Abstract:
This capstone project is performed in partnership with "Alstom Kazakhstan". Alstom is the leading international company operating in rail transport markets. "Alstom Kazakhstan" performs both production and maintenance of locomotives. This capstone project aims to develop life-cycle costing (LCC) model for corrective maintenance of locomotives. This LCC model shall process and combine different input factors, such as the WBS structure of locomotives spare parts, purchase prices of spare parts, relevant labour hours and costs needed for repair and replacement operations, and other data. The LCC model shall calculate specific values and metrics required for budgeting and managerial decision making, such as expected total costs for corrective maintenance, breakdown of costs by category, expected labour hours, and others. The model shall also contain dashboards and visual reports to facilitate managerial decision making. The company has previously developed an LCC model based on Microsoft Excel, however, this existing model has several drawbacks. In the capstone project, we analyze the existing model, identify areas for improvement, redesign the LCC model concept considering current leading industry practices, and reimplement the LCC model from scratch using Power BI software. We have used Microsoft Power BI software in our technical implementation and its embedded languages, including M (for data processing) and DAX (for business logic and calculations). Furthermore, in our model, we have implemented several key improvements, which were not present in the original (legacy) LCC model from the company: (i) incorporation of concepts of financial modelling, such as time value of money, and (ii) incorporation of inventory management calculations, such as calculation of Economic Order Quantity (EOQ). We have also developed dashboards for the end-users and implemented several additional improvements. The new LCC model developed in this capstone project offers several advantages for the company, such as: (i) it has better data structure based on the relational data model, (ii) it is more maintainable and updatable, (iii) it is more understandable for the users, (iv) it is more modern (being based on more modern software like Microsoft Power BI), and (v) it has better computational performance. The methodology and toolset used in this capstone project can be relevant for other research problems in engineering and business modelling.