Rotating equipment, such as Gas turbines, steam turbines, Hydro turbines, generators, motors, compressors, pumps, etc., are critically important components of plant operations, and must always perform reliably and efficiently. However, given the high pressures and harsh environments in which such equipment operate, their failures are all too common.

To keep equipment running for as long as possible, companies must invest in maintenance. Many aspects of these maintenance tasks were less than ideal. Often, plant managers ran equipment until failure instead of performing preventive maintenance. This reactive maintenance approach results in unscheduled downtime, loss of production and revenues, higher labor costs and faster deterioration of assets.

Rotating equipment usually operate in a speed range of 1 to 10,000 rpm and withstand high pressures and temperatures. These factors, combined with centrifugal and centripetal forces, increase wear that will inevitably lead to failure. This could mean several days or weeks of lost production and millions of dollars in downtime and repair costs. 

For example, a gas turbine sub-system failure presents serious risk of significant downtime. A 22% failure rate of the compressor, combustion chamber and turbine sub-systems causes an average downtime of 24 hours per failure. But each individual failure could cause 10 to 100 hours of downtime, leading to significant production losses.

To avoid such costly failures, owners and operators in many industries such as Power Generation, Oil & Gas, Steel, Maritime, and Mining found it mandatory to implement some sort of predictive analytics (maintenance), to detect such potential failures weeks, and sometimes months in advance to take the necessary corrective measures in due course to minimize or eliminate such costly failures. 

Predictive analytics (maintenance) techniques are designed to help determine the condition of in-service equipment to estimate when maintenance should be performed. This approach yields cost savings over routine or time-based preventive maintenance because tasks are performed only when warranted.

TCS, through its affiliate entity, TCS Digital, has worked with OEMs and Predictive analytics pioneers to develop various implementation strategies to ensure value-capture and maximize the benefits from such implementations.

TCS has developed blueprints (Digital Twins) for various types of rotating & fixed equipment from different manufacturers such as GE, Siemens, Brush, Andritz, Metso and many others. Below are some of the equipment we have developed the blueprints for: