Textual data in operator logbooks represent an untappedopportunity to retrieve information about the maintenanceroutines of HVAC equipment and control infrastructure. Thispaper presents a case study in which seven years' worth ofwork order logs from 44 buildings on a university campuswere analyzed. After extracting HVAC-related terms such asfan, AHU, VAV, stuck, and leak from custom operatordescriptions, the apriori algorithm was used to derive associationrules that define the coexistence tendencies of theterms in a work order (e.g., coexistence of the terms radiatorand leak). Based on this analysis, a preliminary HVAC workorder frequency model was put forward. The results indicatethat the annual work order intensity per 1000 m² (10,764 ft²)was about 4. More than 70% of the HVAC-related workorders were issued to address zone-level problems. Amongthe AHU-level work orders issued for a physical subcomponent,more than 90% were related to fans. Future work isplanned to analyze the HVAC-related work order patternswith numeric data from automation and controls networks.