Chain Conveyors Preventive Replacement Schedule: A Case Study

Ibadurrahman, Muhammad Nabil (2025) Chain Conveyors Preventive Replacement Schedule: A Case Study. S1 thesis, Universitas Andalas.

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Abstract

The palm oil industry plays a crucial role in Indonesia’s economy, contributing significantly to national GDP, exports, and employment. To maintain high productivity and meet increasing demand, palm oil processing companies rely heavily on the continuous and efficient operation of their machinery. One critical component in the production line is the chain conveyor system, which transports fresh fruit bunches (FFB) and processed materials throughout the facility. When these systems fail unexpectedly, the resulting unplanned downtime can severely disrupt operations and lead to substantial financial losses. Therefore, implementing an effective maintenance strategy is essential to ensure operational reliability and minimize costs. The objective of this study is to create an optimal preventive replacement schedule for the chain conveyor that balances maintenance costs with machine reliability. Historical breakdown data from 2017 to 2024 were used to analyze the failure patterns of the chain conveyor system. Statistical distribution fitting was performed using the least square curve fitting method in Minitab 19, and the two-parameter lognormal distribution was selected as the most suitable model for Time to Failure (TTF) data. Using the identified distribution parameters, a Python-based cost model was developed to calculate the optimal group replacement interval. The model takes into account component costs, labor costs, and potential financial losses due to downtime. The optimal group replacement interval identified was 15 months for all chain conveyor systems. At this interval, the combined total cost per month using the group replacement strategy is Rp12,566,325,637.25. For comparison, a separate Python program was developed to calculate the cost using the current failure replacement strategy, resulting in a total monthly cost of Rp19,207,042,619.72. These results indicate that implementing the proposed group maintenance strategy can reduce maintenance costs by approximately 34.6% compared to the current approach. The findings demonstrate that a planned, group-based preventive maintenance strategy significantly improves cost efficiency and machine reliability. The model developed in this research provides a practical decision-making tool for maintenance planning in the palm oil industry and can be adapted for similar equipment in other industrial sectors. This preventive approach not only ensures operational continuity but also supports long-term economic sustainability for processing facilities.

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