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All Journal Dinamika Teknik Mesin : Jurnal Keilmuan dan Terapan Teknik Mesin
Bismantolo, P.
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Aerospace Engineering Automotive Engineering Mechanical Engineering Physics

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Prediksi kekasaran permukaan baja S45C terhadap parameter pemesinan dan getaran pada proses bubut menggunakan metode artificial neural network Bismantolo, P.; Utama, F.P.; Kurniawan, A.
Dinamika Teknik Mesin: Jurnal Keilmuan dan Terapan Teknik Mesin Vol 13, No 1 (2023): Dinamika Teknik Mesin: Jurnal Keilmuan dan Terapan Teknik Mesin
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/dtm.v13i1.605

Abstract

Based on machining characteristics, this study gives surface roughness modeling for machine parts. The artificial models used the Artificial Neural Network (ANN) modeling approach and multivariable regression analysis were used to create the prediction model. S45C steel was one of the materials utilized in this research. With a depth of cut 0.5 mm, the parameters are spindle (n) of 165, 330, 585, and 1170 rpm and feed (f) of 0.2 mm/rev. Utilizing TIBCO software, surface roughness values will be predicted. Equations derived from multivariable linear regression serve as the study's findings. At 1170 rpm spindle rotation and 0.5 mm of cut depth, the lowest surface roughness measurement of 1.114 (μm) was recorded. At spindle speed 585 and a cut depth of 2.0 mm, a roughness value of 2.999 (μm) was recorded as the maximum value. Roughness rises at spindle speeds between 585 and 900 rpm when cutting at shallower depths. The third modeling had the smallest error value, which was 11.21%, and surface roughness value using an artificial neural network with five simple multi-layer models.
Pemanfaatan limbah tandan buah kosong kelapa sawit sebagai penguat komposit untuk diaplikasikan sebagai bahan baku outer shell helm Standar Nasional Indonesia (SNI) Bismantolo, P.; Hestiawan, H.; Wardhani, F.; Utama, M.F.
Dinamika Teknik Mesin: Jurnal Keilmuan dan Terapan Teknik Mesin Vol 12, No 1 (2022): Dinamika Teknik Mesin: Jurnal Keilmuan dan Terapan Teknik Mesin
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (388.133 KB) | DOI: 10.29303/dtm.v12i1.498

Abstract

Oil palm empty fruit bunch is abundantly available as waste from palm oil processing which is only used for boiler fuel and plant fertilizers. This study aims to investigate the utilization of oil palm empty fruit bunch as a composite reinforcement material to be applied as a raw material for the outer shell of Indonesian national standard (SNI) helmets. The materials used include oil palm empty fruit bunch, the polyester resin of BQTN yukalac, and the catalyst of MEKPO. The manufacturing process uses the hand lay-up technique by varying the fiber volume fractions 3, 6, 9, 12%, and therefore the fiber size passes mesh of 20 and 50. The tensile test uses the ASTM standard D 638 while the impact test uses the ASTM standard D 5942. Fiber volume fraction and fiber size affect the mechanical properties of oil palm fiber reinforced composites. The results of the tensile and impact tests showed that the highest tensile strength and impact toughness were obtained within the composite with a fiber volume fraction of 6% and a mesh of 50, which were 34.74 MPa and 60.21 kJ/m², respectively. In comparison with the tensile strength of the SNI helmet of 33.93 MPa, the oil palm empty fruit bunch fiber can be used as a composite reinforcement for the outer shell of the SNI helmet.
Prediksi kekasaran permukaan baja S45C terhadap parameter pemesinan dan getaran pada proses bubut menggunakan metode artificial neural network Bismantolo, P.; Utama, F.P.; Kurniawan, A.
Dinamika Teknik Mesin Vol 13, No 1 (2023): Dinamika Teknik Mesin: Jurnal Keilmuan dan Terapan Teknik Mesin
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/dtm.v13i1.605

Abstract

Based on machining characteristics, this study gives surface roughness modeling for machine parts. The artificial models used the Artificial Neural Network (ANN) modeling approach and multivariable regression analysis were used to create the prediction model. S45C steel was one of the materials utilized in this research. With a depth of cut 0.5 mm, the parameters are spindle (n) of 165, 330, 585, and 1170 rpm and feed (f) of 0.2 mm/rev. Utilizing TIBCO software, surface roughness values will be predicted. Equations derived from multivariable linear regression serve as the study's findings. At 1170 rpm spindle rotation and 0.5 mm of cut depth, the lowest surface roughness measurement of 1.114 (μm) was recorded. At spindle speed 585 and a cut depth of 2.0 mm, a roughness value of 2.999 (μm) was recorded as the maximum value. Roughness rises at spindle speeds between 585 and 900 rpm when cutting at shallower depths. The third modeling had the smallest error value, which was 11.21%, and surface roughness value using an artificial neural network with five simple multi-layer models.
Pemanfaatan limbah tandan buah kosong kelapa sawit sebagai penguat komposit untuk diaplikasikan sebagai bahan baku outer shell helm Standar Nasional Indonesia (SNI) Bismantolo, P.; Hestiawan, H.; Wardhani, F.; Utama, M.F.
Dinamika Teknik Mesin Vol 12, No 1 (2022): Dinamika Teknik Mesin: Jurnal Keilmuan dan Terapan Teknik Mesin
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/dtm.v12i1.498

Abstract

Oil palm empty fruit bunch is abundantly available as waste from palm oil processing which is only used for boiler fuel and plant fertilizers. This study aims to investigate the utilization of oil palm empty fruit bunch as a composite reinforcement material to be applied as a raw material for the outer shell of Indonesian national standard (SNI) helmets. The materials used include oil palm empty fruit bunch, the polyester resin of BQTN yukalac, and the catalyst of MEKPO. The manufacturing process uses the hand lay-up technique by varying the fiber volume fractions 3, 6, 9, 12%, and therefore the fiber size passes mesh of 20 and 50. The tensile test uses the ASTM standard D 638 while the impact test uses the ASTM standard D 5942. Fiber volume fraction and fiber size affect the mechanical properties of oil palm fiber reinforced composites. The results of the tensile and impact tests showed that the highest tensile strength and impact toughness were obtained within the composite with a fiber volume fraction of 6% and a mesh of 50, which were 34.74 MPa and 60.21 kJ/m², respectively. In comparison with the tensile strength of the SNI helmet of 33.93 MPa, the oil palm empty fruit bunch fiber can be used as a composite reinforcement for the outer shell of the SNI helmet.
Co-Authors A. Kurniawan Hestiawan, H. Utama, F.P. Utama, M.F. Wardhani, F.