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Reducing wear of undercarriage track propulsion systems used in heavy construction equipment decreases the maintenance costs and increases the equipment's life. Therefore, understanding key factors that affect the wear rate is critical. This study is an attempt to predict undercarriage wear.

This research analyzes a sample of track-type dozers in the eastern half of North Carolina (NC), USA. Sand percentage in the soil, precipitation level, temperature, machine model, machine weight, elevation above sea level and work type code are considered as factors influencing the wear rate. Data are comprised of 353 machines. Machine model and work code data are categorical. Sand percentage, elevation, machine weight, average temperature and average precipitation are continuous. ANOVA is used to test the hypothesis.

The study found that only sand percentage has a significant impact on the wear rate. Consequently, a regression model is developed.

The regression model can be used to predict undercarriage wear and bushing life in soils with different sand percentages. This is demonstrated using a hypothetical scenario for a construction company.

This work is useful in managing maintenance intervals of undercarriage tracks and in bidding construction jobs while predicting machine operating expense for each specific job site soil makeup.