Alarm systems designed according to engineering and safety considerations provide the primary source of information for operators when it comes to abnormal situations. Still, alarm systems have rarely been exploited for fault detection and diagnosis. Recent work has demonstrated the benefits of alarm logs for fault detection and diagnosis. However, alarm settings conceived during the alarm design stage can also be integrated into fault detection and diagnosis methods. This paper suggests the use of those alarm settings in the preprocessing of the process measurements, proposing a normalization based on the alarm thresholds of each process variable. Normalization is needed to render process measurements dimensionless for multivariate analysis. While common normalization approaches such as standardization depend on the historical process measurements available, the proposed alarm-range normalization is based on acceptable variations of the process measurements. An industrial case study of an offshore oil gas separation plant is used to demonstrate that the alarm-range normalization improves the robustness of popular methods for fault detection, fault isolation, and fault identification.