![]() Therefore, for the purpose of providing actionable real-world guidance asset health has been listed as the primary lever to pull to impact rate of fuel use. ![]() While asset health will also impact emission intensity, the exact change is highly difficult to quantify without laboratory results for those specific engine conditions. By using machine learning, MaxMine carbon also separates asset health from other effects such as operator usage meaning the overall opportunity for carbon reductions through maintenance actions can be quantified. Equipment can then be ranked by the excessive fuel usage to help prioritise carbon-based maintenance actions, together with the likely engine fault behind it and supporting evidence. MaxMine is capable of measuring high rate data from all OEM engine sensors, which is analysed to detect issues such as clogged air filters, under-performing turbos and injector issues. Engine health can substantially impact the fuel usage and hence the rate of carbon released to the atmosphere.
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