(245e) Stochastic Financial Analysis in Product Design

Product and process design problems generally require utilization of parameters that are not known with absolute certainty, whether they are physical property parameters, chemical conversions and selectivities, anticipated costs of raw materials, or other design criteria. While most chemical engineering textbooks assume financial analysis is deterministic, stochastic methods are more appropriate and easy to apply.

The capstone course in Chemical Product Design at Columbia University has been teaching undergraduate students to apply probability theory when performing financial analyses. The instruction has included guidance for choosing appropriate probability density functions, and two methodologies for performing calculations with probability density functions, namely the method of moments and Monte Carlo simulation. Students have also been given guidelines as to when each technique is more appropriate. As a result, students are able to calculate financial decision criteria such as breakeven sales volume and net present value to a specified confidence level.

While these techniques have been taught in a context of product design, they are equally appropriate for process design.