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All Journal Rekayasa Mesin JMPM (Jurnal Material dan Proses Manufaktur)
Bambang Riyanta, Bambang
Universitas Muhammadiyah Yogyakarta
Engineering Mechanical Engineering

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Ekstraksi Parameter Statistik Domain Waktu dan Domain Frekuensi untuk Mendeteksi Kavitasi pada Pompa Sentrifugal Berbasis Principal Component Analysis (PCA) Kamiel, Berli Paripurna; Prastomo, Niko; Riyanta, Bambang
Jurnal Rekayasa Mesin Vol 10, No 2 (2019)
Publisher : Jurusan Teknik Mesin, Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jrm.2019.010.02.8

Abstract

Cavitation phenomenon frequently occurs on the centrifugal pump which may decrease its performance. It may cause a catastrophic failure which leads to a total breakdown of the piping system if the presence of cavitation is not immediately detected and solved. Recently, the popular method used to detect cavitation is based on pattern recognition. The use of pattern recognition technique requires statistical features which are used as input for building the classifier. The extraction of statistical features is usually taken from the vibration signal which consists of time domain and frequency domain. Previous research tends to use the statistical features extracted from the time domain or the frequency domain solely. There is a research gap that can be explored by combining statistical features extracted from both time domain and frequency domain. In this study, Principal Component Analysis (PCA) is used as a feature’s selection and fault classification. PCA linearly transforms statistical features from the original coordinate system into a new coordinate system called principal components (PCs). The first few PCs are a set of selected features which can be used as a classifier. The classifier evaluates and classifies the new set of vibration data then decides whether it falls into normal condition or cavitation category. The vibration signal is taken from the cavitation test-rig under normal condition by opening the valve, level 1 cavitation by opening 75% of valve, level 2 by 50%, and level 3 by 25%. The data is extracted into 7 statistical features from the time domain and 5 from the frequency domain.  Five hundred sets of vibration data are recorded using an accelerometer which was then divided into 400 set for training and 100 set for testing. The study shows that the classifier using statistical features taken from the time domain and frequency domain gives promising results where the clustering effect between normal and cavitation condition is clearly observed.
Pengaruh Temperatur dan Arus Listrik Proses Pelapisan Krom Pada Plastik ABS Dengan Metode Elektroplating Rahman, Muhammad Budi Nur; Riyanta, Bambang; Agusman, Delvis
JMPM (Jurnal Material dan Proses Manufaktur) Vol 4, No 1 (2020): JUNI 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jmpm.v4i1.9379

Abstract

Elektroplating pada plastik berfungsi menambah sifat konduktif dan dekoratif. Plastik ABS memiliki tingkat keberhasilan untuk dilakukan elektroplating karena dapat dietsa secara kimiawi. Tujuan penelitian ini adalah mengetahui pengaruh temperatur dan arus listrik proses elektroplating krom terhadap ketebalan lapisan dan kekasaran permukaan. Proses elektroplating pada plastik ABS diawali dengan proses etching, proses metalisasi palladium, dan electrolessplating nikel. Variasi arus proses elektroplating krom yang dilakukan adalah 11 A, 16 A, dan 22 A sedangkan variasi temperatur adalah 55oC, 65oC, dan 75oC. Pengamatan hasil pelapisan meliputi pengamatan struktur mikro menggunakan mikroskop optic dan SEM, ketebalan lapisan, kekasaran permukaan dan kekerasan permukaan. Semakin besar arus proses elektroplating dapat meningkatkan kekasaran permukaan dan ketebalan lapisan. Proses elektroplating dengan arus 22 A menghasilkan kekasaran permukaan 0,493 µm dan ketebalan lapisan sebesar 60,61 µm. Peningkatan temperatur proses elektroplating sampai temperatur 75oC akan menurunkan nilai kekasaran permukaan sebesar 0,40 μm dan ketebalan lapisan sebesar 21,53 μm. Variasi arus dan temperatur proses elektroplating tidak banyak berpengaruh terhadap nilai kekerasan yang berkisar antara 111 - 114 shore-D. Electroplating on plastic serves to add conductive and decorative properties. ABS plastic has a high degree of success for electroplating because it can be chemically etched. The purpose of this study was to determine the effect of temperature and electric current on the chrome electroplating process on the thickness of the layer and surface roughness. The electroplating process on ABS plastic begins with the etching process, the palladium metallization process, and the nickel electroless-plating. The variation of the chromium electroplating process current is 11 A, 16 A, and 22 A while the temperature variation is 55oC, 65oC, and 75oC. Observation of coating results includes observation of microstructure using optical microscopy and SEM, layer thickness, surface roughness and surface hardness. Coating research results include observations of microstructure and SEM, layer thickness, surface roughness and surface hardness. The greater the current electroplating process can increase surface roughness, thickness of the layer. Electroplating process with a current of 22 A produces a surface roughness of 0.493 µm and a layer thickness of 60.61 µm. Increasing the temperature of the electroplating process to a temperature of 75oC will reduce the surface roughness value by 0.40 μm and the thickness of the layer by 21.53 μm. The variation of current and temperature of the electroplating process does not significantly affect the hardness values ranging from 111 - 114 shore-D. 
Perancangan dan Simulasi Trainer Human Machine Interface (HMI) untuk media pembelajaran berbasis CX Designer PLC Yudha, Fitroh Anugrah Kusuma; Riyanta, Bambang
JMPM (Jurnal Material dan Proses Manufaktur) Vol 4, No 2 (2020): DESEMBER 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jmpm.v4i2.10607

Abstract

Penelitian ini bertujuan untuk membuat rancangan media pembelajaran pada mata kuliah Programmable Logic Controller (PLC) berupa trainer Human Machine Interface (HMI) berbasis CX Designer yang terintergrasi dengan CX-Programmer. Desain HMI yang tepat akan membuat pengujian program lebih mudah dan efisien. Sebagai media pembelajaran HMI memberikan efektifitas informasi yang dibutuhkan, sehingga perencanaan dapat dilakukan dengan efisiensi yang maksimal. Metode penelitian yang digunakan adalah metode eksperimental dan pembuatan rancangan produk berupa trainer untuk penguji program oleh mahasiswa atau operator. Dapat disimpulkan hasil dari penelitian ini bahwa penggunaan simulasi HMI berbasis CX Disigner dapat digunakan untuk memahami logika rangkaian suatu program dengan sangat mudah dan cepat untuk melatih ketrampilan pemograman PLC.
Deteksi Cacat Roda Gigi pada Sistem Transmisi Fan Industri Menggunakan Support Vector Machine Kamiel, Berli Paripurna; Wicaksono, Kurniawan Budi; Riyanta, Bambang
Jurnal Rekayasa Mesin Vol 11, No 3 (2020)
Publisher : Jurusan Teknik Mesin, Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jrm.2020.011.03.17

Abstract

A fan is a mechanical device that produces airflow in a particular area. To achieve sufficient torque and speed, an industrial fan often uses a gear transmission. During its operation, the gears may experience damage. The vibration spectrum is a common method to detect a faulty gear. However, the spectrum often produces a graph that is hard to understand. Moreover, the spectrum sometimes fails to show a clear and high amplitude for small gear faults. The study aims to detect faulty gear based on a classification approach using the Support Vector Machine (SVM) algorithm. It is one of the most robust and accurate algorithms among the other classification algorithms especially for cases with a large number of features. The SVM needs statistical parameters as predictors but the decision to choose the parameters seems arbitrary. This research proposes a simple method to select the parameters using a combination of visual inspection and relief feature algorithm. Twelve statistical parameters are introduced and evaluated for potential input for SVM. The statistical parameters are extracted from the time domain of the vibration signal. The experiment is carried out on an industrial fan test rig and introduces 3 carbon steel spur gear conditions i.e. normal, fault 1, fault 2, and records vibration signal using an accelerometer located near the gear transmission system.  The SVM classifier is built using the RBF kernel function and the classification is carried out by one vs one and one vs all methods. The result shows that classification accuracy for both methods achieves 100%.
Co-Authors A.A. Ketut Agung Cahyawan W Delvis Agusman Kamiel, Berli Paripurna Prastomo, Niko Rahman, Muhammad Budi Nur Wicaksono, Kurniawan Budi Yudha, Fitroh Anugrah Kusuma