Predictive maintenance systems save a significant amount of money at your facilities.

The capability of predictive maintenance system technology provides immediate actionable information for the maintenance manager, rather than mere data. 

The current generation of predictive maintenance software offers instant decision-making capabilities for engineers and plant managers responsible for maximising the utility of facilities while keeping maintenance costs to a minimum.

They are capable of instantly analysing and interpreting vibration, process and visual inspection data. Today's predictive maintenance software not only delivers integrated and prioritised information to plant managers in their offices, but throughout the entire organisation.

Predicting the repair needs of critical components in lathes, milling machines, turbines, fans, drills, pumps, and any other rotating device allows today's maintenance, repair, and operations managers to control the fate of plant operations by anticipating unexpected downtime in the first place.

Predictive maintenance software delivers actionable information, not just data. It can be used in all industries and facility sizes. However, this was not always the case. We have come a long way to arrive at today's predictive maintenance systems.

In the early days, plant engineers and technicians relied on a “run till failure” (RTF) maintenance programme, a method that almost guaranteed processes without scheduled downtime. Unsatisfactory, the maintenance industry welcomes continuous advances in technology as a means of helping to avoid costly machine breakdowns.

Even the private sector achieved rudimentary results while absorbing large labour costs. Car manufacturers and electricity companies, for example, maintain a team of vibration experts for the sole purpose of keeping track of the life of their machinery.

The predictive maintenance system saves money.

Overly cautious prevention systems of the past wasted valuable maintenance resources by manually analysing every piece of new data, regardless of whether the machines needed attention or not. The 80% machines in a typical plant will not have mechanical failures, so why waste time on machine parts that do not need to be replaced?

The latest predictive software uses expert systems to eliminate test results that appear acceptable, allowing vibration analysts to focus solely on those machines that may have faults. The time saved by not manually reviewing the data for each machine individually is significant.

The spectacular advances in the efficiency of predictive maintenance systems and savings in euros are the result of integrating predictive techniques into existing facilities. However, with the rigorous use of these techniques, it is possible to predict the useful life of new machines, saving organisations even more money.

During the plant's start-up period, evaluations were requested via vibration analysis and infrared analysis as one of the purchase criteria before signing the ownership of the equipment. Its predictive maintenance system was used to evaluate more than 600 parts of the new equipment, such as water pumps, cooling fans, and gearboxes. 

Using this vibration analysis equipment, they found that some machines did not meet specifications. Some had bad bearings and alignment problems, which led to excessive vibration. These had to be replaced, and the cost was covered by the warranty.

At least 100 pieces of equipment required adjustment or replacement. It was estimated that the maintenance costs to repair these defects, if they had not been detected during their progression, would have amounted to at least €31,000, with a maximum cost of €112,000. Production losses due to the machinery would have resulted in a greater loss in the plant's profitability.

If you are interested in learning more about the actions you can take to maximise the reliability of your industrial facilities, or the ROI of predictive maintenancewe invite you to subscribe to our Newsletter