An expert system (ES) for monitoring aberrations related to feed consumption, ambient temperature and disease detection was developed in order to support day-to-day management on aviary farms for laying hens. Knowledge of five experts was stored in the knowledge base, which consisted of aberration tables for standardising the knowledge representation and inference mechanism of the ES. Detection of aberrations in the production process is based on quantitative and qualitative data. According to the experts, the important quantitative data are: feed consumption, water consumption, ambient temperature, hen-day egg production, egg weight, body weight, flock-uniformity, second grade eggs, floor eggs and mortality. Data from four flocks and five standards were used for the sensitivity analysis and to validate the ES. The sensitivity analysis and the validation showed the importance of choosing a good standard and detection limit. Using farm-specific mathematical curves as standard and a practical set of detection limits, the sensitivity of the ES was 64% and the specificity was 72%. Using a set of starting detection limits, the sensitivity was 91%, but specificity then declined to 28%.