Customer: Wonder Cement
Application: Cement Industry (Raw Material Extraction and Processing)
A rolling bearing is one of the most widely used elements in rotating machinery. As a critical component, it carries most of the load during the running of rotating machinery. If rolling bearing fails, serious problems arise, which will in turn result in the decrease of production efficiency and large economic loss. Records show that faulty bearings contribute to about thirty percent of failures in rotating machinery. Thus, it is of great importance to address effective fault diagnosis for rolling bearings.
Wonder Cement, a trusted brand and one of the leading cement manufacturers in India has always focused on digitalization as a corporate strategy. As a part of the initiative, they have collaborated with Acoem India as their condition monitoring partner for predicting maintenance and reducing unexpected shutdowns.
They have been monitoring their roller presses using conventional monitoring technologies. The client was worried and skeptical regarding the extent of bearing damage and with the present setup, it was difficult and challenging to get a definite outcome.
Early bearing fault detection was challenging because of the slow turning speed of HPGR (15-16 rpm) and high frequencies caused by the crushing process. The existing conventional monitoring methodology had limitations and could not support in providing actionable data to differentiate between these similar frequency patterns.
Additionally conventional techniques of vibration analysis, based on the frequency domain, have shown their limit for low speed rotating parts, where faults can result in very low energy phenomenon and are hardly detectable.
Roller Press is the most critical asset for cement plants as any unplanned shutdown can cause huge production loss. The vibration and shock caused by the bearing faults could endanger the running safety of the roller press. Thus, it is important to detect symptoms of its faults at an early stage to ensure safe operation of the roller press and avoid unplanned downtime .
The goal for Acoem was to create an effective solution which not only answers the concerns of the client but also ensures roller press remains healthy, online, and operational. Acoem Engineers came together with Wonder Cement’s technical team for designing an early fault detection solution package. Equipped with Acoem Falcon Vibration Analyser having patented technology, Acoem developed a customised configuration suited to slow turning machines which clearly identified machines risk and bearing fault with its severity as well as location on the machine.
Designed parameters like customised enveloping, Shock finder index (SFI), Long time waveform of @130 seconds were combined to give out definite results and addressed the issue of differentiating bearing damage frequencies from crushing frequencies
Within a short time, the solution was able to provide early warnings for bearing failure with actionable reports. Now, users have better insights to analyse and address issues with conclusive data on hand.
“The plant now has the information it needs to make the right decisions at the right time. These actions consequently benefit plant uptime, performance, productivity, and safety.”
Mr. Piyush Joshi, Head of Department, Wonder Cement
“Acoem Falcon with customised configuration not only helped us to identify early bearing faults with conclusive enveloping spectrum analysis but also gave us immense reliability in decision making.”
Mr. Amit Kumavat, Dy. Manager ( Systems & Technical Cell), Wonder Cement
Benefits to the customers include improved environmental and economic performance and long-term predictability of their Roller Press. Wonder Cement is also benefiting from optimized equipment maintenance, improved reliability and performance, and flexibility in maintenance planning.