This article proposes an integrated product-service model to ensure the system availability by concurrently allocating reliability, redundancy, and spare parts for a variable fleet. In the literature, reliability and inventory allocation models are often developed based on a static installed base. The decision becomes really challenging during new product introduction, as the demand for spare parts is nonstationary due to the fleet expansion. Under the system availability criteria, our objective is to minimize the fleet costs associated with design, manufacturing, and after-sales support. We tackle this reliability–inventory allocation problem in two steps. First, to accommodate the fleet growth effects, the nonstationary spare parts demand stream is modeled as a sum of randomly delayed renewal processes. When the component’s failure time is exponential, the mean and variance of the lead time inventory demand are explicitly derived. Second, we propose an adaptive base stock policy against the time-varying parts demand rate. A bisection search combined with metaheuristics is used to find the optimal solution. Numerical examples show that spare parts inventory results in a lower fleet cost under short-term performance-based contracts, whereas reliability–redundancy is preferred for long-term service programs.
- Installed base
- Nonstationary demand
- Performance-based contract
- Product-service integration
- Reliability–inventory optimization
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering