For a mining company or large manufacturer with thousands of machines, accurate machine maintenance can save millions of dollars each year.
An effective Predictive Maintenance (PM) program will minimize under- and over-maintenance of your machine. 4Digital's Artificial Intelligence can tell you, based on data, when a machine requires maintenance.
DEEPERING PREDICTIVE MAINTENANCE (PM)
Based on business data, the mining or machinery company currently incurs costs of $27,000 per failed or maintained machine. 4DIGITAL's AI aims to reduce this cost.
Implementation of the Predictive Model
4Digital's AI aims to show the industry how a predictive maintenance (PM) program can save them money.
To do this, a predictive model is built that predicts machine failure within 90 days of actual failure. Note that a suitable error window will always depend on the context of the problem. If a machine breaks without maintenance in 6 months, a three month window is meaningless. Here, where a machine will run for 4 to 6 years without maintenance, a 90-day window becomes reasonable.
“4DIGITAL's AI can tell you, based on data, when a machine requires maintenance, optimizing the balance between corrective and preventive maintenance, facilitating on-time replacement of components.”
"This approach minimizes the cost of unscheduled maintenance and maximizes component life, thus getting more value out of a part or piece."
CONCLUSION
In a scenario where maintenance costs the company about USD 27,000 per machine, a predictive maintenance solution from 4Digital will reduce the cost per machine by about USD 3,560 per machine and considering an example of a universe of 430 machines, the efficiency equals to 1,204 million savings or around a 10% reduction in total expenses.
DOWNLOAD THE FULL BUSINESS CASE
https://www.alacarteai.com/_files/ugd/8e4986_c8ac1b56814e489db7e1e10a5f62f5c6.pdf