Condition-based maintenance (CBM) refers to the philosophy of performing maintenance when the need arises, based
upon indicators of deterioration in the condition of the machinery. Traditionally, CBM involves equipping machinery
with electronic sensors that continuously monitor components and collect data for analysis. The addition of the
multisensory capability of human cognitive functions (i.e., sensemaking, problem detection, planning, adaptation,
coordination, naturalistic decision making) to traditional CBM may create a fuller picture of machinery condition.
Cognitive systems engineering techniques provide an opportunity to utilize a dynamic resource—people acting as soft
sensors. The literature is extensive on techniques to fuse data from electronic sensors, but little work exists on fusing
data from humans with that from electronic sensors (i.e., hard/soft fusion). The purpose of my research is to explore,
observe, investigate, analyze, and evaluate the fusion of pilot and maintainer knowledge, experiences, and sensory
perceptions with digital maintenance resources. Hard/soft information fusion has the potential to increase problem
detection capability, improve flight safety, and increase mission readiness.
This proposed project consists the creation of a methodology that is based upon the Living Laboratories framework, a
research methodology that is built upon cognitive engineering principles1. This study performs a critical assessment of
concept, which will support development of activities to demonstrate hard/soft information fusion in operationally
relevant scenarios of aircraft maintenance. It consists of fieldwork, knowledge elicitation to inform a simulation and a