Design and maintenance for the data storage system considering system rebuilding process

• Published in: Reliability engineering & system safety Vol. 191; p. 106576
• Main Authors: Zhu, Xiaoyan, Wang, Jun, Yuan, Tao
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.11.2019; Elsevier BV
• Subjects: Data redundancy; Data storage; Data storage system; Design; Failure modes; k-out-of-n:F system; Maintenance management; Optimization; Preventive maintenance; Rebuilding; Redundancy; Reliability engineering; Schedules; Sensitivity analysis; Storage area networks; Storage systems; System rebuilding process; System reliability; System reliability design; System rebuilding process; Data storage system; System reliability design; k-out-of-n:F system; Preventive maintenance; Data redundancy
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2019.106576

•Reliability design and maintenance for data storage system.•Data redundancy and system rebuilding process are considered.•Maintenance time is not negligible and external shocks are considered.•The minimal long-run average operating and maintenance cost is provided. Considering the working and failure modes and maintenance process of a data storage system with data redundancy, we propose and study a reliability and maintenance model of a k-out-of-n:F system, in which the system experiences a rebuilding process with downgraded performance that follows preventive maintenance (PM) with replacement of failed components, and the system is subject to failure with different failure criteria during such rebuilding process. In addition, maintenance time is not negligible, and the external shocks would occur and possibly result in the failure of all the components. The maintenance of the k-out-of-n:F system with these characteristics has not been studied, and these characteristics bring in a new reliability and maintenance model and a new optimization problem that synthetically determine system reliability design and PM schedule. Such a problem is motivated by improving availability and efficiency of a data storage system running data redundancy technology. We conduct a numerical study in which the parameters of the models are set according to real data and practice considerations. In addition to demonstrating the established models and presenting optimal results, we also perform sensitivity analysis for the design and maintenance of data storage systems.