For a repairable k-out-of- n : G system consisting of line-replaceable units, its operational availability depends on component reliability, its redundancy level, and spare parts availability. As a result, it is important to consider redundancy allocation and spare parts provisioning simultaneously in maximizing the system’s operational availability. In prior studies, however, these important aspects are often handled separately in the areas of reliability engineering and spare parts logistics. In this paper, we study a collection of operational availability maximization problems, in which the component redundancy and the spares stocking quantities are to be determined simultaneously under economic and physical constraints. To solve this type of problem, continuous-time Markov chain models are developed first for a single repairable k-out-of- n : G system under different shut-off rules, and some important properties of the corresponding operational availability and spare parts availability are derived. Then, we extend the models to series systems consisting of multiple repairable k-out-of- n : G subsystems. The related optimization problems are reformulated as binary integer linear programs and solved using a branch-and-bound method. Numerical examples, including a real-world application of automatic test equipment, are presented to illustrate this integrated product-service solution and to offer valuable managerial insights. Automatic Test Equipment Continuous Operation Continuous-Time Markov Chain First-Come, First Served Multi-Echelon Technique for Recoverable Item Control Mean Down Time of the System Mean Time Between Failures of the System Original Equipment Manufacturer Optimal Operational Availability Optimal Parts Availability Performance-Based Contracting Required Operational Availability Required Parts Availability Suspended Animation number of subsystems in a series system number of suspended components in subsystem l number of components in subsystem l (redundancy level) base-stock level for subsystem l failure rate of the component in subsystem l replenishment rate of spare parts for subsystem l repair-by-replacement rate for subsystem l if a spare part is available steady-state probability for the case with i non-failed components and j on-hand spare parts steady-state probability for cases with i non-failed components steady-state probability for cases with j on-hand spare parts availability of the overall system availability of subsystem l availability of spare parts for subsystem l required parts availability level of subsystem l holding cost per unit time of a spare part for subsystem l operation cost per unit time of a component for subsystem l expected total inventory cost per unit time for subsystem l expected total operation cost per unit time for subsystem l inventory and operation budget per unit time for the overall system incomplete Gamma function ∫ z ∞ t α - 1 e - t dt 
Maximizing system availability through joint decision on component redundancy and spares inventory