One of the world’s largest cement companies in the world, has its operations in Asia, possessing a production capacity of 3.1 million tonnes per annum. The plant was facing acute reduction in production capacity in line #2, since the Kiln main drive motor was exhibiting very high abnormal vibrations.  The plant personnel were forced to operate the equipment at less than 1250 RPM against the rated RPM of 1500. This led to a loss of productivity to the tune of 20% plus there was a lurking fear of catastrophic failure of the machine train resulting into shutdown of the line #2.

The machine train of Kiln consisted of 250KW motor, rated 1500 RPM coupled with a multistage gearbox driving the Kiln. The highest vibrations of 79 mm/sec were recorded at motor NDE bearing, when coupled with gearbox and 17 mm/sec recorded, when Motor was tested on a Solo run. Maintenance team tried with various corrective actions viz. changing the motor, coupling, alignment between Motor & Gearbox etc. but weren’t successful in resolving the problem. We were requested by the Plant personnel to study the encountered problem, identify root cause and recommend implementable solutions. We adopted a systematic consultancy approach aided by site measurements, machine diagnose plots, to resolve the reported problems by sfhifting the structural resonances. After implementation of suggested corrective actions, vibrations were reduced from 79mm/sec to 3.9mm/sec.

Specific benefits accrued to the Plant maintenance directly from this problem solving were-

• Higher line productivity
• Reduced downtime and avoiding catastrophic failure
• Minimize maintenance labour costs
• Reduction in Spare parts consumption

This paper summarizes the problem identification & solving methodologies, measurements taken, analysis of test results, instrumentation used, recommendations and validation of machine dynamic behaviour post corrections.

Presently, Mr. Praveen Gupta is heading Special Oilfield Services Co. LLC’s Reliability Engineering & Asset Management (REAM) business unit, providing solutions and services for reliability improvement, condition monitoring & asset integrity of Plant Assets in Oman & Middle East. Praveen is an experienced professional with 20 years of rich experience & expertise in Condition Monitoring & Reliability with Vibration Analyst Cat III Certification from Mobius Institute, Australia and CMRP certification from Society of Maintenance & Reliability Professionals (SMRP), US. He is an Electronics Engineer with Management Post Graduation from India, having worked for various reputed organisations viz. Indira Gandhi Centre for Atomic Research (IGCAR) in India, IRD Mechanalysis etc. He has been at Pruftechnik Germany & Meggitt Switzerland on Machine Protection & Condition Monitoring Systems. He has been a regular speaker in National & International Conferences on Reliability & Asset Management in India and abroad and has published more than 20 technical papers in leading National Conferences & journals.

Arun Prasath is working as Senior Application Engineer in Reliability Engineering & Asset Management (REAM) business unit, at Special Oilfield Services (SOS) Oman, the leading organization in Oman present since 1986. At SOS, he is the trainer and Condition Monitoring consultant to provide Reliability, Condition Monitoring & Asset Management services and ISO 18436 certified trainings to Plant personnel across Oman & Middle East. Arun has completed B. Tech in Mechanical Engineering and has over 14 years of experience in the fields of condition monitoring, laser alignment, in-situ dynamic balancing etc. A BINDT Level -2 certified vibration analyst, he has worked in various industry segments viz. Pulp & Paper, Power, Cement, Automobile, Metal, Food & Beverages, HPI etc. Over the years, he has gained expertise in predictive maintenance methodologies, as part of the integrated maintenance solution contracts and has also delivered more than 5000 hours of trainings on Vibration Analysis, Machine Alignment, Dynamic Balancing & Reliability trainings all across India.