EXAKT combines equipment age, condition variables, and economical consideration to model and assist maintenance function with repair/replace decision

EXAKT

Predictive maintenance is often regarded as the most advance and desirable form of maintenance. Organisations have spent millions in upgrading their capability to perform effective condition based monitoring. Many have purchased a wealth of advance monitoring tools perceived to automatically enable the maintenance workforce to effectively predict the impending failure of assets. However, in many cases, these concepts are difficult to realize and in some cases they are simply elusive. While almost any type of asset condition data can easily be monitored and captured, it is sometimes difficult, if not very difficult, to interpret the data and turn them into meaningful information to enable the organisation to make the correct replace/repair decision. Even more concerning are the cases whereby as a result of condition monitoring practice have led to the wrong decisions being made. Hence, many organisations have found that the practice of condition monitoring has simply become an exercise to collect asset data without any (or only minor) improvement in asset reliability.

EXAKT is a reliability decision support tool used for predicting asset reliability and optimizing condition based maintenance practice. Developed, under the guidance of Professor Andrew Jardine, in the CBM laboratory in University of Toronto and funded by a consortium of 10 multinational firms, EXAKT aims to:

• Apply statistics equipment history and condition monitoring data
• Identify the critical variables affecting reliability
• Predict remaining useful life and equipment failures
• Define the mix of preventive replacement and breakdown maintenance in order
   to minimize cost, maximize reliability by achieving the optimum risk/cost/reliability
   balance


Benefits of EXAKT
 
Relates condition variables to failure modes with statistical confidence levels and therefore prompts the company to orient their CBM programs toward collecting significant data
Gives the equipment operator a high level of confidence that the equipment will not fail before the end of the production run
Reduces maintenance costs by optimizing the blend of preventive renewals and renewals due to failure
 
Provides for orderly replacement planning by predicting remaining useful life
 
For complex equipment, increases the accuracy of failure prediction by detecting potential failures at the component level
Provides accurate and consistent prediction model for entire equipment (multiple failure modes)
 
easy to read graphical output shows results at a glance and easily integrated with current maintenance management systems and procedures.


Please contact us for more information on EXAKT, or download the brochure here.