Financial analysis in multidisciplinary design optimization

Abstract

MDO is moving beyond the small group of NASA and Aerospace companies and is increasingly being adopted by organizations around the world. With MDO, we can optimize across multiple disciplines and find the ideal design which maximizes benefit to the company and society. Given the complexity of working with multiple disciplines and stakeholders, it is important to have a single metric which teams and organizations can use to choose the best design. Since financial metrics play a dominant role in the decision-making process, we can use them to choose the best design for the company. In the thesis, we created a framework for doing financial analysis in MDO. We applied the framework to the baseplate, a component used within the excavator pump, and optimized across three different disciplines of cost, natural frequency and temperature to find the baseplate design with the highest sales potential.

We focused on sales as it is the most important financial metric for the product, but a similar framework can be used for maximizing profit, NPV, IRR or any other financial metric. We used two approaches for finding the best design for the company. In the first approach, we found designs which minimized cost and temperature, while increasing the natural frequency. We then converted the cost and temperature data into sales and chose the design with most sales. In the second approach, we only set one objective of maximizing sales and chose the design with the highest sales. In both the approaches we were able to significantly increase sales. We would recommend approach 1 as we get higher sales with the method, and because of limitations within the optimization software OptiSLang in regards to implementing approach 2. Approach 2 might become the better option in the coming years as MDO software, including OptiSLang, is in the early stage and might significantly improve.

Approach 2 also has the advantage of MDO teams only setting one objective, helping establish consistency and uniformity in MDO implementation. We believe MDO has a lot of potential. Similar to CAD, it is an extremely powerful tool. Some of the challenges to successful implementation were: computational resources, high quality and reliable financial data and early stage MDO software. Organizations which implement MDO will create better products which maximize savings and financial benefit.