visually, the more rice husk on the bio-composite material, the darker the product color. The differences in tensile strength values decreased along with increased rice husk content. All bio-composite materials had roughly the same tensile strength value and were lower than polypropylene, except RH-5%. The impact value of bio-composites was lower than polypropylene impact value and tended to decline along with the increase in the rice husk content. Scanning electron microscope (SEM) analyzes were done on the fracture side of the impact specimen. Microscale voids decreased and were rarely found by adding rice husk to the material bio-composite. On the other hand, rice husk breakage and pullout phenomenon on bio-composite material were found.
Determination of Injection Molding Process Parameters using Combination of Backpropagation Neural Network and Genetic Algorithm Optimization Method Arif Wahjudi; Thenny Daus Salamoni; I Made Londen Batan; Dinny Harnany
JMES: The International Journal of Mechanical Engineering and Sciences Vol 5 No 2 (2021)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v5i2.8592

Abstract

Co-Authors Agus Sigit Pramono Arif Wahjudi Arleta Listiyana Chandradewi Faizal Fatah Fungky Dyan Pratiwi I Made Londen Batan Mohammad Khoirul Effendi Nur Layli Amanah Amanah Sampurno Sampurno Suhardjono Suhardjono Sylvia Ayu Pradanawati Thenny Daus Salamoni