IMPROVING THE SALES OF MAJOR COMPONENT IN BIG MACHINE REMANUFACTURING USING TOOLS MACHINE LEARNING

Abstract

This study focuses on leveraging advanced analytics through machine learning with big data utilization to create additional revenue streams in the big machine component remanufacturing business at PT XYZ. The main issue identified is a 26% decline in revenue from big machine component remanufacturing compared to 2023. To address this, this study aims to increase revenue of at least IDR 5 billion/month from major component remanufacturing by leveraging big data using Machine Learning. The research methodology adopted the DMAIC framework, which revealed that the failure to achieve sales targets was not due to weak demand, but rather the inability of the current system to capture opportunities. For the result, there has been an additional in average revenue of approximately 12 billion rupiah per month from major component remanufacturing, far exceeding the minimum target of 5 billion rupiah per month. This success is supported by a shift in transaction patterns from reactive to proactive. With this new system, ASC can educate customers about potential unit failures early on and prepare components well before the unit breaks down, ultimately shortening the downtime of damaged units and helping customers implement their production plans.