Developing a machine integrated lube oil analysis system

船舶的可靠性和可用性对生活质量至关重要，并对全球消费的商品成本产生重大影响。这是因为海运业占全球贸易的90%，因此海上服务的中断会影响我们的生活方式和我们为商品支付的费用。到目前为止，很难确定地预测船舶的机械故障。这导致了旋转润滑机械（如发动机）的高故障率。船舶发动机的高故障率是海运业服务中断的主要原因。然而，这种中断可以通过早期发现发动机故障来避免，确保发动机故障被避免。早期诊断船舶润滑设备（如发动机）的潜在故障对船舶的运行至关重要。rab - microfluics开发了尖端的微流控芯片实验室技术，可提供润滑油的实时连续测试和分析。我们的“Lab-on-a-Chip”技术比目前的“将样品送到实验室”方法快1000倍，便宜10倍。分析机油、变速箱等中的污染物是检测问题的一种行之有效的方法。这个程序称为油况监测。我们在现场实时交付，这是对目前将样品送到陆上实验室进行分析的实践的重大改进，从而节省了成本，提高了机械可靠性和船舶可用性。我们通过开发机器学习能力，将硬件技术与数据计算相结合，利用硬件产生的大数据。这提供了实时连续监测，早期问题诊断，快速决策，提高效率和节约成本。该项目旨在进一步发展这一核心技术，并建立一个与实际操作船用发动机集成的现场原型演示器。这将确保我们充分展示我们的新型油况监测过程的自动化。这将是首个此类开发项目，通过确保及早发现关键设备的发展故障，有可能大幅提高船舶的可靠性和可用性。如果成功，我们的技术将预示着海事行业的游戏规则改变，并通过确保减少海事服务中断，必然会对我们的生活质量产生连锁反应。由于海运成本降低，这种成功也有可能反映在我们消费的商品成本上。

Reliability and availability of shipping vessels is critical to quality of life and impacts significantly on cost of goods consumed globally. This is because the maritime industry is responsible for 90% of global trade, hence disruptions in maritime service impacts the way we live and how much we pay for our goods. Until now, it has been difficult to predict with any certainty machinery failure in shipping vessels. This has resulted in high rate of failure in rotating lubricated machinery such as engines. The high rate of marine engine failure is the leading cause of service disruptions in the maritime industry. However, such disruptions could be avoided with early detection of engine faults ensuring that engine failure is prevented.Diagnosing early, potential failure of marine lubricated equipment such as engines is critical to operation of a shipping vessel. RAB-Microfluidics has developed cutting edge microfluidic lab-on-a-chip technology to deliver real-time continuous testing and analysis of lubricating oil. Our "Lab-on-a-Chip" technology delivers oil analysis 1000x faster and 10x cheaper than the current "send the sample to the Laboratory" approach. Analysis of contaminants in engine oil, gearboxes, etc. is a well-established method of detecting problems. This procedure is called Oil Condition Monitoring. We deliver this onsite, in real time and this is a significant improvement on the current practice of sending the sample to onshore laboratories for analysis thus saving cost and improving machinery reliability and vessel availability. We combine our hardware technology with data computing by developing machine learning capabilities to utilise the big data generated from our hardware. This offers real-time continuous monitoring, early problem diagnosis, rapid decision making, enhanced efficiency and cost savings.This project seeks to develop this core technology further and build a field prototype demonstrator that integrates with a live operational marine engine. This will ensure we fully demonstrate the automation of our novel Oil Condition Monitoring process. This will be a first-of-its-kind development with potential to dramatically improve shipping vessel reliability and availability by ensuring developing faults of key equipment are identified early. If successful, our technology will herald a game changer for the maritime sector and would invariably have a ripple effect on our quality of life by ensuring reduced marine service disruptions. There is also the added possibility of such success being reflected on the cost of good we consumed due to lower marine transportation costs.