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Vibration Analysis

  • Vibration Analysis

Lantabur  Technology  Persada  will  carry   out   monthly   vibration   service   on   customer   rotating  equipment  and provide   analysis  data  and   comprehensive   report   with  recomendation  for  corrective   action  if  find   failure   on machine. Customer will be  involve  in  program  to make  sure transfer knowledge on vibration analysis.  We  also will provide free training program with predictive maintenance  topic  to  improve  customer  personnel knowledge and at the end of project, customer will capable to do predictive maintenance program by themselves.

One of technology in predictive maintenance is vibration that utilize  vibration  signature as tool to indicate machine condition in two basic facts : (1) all common failure mode have distinct vibration  frequency  components  that  can be isolated and identified, and (2) the amplitude  of each  distinct  vibration component will remain constant unless there is a change in the operating dynamics of the machine train.

 

 

 

 

 

Since machines are constantly monitored, there is a growing  body  of information on  the  characteristics  of  each machine and guide us to put maintenance effort where it is needed the most.

 

The objectives of predictive maintenance services program are:

 

  • Customer will get information  about their machine condition  by   providing   vibration   analysis  data   and  its machinery condition status as reference for corrective action team to remove the problem.
  • Maintenance department can identify, eliminate machine failure  y  modification  and  correction  of   machine from   failure  mode  and  its  maintenance  historical  data,  so  the Mean  Time  Between  Failure  ( MTBF )  of machines can be extended.
  • By   comprehensive   PdM   training   program,   customer   personnel  will   have   knowledge  about  condition monitoring   technique including collecting   data,   vibration   analysis   data,   develop   comprehensive   report  and build recommedation action to be followed up by corrective team.
  • By   coacing  program , customer  will involve directly in collectiong data and analysis that make them familiar and capable to do the program after project end by their own resources.
  • Assisting  in  development  of  plant  maintenance  strategy by providing data for Planner to generate reactive, preventive, and predictive maintenance work schedule and
  • Increase plant capacity/production through the elimination of downtime.

Scope of Work

 

This predictive maintenance program cover activity to collect data  and  provide  analysis to inform customer about their machine condition status. PT.Lantabur Technology Persada  also will provide free training program that assist customer to improve knowledge on predictive maintenance especially vibration analysis.

 

  1. PT.Lantabur Technology  Persada  will   provide   coacing   program   in   predictive   maintenance  by   involve  customer personnel   on   program   and   coach   them   how   to  collect  data,  analyze the data and develope report for corrective action.

These scopes of work are summarized as follow :

  1. Monthly condition monitoring service
  2. PT.Lantabur Technology Persada  team   will   carry   out   monthly  condition  monitoring  service on rotating equipment by vibration technology and deliver analysis report about machines condition status. The duration of execution is 5 days per week for two years project duration.

PT.Lantabur Technology Persada will coach customer personnel during project by involving their  personnel  project execution   from   building   database,   data   collection,   data   analysis,   and   develop   comprehensive   report    & recommendation for corrective action.

This service shall  be done  by  using  new  vibration analyzer  which  will   be   customer   property   after  project   en
Predictive Maintenance Training Program.
PT Lantabur Technology Persaada will provide free  courses  for  customer  personnel  to  improve knowledge and competency in predictive maintenance and give more understanding about best practice of maintenance.