10006008Automating lubricating oil analysis as a means to reduce engine GHG emissions.ClosedCollaborative R&DInnovate UKGreenhouse gas (GHG) emissions from maritime transport is estimated at around 1 Bn ton of carbon dioxide equivalents (CO2 eq.) accounting for 3% of global anthropogenic emissions (IMO 2020). Emissions need to be cut by 50% up to 2050 to meet the Paris agreements (IMO 2020). Automation and digitisation have gained significant traction as enablers of greater efficiency in the maritime industry and can contribute meaningfully to reducing GHG emissions. RAB-Microfluidics have developed a microfluidic lab-on-a-chip technology that automates and digitises a key aspect of a shipping vessel operation -- Oil Condition Monitoring (OCM) which has the potential to enable marine engine efficiency, thereby reducing GHG emissions. OCM has remained relatively unchanged for over a hundred years with conventional wet chemistry techniques being the gold standard for industrial testing and analysis for engine condition monitoring. While these techniques deliver, robust compositional information, they are unable to provide to the desired frequency (because it is a manual process) data that can enable key insights to aid efficiencies and energy savings that lead to reduction in GHG emissions. RAB-Microfluidics lab-on-a-chip technology completely changes this as our technology automates the OCM process. Consequently, there is now the opportunity to plug that existing knowledge gap. In this project, we will integrate this technology with a live marine engine to continuously monitor the condition of engine condition during operation in real-time. Engine condition data will then be correlated with engine operation information (e.g., engine load, exhaust temperatures, shaft power/torque, engine speed, fuel pressure, etc.), performance data (e.g., energy efficiency plan, lube-oil consumption, fuel consumption etc.) and GHG emissions data to establish a cause-and-effect relationship. Such automation will allow generation of continuous streams of data on engine condition to provide insights that ensure the optimisation of marine engine operation/performance, permitting energy savings which will lead to reduction of GHG emissions. This potentially creates an offering that does not currently exist. This automation of the OCM process permits a potentially disruptive offering that transitions businesses from reactive to predictive operational strategies with the added potential to open up a £400Mn OCM automation market. This will be a first-of-its-kind development with potential to impact the reduction of GHG emissions. If successful, our technology will herald a stepwise change for the maritime sector helping maritime companies transition to next zero emission.