SBIR-STTR Award

Augmented Maintenance Prediction (AMP) enhances Condition Based Maintenance (CBM+) activities by monitoring the unique molecular markers produced by the decomposition of gaskets, fluids, and lubricants in complex mechanical systems. The current information driving CBM+ predictive maintenance is generally limited to a fleet’s logs of historic use, reported issues, SOAPS analysis, and historic maintenance, each of which is used to predict the probability of mechanical failure. AMP increases the ability of CMB+ to predict mechanical failure by identifying the molecular markers of aging/failing parts before they are observable to maintenance staff. With this molecular analysis, AMP improves the ability of CMB+ to proactively identify opportunities for low-cost interventions to avoid high-cost catastrophic failure. ?AMP leverages a novel and inexpensive batch-collection technology to capture the full spectrum of volatile chemistry present at different physical locations in the mechanical system. AMP can be used before, during, or after equipment use. The AMP Collectors are then batch-processed through a GC-Mass Spectrometer. AMP’s unique AI is then applied to match chemical signatures identified to specific lubricants, fluids, degradation of gaskets, and by-products of combustion. Combining AMP’s intelligence with the data from historic use, environmental conditions, and maintenance logs, AMP will recommend parts to be inspected by technicians during future field- and depot-level maintenance. With the subsequent and ongoing feedback of the findings from activities prescribed by AMP, the system becomes more intelligent and accurate at predicting mechanical failure and optimizing maintenance in the context of part availability and other supply chain constraints. In addition to identifying the need for service, AMP assists in optimizing the schedule for “Time-Change Tasks”, moving them to “Demand-Change Tasks”: reducing unnecessary basic maintenance and expediting the detection of advanced issues prior to scheduled maintenance. AMP enhances the ability of CMB+ to reduce cost, improve performance, enhance readiness, and improves the predictability of the overall maintenance and requisition

Homeland and base security require the ability for WMD-CST, HAZMAT, and AF Emergency Management teams to detect, analyze, and monitor chemical, biological, radiological, and nuclear events (CBRN). Today, these first responders suit up in protective gear and walk with their sensors, directly into gaseous plumes in order to collect and analyze samples of these hazardous materials, putting their lives in immediate danger. It also significantly limits their ability to monitor multiple concurrent events as well as their ability to collect sufficient data to optimize real-time knowledge of the true behavior of these chemical plumes as they move through the air. Because a person is currently required to physically take the samples, it may take four to six hours to have a team in place ready to take samples. With that, the number of samples those individuals can collect are limited based on the mobility of the person and equipment. Riis’ technology has the capacity to collect this chemistry inexpensively and at a reduced risk to the user. This allows for multiple observations through in three dimensional space and over time, creating both a baseline model for the plume, with appropriate placement, and control view of the plume as it progresses