Maintenance data entry is often inaccurate, inefficient, & inconvenient. Efficiency dependent on maintainer memory or knowledge. Short cuts are taken often as various technical manuals and different nomenclatures are needed to identify the ideal WUC. Sustainment lifecycle management and engineering functions performed by Air Force Lifecycle Management Center (AFLCMC) require accurate and standardized information to be effective. There is an opportunity to develop a WUC tool to increase accuracy of WUC and other maintenance data fields, that uses a collated information source that can sit along-side the web-CAMS window to allow maintainers to easily look up the best WUC for their specific task. Future functionality can include finding ideal action taken codes (ATC) and how-mal codes and making sure they are internally consistent. We propose creating a functional prototype WUC suggestion tool built in Python and deployed on AWS. The target users are maintainers during field maintenance activities. The functional prototype will utilize user inputs including part/assembly name, part number, & maintenance narrative to suggest an ideal, typically the most specific, WUC. Part numbers and names from the -4 Illustrated Parts Breakdown (IPB) will be linked to the WUCs in the -6 WUC technical manual and be used as metadata. This will allow the part number or part name to be linked to a WUC at the lowest level. An algorithmic keyword extraction technique will be used to process the inputs in the maintenance narrative and part name fields and matched to the metadata.
