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The benefits of a holistic approach to plant maintenance

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Phil Burge, Marketing Manager at SKF, explains how a holistic approach to plant maintenance can have a significant impact on productivity and profitability.

Despite a widespread shift from reactive to more proactive programmes, maintenance continues to be perceived as an unavoidable expense in most cases. Across a wide range of industries, machinery needs continuous monitoring, checking, maintaining and repair work, all taking a bite out of a company's bottom line. However, this no longer needs to be the case. With a holistic approach to maintenance that involves managing both system reliability and risk assessment across an entire organisation, the efficiency of plant and equipment can be optimised, increasing productivity, and ultimately profitability.

Today it is generally understood that a proactive approach to maintenance is more effective than simply waiting for equipment to fail before taking action. Condition monitoring for predictive and preventative maintenance is now widely used throughout industry, with the long-term reliability of process systems depending on devices designed to allow plant operators to react to impending failure within the system being monitored.

Vibration, caused by damage to or wear of components, or the misalignment of rotating shafts, is a common problem in equipment such as pumps, fans and motors. In many instances, however, failure is due not to normal wear but by incorrect installation and maintenance of equipment and components. For example, it is common for shafts to be misaligned, for rotating parts to be incorrectly balanced, and for lubrication systems to be under-specified for the task in hand. In fact an estimated 14 per cent of all bearing failures are due to incorrect installation.

Asset Efficiency Optimisation

Many of these problems can easily be overcome by implementing best-practice procedures and using the appropriate testing equipment - such as alignment tools and automatic lubricators - during plant construction and routine maintenance. Using simple but effective techniques to monitor levels of vibration, it is possible to identify wear before it becomes a problem, and therefore implement an effective predictive maintenance programme.

For these practices to work most effectively, they need to be part of a holistic approach to plant maintenance that takes into account the needs of equipment across the entire organisation. This increasingly popular strategy is known as asset efficiency optimisation (AEO), which has been developed to enable companies to minimise costs and maximise profitability efficiently by achieving consistently high levels of uptime and productivity.

AEO creates a dynamic programme that combines the advantages of traditional techniques with procedures that identify the root causes of machine and process problems and empower front-line operators to take 'ownership' of their machinery, identifying and communicating information to a plant-wide team to maximise uptime. AEO allows businesses to analyse, assess, and manage maintenance issues simultaneously, making it extremely efficient and cost effective.

Data management

Information is key to a successful AEO strategy. 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 on an organisation's assets is a vital component of a successful asset management programme, and can enable an organisation to balance maximum performance and minimal timely maintenance to achieve its cost and production goals.

Importantly, AEO provides a sustainable approach to maintenance rather than a series of short-term fixes. A holistic approach enables effective plant-wide communication between machine operators, maintenance and engineering teams, and management, allowing informed decisions to be made and better utilisation of resources to be achieved. Everything from top-level business planning, system-wide analysis, and a shift from largely reactive repairs to an optimised mix of planned, predictive maintenance needs to be adopted.

Integrating condition-based maintenance programmes into an overall AEO strategy enables mean time between failures (MTBF) to be increased and, as a result, a significantly lower cost of ownership is achieved. 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.

Four elements

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 sets in place a recognised and auditable company asset management strategy, which can be easily communicated throughout the organisation.

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 the corrective maintenance operations to be carried out. At this stage an industrial Decision Support System (iDSS), such as SKF's @ptitude system, can provide valuable support to senior maintenance engineers by making relevant condition-based maintenance recommendations available online, as well as providing 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 tasks prioritised, 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 carried out. 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.

Conclusion

Asset Efficiency Optimisation can have a dramatic effect on a company's productivity and profitability by enabling maintenance to be both planned and conducted more efficiently and cost-effectively. With a holistic maintenance strategy in place, involving everyone from senior managers to plant operators, communication can be increased and information collected and acted upon much more quickly and effectively. The outcome is a sustainable condition monitoring and predictive maintenance programme that maximises output and cuts downtime and costs. As a result, maintenance ceases to be an unavoidable expense and instead becomes an opportunity to increase profits.

 
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