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Failure Modes and Effects Analysis (FMEA) is a very useful reliability-management instrument for detecting and mitigating risks in various fields. The linguistic assessment approach has recently been widely used in FMEA. Words mean different things to different people, so FMEA members may present Personalized Individual Semantics (PIS) in their linguistic assessment information. This article presents the design of a PIS-based FMEA approach, in which members express their opinions over failure modes and risk factors using Linguistic Distribution Assessment Matrices (LDAMs) and also provide their opinions over failure modes using incomplete Additive Preference Relations (APRs). A preference information preprocessing method with a two-stage optimization model is presented to generate complete APRs with acceptable consistency levels from incomplete APRs. Then, a deviation minimum-based …