From Monitoring to Reliability Analytics: Designing a Reliability Information System for Data Centers Using DT and QFD

Abstract

Equipment reliability is critical to ensuring service continuity in data centers as strategic digital infrastructure. However, existing operational information systems remain largely alarm-oriented and do not adequately distinguish warning notifications from actual equipment failures. Key reliability indicators such as time to repair (TTR), repair cost, and annual failure rate (AFR) are often unavailable in an integrated historical format, limiting data-driven maintenance decision-making. This study proposes the design of an equipment reliability information system using an integrated Design Thinking (DT) and Quality Function Deployment (QFD) approach. The research was conducted in an operational data center through semi-structured interviews with six key stakeholders, including maintenance technicians and management. DT was applied across the empathize, define, ideate, prototype, and test stages, while QFD translated user needs into prioritized technical features. Validation was performed through prototype testing using historical maintenance and failure data. The results indicate that prioritized features include work order tracking, equipment-level maintenance history, asset data management, and reliability analysis modules. The proposed DT–QFD framework offers a replicable approach for designing reliability information systems in data centers and other critical infrastructure environments.

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