SKF takes a look at how preventative plant maintenance has evolved to enable engineers a holistic approach to condition monitoring, resulting in significantly increased productivity and profitability.

Waiting for machine failure before carrying out maintenance has now largely been replaced by more effective preventative maintenance programmes, supported by an emerging range of diagnostic tools and software. However, although this approach has provided a more effective way for engineers to manage maintenance and repairs, it is often dislocated, and, to a certain degree, remains re-active, contribution little to the bottom line.

A holistic solution that takes into account the requirements of an entire organisation, simultaneously analysing, assessing, and managing maintenance issues, is needed. This type of programme will enable companies to minimise maintenance costs and maximise profitability efficiently through achieving consistently high levels of uptime and productivity.

Asset Efficiency Optimisation (AEO), developed by SKF, is a new approach that allows companies to manage assets, as part of an integrated maintenance strategy, more effectively. By ensuring that a plant runs smoothly with minimum downtime considerably increases productivity and profitability.

AEO focuses simultaneously on the maintenance requirements of an entire plant, as well as the specific needs of individual pieces of equipment; maximizing performance and uptime.

In order for senior plant engineers to identify the root cause of machine failures and proactively plan corrections and upgrades to equipment and maintenance programmes, it is essential that asset information is collected and used effectively. Capturing and documenting both current and historical data under an organisation's assets is a key component of a successful asset management programme. This enables an organisation to balance maximum performance and minimal timely maintenance to achieve cost and production goals.

Rather than used merely as a short-term solution to maintenance issues, a successful AEO strategy needs to be sustainable over the long term in order to generate the most beneficial results. A holistic approach enables effective plant-wide communication between machine operators, maintenance and engineering teams, as well as management, allowing informed decisions and improved utilisation of resources. Top-level business planning, system-wide analysis, and a shift from largely reactive repairs to an optimised mix of planned, predictive maintenance need to be adopted.

Integrating condition based maintenance programmes into an overall AEO strategy enables increased mean time between failures (MTBF) to be achieved and, as a result, a significantly lower cost of ownership. With the latest advanced condition monitoring processes, machine vibration and wear levels can be reduced, extending the service life of plant assets, and minimising the frequency of unplanned downtime.

Asset Efficiency Optimisation (AEO) incorporates four key elements: maintenance strategy, work identification, work control, and work execution. Although all four elements should ideally be carried out simultaneously for maximum effect, the individual stages can be approached consecutively if time, money or resource constraints apply.

The first process in the programme, maintenance strategy, is the stage at which a business sets out its larger goals and objectives, assesses plant criticality and risk, and decides what the most important issues and priorities are. This is essential for a suitable and effective maintenance plan to be created, and a recognised and auditable company Asset Management strategy, which can be easily communicated throughout an organisation, is put into place.

This information is then put to use in the second stage - work identification, where critical plant information is gathered and analysed, allowing informed decisions to be made and corrective maintenance operations to be carried out. At this stage an industrial Decision Support System (iDSS), such as SKF's @ptitude system, can p[pjtgrewqrovide valuable support to senior maintenance engineers, by making relevant condition-based maintenance recommendations available online, as well asproviding access to a wealth of specific and expert knowledge on asset maintenance. Work requests are then submitted to a Computerised Maintenance Management System (CMMS), to be combined with other pre-determined planned and corrective maintenance activities.

The third stage, work control, relies heavily on the priorities and structure determined during stages one and two, allowing maintenance activity to be planned in detail and scheduled, with prioritised tasks, taking into account timescales, man-hours required, data feedback, and competence requirements. Effective planning at this stage, combined with good spares management, well-defined job plans and trained staff, allows resources to be utilised in the most efficient and productive way.

With these three components fully realised, the final stage, work execution, can be implemented, with detailed plans put into action and maintenance work being done. It is crucial that feedback is collected via post-maintenance testing in order for continuous improvement to be maintained and maximum return on investment to be achieved.

Through introducing a clearly structured and pro-active approach to condition monitoring, such as SKF's Asset Efficiency Optimisation, an effective and, important sustainable approach to plant maintenance can be established offering long term benefits for a company's bottom line. This integrated, holistic approach, that takes the requirements of the entire company' into account, significantly increases productivity and profitability by minimising unscheduled downtime and ultimately reducing maintenance costs.

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