A FRAMEWORK FOR ACHIEVING LIFECYCLE VALUE IN AEROSPACE PRODUCT DEVELOPMENT

Creation of lifecycle value - a balance of performance with cost and other attributes - represents a challenge for the development of aerospace products in the twenty-first century. This paper examines the concept of lifecycle value that stems from existing approaches of value management and analysis, lifecycle costing, and systems engineering. To ascertain common characteristics of lifecycle value creation, case studies were done for four aircraft programs: F/A- 18E/F, JAS 39 Gripen, F-16C/D, and B-777. A lifecycle value creation framework is introduced, comprised of three phases: value identification, value proposition, value delivery. Based upon observed practices in the four case studies, six value creation attributes were identified. Capability maturity models for the six attributes and three value creation phases are presented. The resulting framework represents a starting point for programs seeking to create lifecycle value for aerospace products.

A Reinforcement-Learning Approach to Power Management

We describe an adaptive, mid-level approach to the wireless device power management problem. Our approach is based on reinforcement learning, a machine learning framework for autonomous agents. We describe how our framework can be applied to the power management problem in both infrastructure and ad~hoc wireless networks. From this thesis we conclude that mid-level power management policies can outperform low-level policies and are more convenient to implement than high-level policies. We also conclude that power management policies need to adapt to the user and network, and that a mid-level power management framework based on reinforcement learning fulfills these requirements.

Risk Aversion in Inventory Management

Traditional inventory models focus on risk-neutral decision makers, i.e., characterizing replenishment strategies that maximize expected total profit, or equivalently, minimize expected total cost over a planning horizon. In this paper, we propose a framework for incorporating risk aversion in multi-period inventory models as well as multi-period models that coordinate inventory and pricing strategies. In each case, we characterize the optimal policy for various measures of risk that have been commonly used in the finance literature. In particular, we show that the structure of the optimal policy for a decision maker with exponential utility functions is almost identical to the structure of the optimal risk-neutral inventory (and pricing) policies. Computational results demonstrate the importance of this approach not only to risk-averse decision makers, but also to risk-neutral decision makers with limited information on the demand distribution.