# Life Cycle Cost Estimation and Analysis of Transformers Based on Failure Rate
## 3 Results
### Life Cycle Cost Fitting  
According to LCC theory, in order to clarify the cost types of the entire life cycle of assets, and achieve quantitative analysis and application of production costs, LCC calculation divides costs into five stages for calculation: initial investment, operation and maintenance, failure, and recovery disposal costs. The measurement of equipment life cycle cost is a comprehensive issue that needs to consider multiple stages such as equipment procurement, operation, maintenance, and scrapping. It takes a long time (usually 20-30 years) to complete the collection of life cycle costs, and the data that companies can effectively collect is generally within 10 years, which cannot provide detailed data on equipment procurement, operation, maintenance, and recycling throughout the entire life cycle. In the absence of complete and reliable historical data, it is difficult to accurately evaluate past costs and predict future costs. In the measurement of full life cycle costs, it is necessary to quantify various costs, including direct and indirect costs. The incompleteness, inaccuracy, and inconsistency of historical data directly affect the accuracy of the evaluation, modeling, and measurement of the entire life cycle cost. As can be seen from the above, establishing a complete cost measurement model for the entire life cycle of equipment under nonsound information, and obtaining effective and reliable LCC fitting curves is one of the difficulties in this study. As shown in Figure 4, the research route of this study includes organizing data, analyzing data, fitting data, and predicting costs. Based on detailed data provided by a northern company for 2016-2021, we analyzed the overall trend and possible patterns of equipment operating, maintenance and failure costs over time. Based on the characteristics and trends of the data, we selected an appropriate fitting function to fit the functions of equipment operating, maintenance, and failure costs over time, in order to measure the life cycle cost of the transformer. Firstly, we processed the data provided by a northern power company from 2016 to 2021 to ensure the reliability and accuracy of subsequent data analysis. (1) Integrity check: we checked for any missing years or data points to ensure that the dataset is complete. (2) Data cleaning: we cleaned up any outliers or erroneous data in the data, including duplicate records, outliers, or data points that did not match the actual situation. (3) Unit standardization: we ensured that all cost data adopted unified units and measurement standards. (4) Data validation: we compared the data with other reliable data sources or related records to verify the accuracy of the data. (5) Time range confirmation: we ensured that the time range of the data matched the required analysis period. By following the above steps, we ensured the accuracy of the collected equipment operation and maintenance cost data, and laid a solid foundation for subsequent analysis and fitting work. Subsequently, we plotted the corresponding distribution map of the transformer failure rate and the trend chart of operating costs, maintenance costs, and failure costs (C2 + C3 + C4) over time by estimating the transformer failure rate. This helps to observe the overall trend and possible patterns of the data, thereby determining the maintenance interval and various maintenance costs of transformers. And, based on the characteristics and trends of the data, we selected an appropriate fitting function and further calculated the corresponding transformer life cost. Then, we used the programming language Python to perform fitting operations, select the most suitable parameters, and construct a cost fitting model. Finally, we used the fitting model to predict the operating costs, maintenance costs, and failure costs (C2, C3, C4) of the entire life cycle of the equipment. Based on the equation of the model and the expected service life of the equipment, we calculated the estimated values of C2, C3 and C4.