Proactive Versus Reactive Maintenance Measurement/Improvement

Successful maintenance improvement projects in large organisations require a systematic and well-founded approach to ensure tangible technical outcomes. A structured maintenance data analysis has been developed to address key maintenance objectives known as proactive maintenance, backlog management and failure mode analysis.

Maintenance data (i.e. work orders) for one fiscal year 2002/2003 in a large Alumina refinery is investigated in an attempt to established short, medium and long-term maintenance improvement strategies. Data set included more than 61,000 individual work orders with a total amount of actual cost recorded as high as $63m with more than 330,000 hours of actual work registered in the CMMS.

Such a structured analysis has led to specific set of recommendations for improvements in planning and scheduling of works, PM strategies for number of critical assets, new backlog management strategy and engineering investigations into major failure modes. Since delivering the full report, several of these improvement initiatives have been successfully implemented, and few others are being considered for implementation.



Maintenance Engineering Bureau Using Maintenance Data To Drive Improvement

This paper presents an objective methodology for maintenance data analysis. The purposes of these analyses are to identify strengths and weaknesses in the maintenance management system, opportunities for improvements, and benchmark maintenance key elements against maintenance best practice. A wide range of reports can be provided from analysing the data from computerised maintenance management systems. These reports can be categorised as Performance Reports, Benchmarking Reports, Optimisation Reports, and Data Integrity Reports.

Failure Modes and Effect Analysis is one of the main outcomes of the maintenance engineering bureau services. This analysis is an easy to use and yet powerful, proactive maintenance engineering method, which can identify potential failure modes, determine their effect on the maintenance costs, and identify actions to mitigate the failures. The results of the analyses of the various maintenance system data sets based on the developed methodology are presented.