APMS  
     
     
 
     
     
     
     
     
  Our Mission
 
   
     
 

Every predictive maintenance
technology should foresee failures
before their occurrence,
but none gave you actionable
instruction about how to solve them.
Every predictive maintenance
technology can survey a single
critical machine,
but none could control a complex
mechanical ecosystem.

APMS is the only one.
We wanted to develop an advanced
maintenance technology able to
constantly keep the asset in optimal
conditions through asset integrity.

 
     
     
     
 
     
     
  Our Promise
 
   
     
 

We will provide you with a live dynamic prognosis
of your mechanical assets.
Four main steps to guarantee your asset health:

 

Signs & symptoms :
Data collection of the machinery’s health
condition


Symptoms’ correlation :
Root Cause Analysis which relies on the
correlation of condition and process data


Disease identification :
Automated technical diagnosis provides
the upcoming technical “illnesses” of
your asset.


Prescription :
Actionable and accurate detailed
mechanical advice to solve the identified
technical issues.

 

AND MORE...

 


Total integration with other
Asset Integrity Management
systems
Maintenance Cost reduction
Productivity Optimization
Online remote-control access:
accessibility, parametrization,
updating and debugging from
everywhere

 
     
     
     
 
     
     
  Our Solution
 
   
     
 

APMS is a Prescriptive Diagnostic System
which provides effective control of
mechanical eco-systems.
In details APMS is:

A predictive mechanical failures
detection system.


An autonomous system capable to
provide technical insights for corrective
actions.

 

APMS is a comprehensive system motorized
by algorithms and rules. It has been
developed in technological partnership with
Rockwell Automation.


APMS is a decision support tool. It easily
shares information with Plan Maintenance,
Logistic & Procurement and Safety &
Environment ones.

 
     
  THE ULTIMATE TECHNOLOGY IN THE
MAINTENANCE WORLD.
 
     
     
 

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