Differences between predictive and preventive maintenance

These inspections are generally scheduled based on the lifespan of the machinery, which can even extend its useful life. This type of maintenance is known as a "regular checkup"; however, it has a drawback: the reports are not based on the actual condition of the equipment. In fact, IBM estimates that 50% of maintenance performed under this modality could be considered "wasteful."

According to another ARC article, only 18% of assets have an age-related failure pattern, while 82% of asset failures occur randomly. This means that 82% of assets are not actually at risk of failing due to age, and preventive maintenance performed on assets is ineffective. The perfect balance between investment in maintenance and reliable assets requires a more modern approach.

That's why companies are shifting their focus to predictive maintenance, which considers certain predetermined conditions for its performance. Constant monitoring of equipment is necessary to be alert to any signs the asset may be giving, such as changes in temperature, vibration, sounds, among others. The objective of this is to be able to predict the occurrence of failures in order to reduce the amount of unnecessary maintenance, increase the useful life of assets, and ultimately, lower costs on unnecessary materials and inventory. In fact, a report from the United States Department of Energy suggests that predictive maintenance can save between 25% and 30% compared to corrective maintenance.

Another study, conducted by TA Cook on maintenance efficiency, concluded that 86% of companies that regularly benchmark can increase efficiency as a result. Benchmarking, or the continuous and systematic comparison of your processes and key performance indicators with industry best practices, is a key way to identify inefficiencies. Typical KPIs tracked by companies that saw the greatest efficiency improvements include maintenance cost ratio, asset availability, and performance against tracked targets or goals.

Software is the best ally when it comes to managing reliable maintenance that optimizes results. That's why we created Aisoncore, a platform that allows mining companies to obtain real-time traceability of components undergoing repair. This enables asset management and monitoring, which ultimately translates into improved decision-making in predictive maintenance.

For this reason, we invite you to learn more about it and how it can support your management in the industry. We'll also prepare a personalized demo for you. Request it by visiting Contact.