Cost Optimisation of Maintenance in Large Organizations

Abstract

Large organizations routinely deploy extensive computerised systems for work management control, thereby collating databases of work order information which may be of variable quality. It is possible to analyse these data sets, taking into account issues with codification and gaps in individual work order completeness, to determine trends in work management, PM strategies, failure modes in critical plant and overall expenditure. Cost optimisation of maintenance involves three steps. The first is to understand the raw data and determine trends in what is driving the expenditure and which parts of the asset base require the most investment. The second is a codification system for the data to enable searching for possible savings across large fleets of assets. The third is to implement a search routine for savings and then apply it, to develop a credible budget savings strategy. The areas of improvement which need to be considered include work management with improvement in the planning of work so that simple or temporary fixes are replaced by well-considered and executed repairs. Secondly there is a need to improve the PM strategy so that reactive approaches to specific assets at various facilities are lifted to a more proactive approach. Both of these cases relate to addressing the issue that poor maintenance equates to high levels of work orders on assets which otherwise should not require this intensity of work resulting in wasted effort and increased cost of maintenance. In order to determine which assets have high cost levels, an internal benchmarking process can be applied to large organisations. This is implemented by comparing the maintenance of specific asset types in different facilities throughout the organisation and identifying those which have above average levels of maintenance. Results to date have shown that a credible level of overall maintenance savings may be claimed by simply identifying asset areas which are receiving too much work and then proposing improvement work to address these high rates.