Sustainment constitutes 70% or more of the total life-cycle cost of many safety-, mission- and infrastructure-critical systems. Prediction and control of the life-cycle cost is an essential part of all sustainment contracts. For many types of systems, availability is the most critical factor in determining the total life-cycle cost of the system. To address this, availability-based contracts have been introduced into the governmental and non-governmental acquisitions space (e.g., energy, defense, transportation, and healthcare).However, the development, implementation, and impact of availability requirements within contracts is not well understood.

This dissertation develops a decision support model based on contract theory, formal modeling and stochastic optimization for availability-based contract design. By adoption and extension of the “availability payment” concept introduced for civil infrastructure Public-Private Partnerships (PPPs) and pricing for Performance-Based Logistics (PBL) contracts, this dissertation develops requirements that maximize the outcome of contracts for both parties.

Under the civil infrastructure “availability payment” PPP, once the asset is available for use, the private sector begins receiving a periodical payment for the contracted number of years based on meeting performance requirements. This approach has been applied to highways, bridges, etc. The challenge is to determine the most effective requirements, metrics and payment model that protects the public interest, (i.e., does not overpay the private sector) but also minimizes that risk that the asset will become unsupported. This dissertation focuses on availability as the key required outcome for mission-critical systems and provides a methodology for finding the optimum requirements and optimum payment parameters, and introduces new metrics into availability-based contract structures.

In a product-service oriented environment, formal modeling of contracts (for both the customer and the contractor) will be necessary for pricing, negotiations, and transparency. Conventional methods for simulating a system through its life cycle do not include the effect of the relationship between the contractor and customer. This dissertation integrates engineering models with the incentive structure using a game theoretic simulation, affine controller design and stochastic optimization. The model has been used to explore the optimum availability assessment window (i.e., the length of time over which availability must be assessed) for an availability-based contract.