Engineering Economics:Risk and Uncertainty Analysis

      This part focuses on the uncertainty commonly encountered in the implementation of engineering projects and systematically presents the basic concepts, analytical framework, and main methods of risk and uncertainty analysis in engineering economics. From project initiation and design to construction and operation, engineering projects are often influenced by various uncertain factors such as market demand fluctuations, price changes, technological conditions, policy environments, and management performance. These factors can directly or indirectly affect the economic outcomes of a project. Therefore, introducing risk and uncertainty analysis on the basis of traditional deterministic economic evaluation is of great significance for improving the scientific rigor and reliability of engineering decision-making.

       This part emphasizes three methods that are most widely used in engineering economic analysis. The first is break-even analysis, which examines the quantitative relationship among costs, revenues, and output levels to determine the break-even point of a project. Through this analysis, the project’s ability to withstand risk and its margin of safety under normal operating conditions can be assessed. Due to its intuitive nature and ease of application, break-even analysis is commonly used in the preliminary stage of feasibility studies. The second method is sensitivity analysis, which focuses on key project parameters such as initial investment, operating costs, product prices, and production volumes, and investigates how changes in these factors affect economic evaluation indicators. By comparing the degree of sensitivity of different variables, decision-makers can identify the most critical risk factors and provide a basis for targeted risk control and project optimization. The third method is probability analysis, which introduces random variables and probability distributions to quantitatively describe the uncertainty of project economic outcomes. This method enables decision-makers to evaluate project returns and risks from a probabilistic perspective and is particularly suitable for projects characterized by high uncertainty and relatively sufficient data.

      Through systematic learning of these three methods, learners will be able to analyze project risks from multiple perspectives, understand the relationship and differences between deterministic and uncertainty-based analyses, and gradually develop comprehensive capabilities for engineering economic evaluation and decision-making under complex and uncertain conditions.