IMPROVING HEAVY EQUIPMENT DUMP TRUCK HD785-7 FUEL RATIO BY USING EXPLORATORY DATA ANALYSIS METHOD

Abstract

This thesis investigates the improvement of fuel efficiency for Komatsu HD785-7 dump truck at PT XYZ by employing Exploratory Data Analysis (EDA) method. The objective is to reduce the fuel ratio from 0.17 to 0.15, addressing operational inefficiencies that have been identified as a significant issue. The research utilizes the DMAIC framework, to guide the analysis and implementation of solutions. Data collection encompasses three main categories: manpower, equipment condition, and operational data, which analysed to identify patterns and root causes. The study employs statistical methods, including SHAP and PDP, to interpret data and assess the impact of different variables on fuel consumption. The results indicate that improvements in operator, equipment, and operational strategies can enhance fuel efficiency. The implementation of a cloud-based data architecture using Google Cloud Platform. The quantitative results for selected dump trucks showed 10% higher payload per cycle, 37% higher refuelling quantity, and a 23% reduction in fuel ratio. This led to a conservative profit increase for PT XYZ of over IDR 1.2 billion per month for four units. This research successfully demonstrates how a data-driven EDA approach combined with the DMAIC framework can optimize fuel consumption in heavy-duty dump truck, delivering substantial operational and financial benefits.