Undercarriage management is a critical concern for heavy equipment owners that often can account for over half of the operating cost of a piece of machinery. Understanding the most economical time to stop a machine for undercarriage maintenance is critical in the management of the undercarriage system and for optimizing profitability for the equipment owner. There has been much laboratory research performed on steel track undercarriage system wear found on dozers and track type loaders, however there has been little formal research to determine the wear patterns based on geographic location. This research analyzed the entire population of track type heavy construction equipment within a construction equipment territory to determine if there are differences in the undercarriage wear rates based on geographic location. There are 5 sub-territories that are researched to determine if the wear rates are different between these 5 geographic locations. Two of these locations are in the coastal plains region of North Carolina and three are in what is known as piedmont area of the state. This research is important because the results will assist the machine owner in maximizing the life of the undercarriage system and will result in better machine maintenance recommendations for the equipment owners. The researchers tested two hypotheses, these are: (a) the median wear out rates are the same between all geographic store locations and, (b) the median wear out rate is the same between the regions. Both null hypotheses in this study were rejected indicating there are differences in the undercarriage wear rates.
PurposeReducing 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.Design/methodology/approachThis 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.FindingsThe study found that only sand percentage has a significant impact on the wear rate. Consequently, a regression model is developed.Research limitations/implicationsThe 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.Originality/valueThis 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.
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