Profitable production demands continuously improved maintenance decision accuracy for reducing/avoiding failures and unplanned stoppages due to their consequences. More accurate decisions prolong life length of components and consequently machines, and maintain the production running longer. When a condition monitoring (CM) value exceeds a significant (warning) level it demands a clear understanding of what happened and how it will develop in the next future to avoid failures. Also, CM demands reliable information concerning the probability of failure, residual life time and when is the most profitable time of conducting maintenance. Companies strive to reduce production cost in order to increase the possibility of offering customers lower prices & generating additional competitive advantages. But, applying new technologies for enhancing maintenance and production performances and company competitiveness counter many problems in industry. In this paper, a new innovative e-Maintenance Decision Support System (eMDSS) is introduced and discussed; the problems facing successful implementation of eMDSS based on a case study are introduced and discussed. Solutions to avoid the problems facing successful implementation of e MDSS are suggested and discussed. eMDSS offers a unique opportunity to achieve just in time dynamic and cost-effective maintenance by selecting the most profitable time for maintenance. It offers innovative solutions to increase maintenance profitability by enhancing maintenance decision accuracy via:
Identifying & classifying problems based on their shares in losses in production.
Predicting the value of CM parameter, e.g. vibration, level in the near future.
Estimating the probability of failure and component remaining life in the near future.
Estimating the most profitable time for maintenance action.
Selecting the most profitable maintenance action.
Mapping & following up maintenance & production performances.
Identifying and following up the most profitable investment in maintenance.
eMDSS combines technical and economic data describing future situation in addition to the current & past data, which is necessary for production and maintenance successful planning. The major conclusion is that applying eMDSS it is possible to reduce failures appreciably, prolong life length of components/equipment & perform profitable maintenance