Climate contribution with predictive maintenance
The United Nations predicts that by 2030, the world population will reach 9 billion, which will have a heavy toll on the earth’s resources. An enormous population requires more goods to be manufactured. As comprehensive maintenance aims to extend the lifetime of machinery, reduce energy and the downtime of assets, it contributes to the climate. Several researchers have suggested that growth in cloud maintenance for heavy assets significantly increases machinery’s effectiveness (Pourbozorgi-Langroudi & Weidlich, 2020).
The United Nations climate change
The United Nations (UN) set goals to be achieved by 2030 for the manufacturing industry to diminish the carbon footprint. Our Common Future that the most significant challenges for the future of sustainable manufacturing are the need for move economic growth patterns which are more environmentally sound, the particular responsibility of developed countries in this regard and the need for increased international cooperation. To achieve this goal, the UN’s member states will have to implement a range of mitigation options to reduce climate change. The UN’s sustainable manufacturing declaration supports predictive maintenance to reduce climate change.
What is predictive maintenance
Predictive maintenance is a way that helps to reduce this environmental effect by analysing the assets to predict when they are going to break down. This has three main benefits for the company. Firstly, it reduces the harm caused to climate by reducing energy consumption. Secondly, it improves productivity because predictive maintenance reduces downtime and waste of machinery by repairing them before they break down. Thirdly, it enhances quality because predictive maintenance can identify problems in products early on. Predictive maintenance systems can identify the assets at the most risk for breakdown and harm to the environment.
How does predictive maintenance exactly contribute to the climate?
Predictive maintenance is a technique in which machine data from an asset is used to predict when it will fail and act before a failure occurs to avoid downtime, maintain production levels, and prevent further damage. Predictive maintenance is an approach to the maintenance of machines and equipment. It takes a proactive approach by using predictive analytics to identify the likely causes of failure. Predictive maintenance can be applied to most assets, and it has a measurable impact on the environment.
It contributes to the climate as manufacturing can be done by using less energy, reducing water use and lowering costs associated with machine repairs. Predictive maintenance offers improvements in efficiency, safety and profitability for manufacturing companies while minimising environmental impacts. Predictive maintenance benefits the environment with sustainable manufacturing because it reduces harmful emissions by preventing machine failures and reducing energy use during unplanned shutdowns.
Predictive maintenance with UReason
With UReaon’s APM Studio; a reduction in downtimes, cost savings for unexpected breakdowns, and extended asset life are all major benefits of implementing a preventive maintenance program. Preventive maintenance keeps machines working correctly by ensuring that any problems are caught before they lead to costly downtime issues. This could result in 25% reduction of downtime of the assets. It’s important to understand though that preventive maintenance will not solve all issues with your equipment. However, when implemented successfully, Predictive Maintenance keeps machines up and running with a decrease of costly maintenance costs of 20% by preventing unexpected failures. Moreover, APM software provides companies with a real time overview of their assets lifetime which leads to longer asset life and significant reductions in machinery costs over time. Predictive maintenance can increase the durability of assets with 80%.