Achieving operational availability of mission systems is challenging for naval shipboard maintainers, who analyze large amounts of maintenance data to determine how and when to address equipment repair and replacement needs. Current data is available through a set of disparate sources that insufficiently portray the criticality of correcting the malfunction or reveal interrelationships and overall operational impacts. This makes it difficult to efficiently and effectively select, prioritize, and schedule future maintenance activities. To address this, we propose to design and demonstrate a Blended Advanced Decision GUI Environment for Reasoning Support (BADGERS). The BADGERS decision-support system (DSS) will enable shipboard maintainers to analyze system status and predicted malfunctions, evaluate high-level mission impacts, and efficiently make maintenance decisions through intuitive and innovative data visualizations. This system will provide maintainers with an integrated workspace that provides observability for fixing the issue through rule-based maintenance knowledge, as well as ecological graphical user interfaces (GUIs) to assess the operational impacts and validate root causes of predicted system failures. We will take an iterative Cognitive Systems Engineering (CSE) approach and presented within a software Prototyping and Demonstration Environment (PDE) to allow for rapid integration to Navy systems.
Benefit: We expect the fully developed BADGERS integrated workspace, rule-based reasoning and validation service, and ecological maintenance GUI to have immediate and tangible benefits across both Government and commercial applications. Government applications include the development of decision-support systems that reduce the workload and/or training requirements for maintenance operators for a variety of Navy systems, such as those envisioned for the Aegis Weapon System (AWS). Commercial applications include improved coordinated spatial, temporal, and relational visualization capabilities for a broad variety of web-based applications developed through Charles River Analytics Medusa application framework.
Keywords: maintenance visualizations, maintenance visualizations, Graphical User Interface (GUI), Decision Support System (DSS), Ecological Interface Design (EID), Cognitive Systems Engineering (CSE), integrated workspace, rule-based knowledge