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Prodi S1 Teknik Industri Gedung At-Tauhid Lantai 3 Universitas Muhammadiyah Surabaya Jalan Sutorejo No 59 Surabaya, Jawa Timur, Indonesia 60113 Email: mine-tech@um-surabaya.ac.id
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Journal of Manufacturing in Industrial Engineering & Technology
Published by Universitas Muhammadiyah Surabaya
ISSN : -     EISSN : 29853516     DOI : https://doi.org/10.30651/mine-tech
Core Subject : Health, Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering Public Health Other
MINE-TECH: Journal of Manufacturing in Industrial Engineering & Technology (E-ISSN: 2985-3516) diterbitkan oleh Universitas Muhammadiyah Surabaya Publishing yang terbit setiap bulan Juni dan Desember. MINE-TECH menyediakan forum penyebaran hasil penelitian baru berupa manufaktur di bidang sistem industri dan teknologi industri. Jurnal ini tertarik pada pendekatan yang memanfaatkan kolaborasi bidang keilmuan lain. Topik yang tercakup di jurnal ini antara lain: Supply Chain & Logistic, Operations Research, Planning & Scheduling, Quality & Reliability, Industrial Food, Pharmacies, and Medic, Halal Industry, Enterprise Engineering, Project Management, Energy & Environmental Management, Decision Analysis, System & Digital Manufacturing, Occupational Safety and Health, Computational Intelligence Service & Healthcare System, Data Mining, Other Relevant Study Topics
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 63 Documents
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Implementasi Machine Learning pada Industri PLN Untuk Klasifikasi Gangguan Listrik Berdasarkan Data DFR Novianti, Triuli; Santosa, Iwan
Journal of Manufacturing in Industrial Engineering & Technology Vol 4 No 2 (2025): Journal of Manufacturing in Industrial Engineering & Technology
Publisher : Universitas Muhammadiyah Surabaya Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/mine-tech.v4i2.28951

Abstract

This study discusses the implementation of the Decision Tree algorithm for classifying electrical fault types based on data obtained from the Disturbance Fault Recorder (DFR) on a 150 kV transmission system. Disturbances in the electric power system can cause power instability and equipment damage if not detected quickly. The data used consists of 12 fault data including the fault current (I Fault), voltage during fault (V Fault), impedance (RΩ), and the cause of the fault. The classification process is carried out to distinguish the types of 1-phase, 2-phase, and 3-phase faults using a supervised learning approach with an entropy-based Decision Tree algorithm as a separation criterion. Model performance evaluation is carried out using the Leave-One-Out Cross Validation (LOOCV) method to maximize the use of small datasets. The test results show an accuracy of 91.67%, with the V Fault and I Fault parameters as the most influential features in the classification process. This study shows that the Decision Tree algorithm is capable of being an effective artificial intelligence-based solution for detecting electrical fault types quickly and interpretively. In the future, research can be developed by increasing the amount of data and conducting comparisons with other algorithms such as Random Forest and Support Vector Machine (SVM) to obtain more optimal results.
Analisis Peningkatan Kualitas Produksi Kemasan Plastik di PT.XYZ dengan Metode Fishbone dan Failure Mode And Effect Analysis (FMEA) Angely Saputro, Catherine Maudy; Hakim, M.Hanifuddin
Journal of Manufacturing in Industrial Engineering & Technology Vol 4 No 2 (2025): Journal of Manufacturing in Industrial Engineering & Technology
Publisher : Universitas Muhammadiyah Surabaya Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/mine-tech.v4i2.29195

Abstract

Penelitian ini dilaksanakan untuk menganalisis permasalahan cacat produk pada botol plastik Liora yang diproduksi oleh PT.XYZ. Permasalahan utama yang ditemukan berupa tingginya jumlah cacat, yang berdampak pada meningkatnya biaya produksi serta menurunnya kualitas dan keandalan produk. Penelitian ini menggunakan dua pendekatan analisis, yaitu diagram sebab-akibat untuk mengidentifikasi faktor penyebab cacat dari aspek manusia, mesin, metode, dan lingkungan, serta analisis mode kegagalan dan efeknya untuk menilai tingkat risiko setiap penyebab cacat melalui penentuan nilai prioritas risiko. Hasil penelitian menunjukkan bahwa cacat dominan terdiri atas botol penyok, mulut botol tidak rata, dan permukaan botol tipis atau bergaris. Nilai risiko tertinggi diperoleh pada kesalahan teknik pengemasan, pengaturan waktu proses yang terlalu cepat, kontaminasi bahan, dan ketidaktepatan posisi komponen mesin. Berdasarkan temuan tersebut, penelitian ini menyimpulkan bahwa perbaikan kualitas dapat dicapai melalui penyesuaian parameter proses, peningkatan kebersihan alat dan area kerja, pemeliharaan mesin yang teratur, serta peningkatan ketelitian operator.
Analisis Keandalan Dan Penjadwalan Pemeliharaan Mesin Line Corrugated Dan Flexo Serta Optimasi Persediaan Sparepart Di Perusahahan Pembuatan Karton Box Nurdianto, Donny; Widiasih, Wiwin
Journal of Manufacturing in Industrial Engineering & Technology Vol 4 No 2 (2025): Journal of Manufacturing in Industrial Engineering & Technology
Publisher : Universitas Muhammadiyah Surabaya Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/mine-tech.v4i2.29245

Abstract

The corrugated box packaging industry plays an essential role in supporting the supply chain of various manufacturing sectors, making machine reliability a critical factor in ensuring production continuity. This study was conducted at a corrugated box manufacturing company in Gresik that operates corrugated line and flexo machines under a three-shift system with high production capacity. Based on downtime data from January 2024 to June 2025, it was found that the failure frequency of machine components was relatively high and had a significant impact on the production flow, particularly because the company still relies on corrective maintenance and does not yet have a structured spare parts control system.The research adopts a quantitative approach, involving calculations of Mean Time To Failure (MTTF), Mean Time To Repair (MTTR), Mean Time Between Failures (MTBF), reliability analysis using Weibull, Normal, and Exponential distributions, as well as determining the Reorder Point (ROP) based on actual demand and procurement lead time. The results show that most machine components exhibit low reliability levels, ranging from 37% to 66%, with failure patterns predominantly occurring in the wear-out phase. Based on these findings, a reliability-based preventive maintenance schedule was developed, allowing maintenance actions to be performed proactively rather than reactively.In addition, the ROP calculation indicates that the required spare parts range from 1 to 9 units depending on the component’s risk level and failure frequency. Overall, the implementation of preventive maintenance and ROP proves effective in improving maintenance performance, reducing downtime, and supporting the smooth operation of corrugated box production.

Page 7 of 7 | Total Record : 63

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