ANALISIS ALAT MEKANIS PADA TAMBANG TERBUKA DENGAN PENDEKATAN ANTRIAN UNTUK MEMENUHI TARGET PRODUKSI PADA PT. SEMEN TONASA
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ANALISIS ALAT MEKANIS PADA TAMBANG TERBUKA DENGAN PENDEKATAN ANTRIAN UNTUK MEMENUHI TARGET PRODUKSI PADA PT. SEMEN TONASA

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Introduction

Analisis alat mekanis pada tambang terbuka dengan pendekatan antrian untuk memenuhi target produksi pada pt. Semen tonasa. Analisis alat mekanis (excavator & dump truck) pada tambang terbuka PT. Semen Tonasa dengan pendekatan antrian untuk optimasi & penuhi target produksi batu gamping.

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Abstract

Industri pertambangan dengan sistem tambang terbuka  (open Pit), peralatan mekanis sangat penting dalam memenuhi target produksi.   Penelitian ini bertujuan untuk mengetahui nilai produksi dan kinerja alat mekanis yang optimal. Peningkatkan nilai    produksi    perlu  perhitungan   mengenai optimasi excavator dan dump truck dengan pendekatan   antrian. Jumlah   dump   truck  yang  digunakan  dalam proses penambangan batu gamping  pada  2  lokasi   tambang  PT   Semen Tonasa   pada Blok 5 selatan   dengan  1  unit excavator dan 5  unit dump truck serta Blok 9 selatan dengan 1 unit excavator dan 5 unit dump truck.  Berdasarakan hasil  perhitungan produksi dump truck dengan   pendekatan   antrian dan  produksi Excavator Kobelco 480 378,77 ton/jam, sedangkan 5  unit dump  truck PC 200 sebesar 3.659,24 ton/jam. Pada Blok 9 selatan menggunakan 1 unit excavator Doozan 500 LCV sebesar 468,49 ton/jam, sedangkan 5 unit dump truck PC 200 sebesar 4.618,03 ton/jam. Produksi alat mekanis tersebut pada masing - masing blok sudah memenuhi target produksi sebesar 312,5 ton/jam.


Review

This study, titled "ANALISIS ALAT MEKANIS PADA TAMBANG TERBUKA DENGAN PENDEKATAN ANTRIAN UNTUK MEMENUHI TARGET PRODUKSI PADA PT. SEMEN TONASA," addresses a highly relevant operational challenge in open-pit mining: optimizing mechanical equipment to achieve production targets. The authors utilize a queuing theory approach to analyze the performance of excavators and dump trucks, aiming to determine optimal production values and equipment performance. This quantitative approach to a practical industry problem, focusing on a specific company (PT. Semen Tonasa) and its limestone mining operations, provides valuable insights into the efficiency of current mining processes. The methodology centers on analyzing the production of mechanical equipment across two specific mining blocks: Blok 5 selatan and Blok 9 selatan. In each block, the configuration studied involves one excavator and five dump trucks. The abstract provides specific production figures: for Blok 5 selatan, the Kobelco 480 excavator achieved 378.77 tons/hour, while the five PC 200 dump trucks achieved 3,659.24 tons/hour. Similarly, for Blok 9 selatan, the Doozan 500 LCV excavator produced 468.49 tons/hour, and the five PC 200 dump trucks produced 4,618.03 tons/hour. A crucial finding is that the mechanical equipment's production in both blocks successfully met the target of 312.5 tons/hour, validating the effectiveness of the current operational setup for production volume. While the study successfully demonstrates that current production targets are met using a queuing theory approach, the abstract could benefit from further detail regarding the "optimization" aspect. It is stated that the research aims "mengetahui nilai produksi dan kinerja alat mekanis yang optimal," yet the presented results primarily confirm that the *current* configuration meets the target. It is not explicitly clear if the current 1 excavator to 5 dump truck ratio is indeed the *optimal* configuration derived from the queuing model, or merely a sufficiently productive one. Future iterations or a more comprehensive write-up would ideally elaborate on the specifics of the queuing model parameters, such as average waiting times, equipment utilization rates, and how different fleet configurations were evaluated to arrive at "optimal" performance beyond simply meeting the production target. This would significantly enhance the paper's contribution to operational efficiency and resource allocation in mining.


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