What sounded like science fiction just a short time ago is now digital reality in Australasia in the new predictive maintenance solutions presented at this year’s IMVAC conference on the Gold Coast from August 6-9.

The International Machine Vibration Analysis and Condition Monitoring (IMVAC) professional development conference heard presentations from technology leaders such as the global Schaeffler Group, highlighting advances in its industry 4.0 “Smart Factory” automation and data exchange technologies.

Schaeffler’s latest predictive maintenance solutions enable machinery operators to look ever more clearly into the future – they provide machine operators with vital information about the future condition of their machines.

Predictive maintenance allows not only the capacity utilisation of factories, mines, utilities and processing plants to be optimised, but also makes it possible to plan maintenance intervals at precisely the right time for optimised “Total Cost of Ownership” calculations.

An important prerequisite for predictive maintenance is automated rolling bearing diagnostics, a function that is used in motor gearbox units, for example. These units are used not only in machine tools but also in belt conveyors, presses, and steel mill rollers, for example.

Schaeffler BEARINX software is one of the leading programs for performing rolling bearing calculations. It enables rolling bearing supports to be analysed in detail – from single bearings to complex gear systems and linear guide systems.

All calculations are performed in a consistent calculation model. Even for complex gears, the contact pressure on each rolling element is considered in the calculation.

Because machine drives are operated virtually without interruption, they require intensive maintenance to prevent production downtimes.

Therefore, it is important for operators to know the condition of the drive components at all times, and why the bearings are becoming particularly important as a central machine element.

The latest generation of the FAG SmartCheck diagnostic system represents a further step forward for Schaeffler in these areas. In addition to identifying the threat of bearing damage, wear, and irregularities such as imbalance and misalignments based on vibration pattern changes, this system also features a cloud connection.

The system creates an automated diagnosis in the cloud from the raw data supplied by the FAG SmartCheck and from additional data, e.g. from the machine control system.

Applications for this technology include bulk handling and conveyor applications, mining and energy; building, construction and access equipment installations, such as forklifts and logistics; food and beverage and agribusiness processes, including paper and packaging; manufacturing, metals and process engineering, transport and industrial motor and transmission applications, including pumping and HVAC installations and utilities including electricity, water and waste water.

Systems such as the FAG SmartCheck allow the condition of rolling bearings and machine components to be diagnosed automatically. What is more, storing the data in a cloud also allows them to be used for other calculations, such as drive train and rolling bearing simulations relating to their static and dynamic strength.

Using the real load spectra gathered during operation, Schaeffler can continuously calculate the bearings’ remaining useful life on the customer’s behalf at freely definable time intervals. Schaeffler’s BEARINX calculation tool retrieves the data from the cloud. The customer can then view the remaining useful life of every bearing in the machine using an internet-capable end device.

Schaeffler’s solution is based on three central elements:

• A suitable system of sensors gathers reliable load data for the machine and its bearings.
• Simulation models calculate the remaining useful life based on the dimensions of the machine and the actual loads.
• A software platform through which the customer can access the calculations and retrieve information about his or her machine individually.