TY - JOUR
T1 - Allocation of reliability–redundancy and spares inventory under Poisson fleet expansion
AU - Jin, Tongdan
AU - Taboada, Heidi
AU - Espiritu, Jose
AU - Liao, Haitao
N1 - Publisher Copyright:
© 2017 “IISE”.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Installed base
KW - Nonstationary demand
KW - Performance-based contract
KW - Product-service integration
KW - Reliability–inventory optimization
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U2 - 10.1080/24725854.2016.1271963
DO - 10.1080/24725854.2016.1271963
M3 - Article
AN - SCOPUS:85020688369
SN - 2472-5854
VL - 49
SP - 737
EP - 751
JO - IISE Transactions
JF - IISE Transactions
IS - 7
ER -