Product Performance Evolution Prediction by Lotka-Volterra Equations Conference Paper uri icon

abstract

  • Copyright © 2017 ASME. During the development planning of a new product, designers rely on the prediction of the product performance to make business investments and frame design strategy. The Scurve model is commonly used for this purpose, but it has several drawbacks. A significant volume of product performance data doesn't fit well with an S-curve. An S-curve model is also not capable of showing what factors shape the future performance of a product and how designers can change it. In this paper, Lotka-Volterra equations, which subsume both the logistic S-curve model and Moore's Law, are used to describe the interaction between a product (system technology) and the components and elements (component technologies) that are combined to form the product. The equations are simplified by a relationship table and a maturation evaluation process as a two-step simplification. The historical performance data of the system and its components are fitted by the simplified Lotka-Volterra equations. The methods developed here allow designers to predict the performances of a product and its components quantitatively by the simplified Lotka- Volterra equations. The methods also shed light on the extent of performance impact from a specific module on a product, which is valuable for identifying the key features of a product and thus making outsourcing decisions. Smart phones are used as an example to demonstrate the two-step simplification. The data fitting method is validated by the time history performance data of airliners and turbofan aero-engines.

author list (cited authors)

  • Zhang, G., McAdams, D. A., Darani, M. M., & Shankar, V.

citation count

  • 0

publication date

  • August 2017