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Perencanaan Penggantian Komponen Generator Listrik Daya 2,5 kW Reza Nandhika Putra Wijaya; Syamsul Hadi; Mochammad Reza Maulana Ramadhon; Bintang Erlangga; Yohan Nur Azizi; Hallan Shandria Rifqi
Manufaktur: Publikasi Sub Rumpun Ilmu Keteknikan Industri Vol. 3 No. 4 (2025): Manufaktur : Publikasi Sub Rumpun Ilmu Keteknikan Industri
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/manufaktur.v3i4.1274

Abstract

The problem with a 4-stroke gasoline engine-driven electric generator is a decrease in tool performance due to wear on important components for the stator, cooling fan, air filter, oil filter, and gasket. The purpose of component replacement planning is to obtain replacement costs, maintenance schedules in 2027, and the ratio of maintenance costs to profits. The component replacement planning method includes collecting maintenance data from previous years, applying the inspection-replace-repair-overhaul (IRRO) method, assessing component conditions, predicting component lifespan, predicting labor costs, predicting supporting equipment to be used in maintenance, predicting spare part replacement times, predicting maintenance costs in 2027, and calculating the ratio of maintenance costs to profits. The results of the replacement planning obtained maintenance costs in 2027 amounting to IDR 570,007,- with an estimated electric generator rental rate of IDR 30,000,-/hour which has the potential to be rented for 128 hours/year, a profit of IDR 3,840,000,- was obtained, and the ratio of maintenance costs to profits was 14.84% which implies that a 2.5 kW electric generator that uses gasoline-pertalite fuel of around 1.5 liters/hour at maximum power is still suitable for use in the next few years and has the potential to generate profits.
RANCANG BANGUN SISTEM MONITORING KENDARAAN MATERIAL BERBASIS IOT DENGAN BOX TAHAN AIR UNTUK MENDUKUNG PROSES PRODUKSI MESIN PEMECAH BATU Yohan Nur Azizi; Zakiyah Amalia
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 03 (2026): Volume 11 No. 03, September 2026 Processed
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i03.61881

Abstract

The monitoring of material transport vehicles in stone crusher production is commonly performed manually, resulting in delays in information delivery, inaccuracies in vehicle records, and increased production downtime caused by late material supply. This study aimed to design and develop an Internet of Things (IoT)-based material vehicle monitoring system using an ESP32-CAM to support the stone crusher production process. The proposed system integrates two ultrasonic sensors to detect the direction of vehicle movement, an ESP32-CAM to capture vehicle images, a DHT11 sensor to monitor the temperature inside the enclosure, and the Telegram application to deliver real-time notifications and monitoring information. The research consisted of hardware and software design, system implementation, functional testing, and statistical analysis. Experimental data were analyzed using descriptive statistics and an Independent Samples t-test after satisfying the assumptions of normality and homogeneity to evaluate the effect of Wi-Fi network speed on data transmission time. The results showed that the developed system successfully detected incoming and outgoing vehicles with a 100% detection accuracy and automatically transmitted vehicle images and information to Telegram. The average data transmission time was 3.0139 s using a 10 Mbps Wi-Fi network and 1.7130 s using a 50 Mbps Wi-Fi network. Statistical analysis indicated that Wi-Fi network speed had a significant effect on data transmission time (p < 0.05). Furthermore, the implementation of the proposed system reduced production downtime caused by delayed material supply from 60 min to 10 min per day, representing an 83.33% reduction. These findings demonstrate that the developed IoT-based monitoring system improves vehicle recording accuracy, accelerates information delivery, and supports more efficient production operations in the stone crusher industry.