When we speak of different types of maintenance, two main types come to mind: corrective maintenance and preventive maintenance. And, naturally, we associate preventive maintenance with something positive and one that should be given priority, while corrective maintenance is seen as something that is not so good, and that should be applied only in cases of emergency. However, a third type, known as predictive maintenance, which is often undervalued by companies, has proven benefits that will surprise you.

Predictive maintenance, a corporate philosophy

Predictive maintenance is a methodology or, in other words, a corporate philosophy that takes into account the state of a company’s equipment. Predictive maintenance periodically monitors equipment based on the analysis of data collected through monitoring or on-site inspections. One of the objectives of predictive maintenance is the timely verification of equipment in order to anticipate eventual problems that may lead to higher costs with corrective maintenance. However, the main objective is to optimize the use of machines and equipment, increasing productivity and reducing costs for companies.

Predictive maintenance is a valuable practice for building a comprehensive maintenance management program for an industrial plant, but it does not completely replace more traditional maintenance management methods. While traditional programs rely on servicing routines for all equipment and a rapid response to unexpected failures, predictive maintenance schedules specific maintenance tasks only when they are actually needed.

It does not completely eliminate all aspects of traditional preventive and corrective maintenance programs, but it can reduce the number of unexpected failures, as well as provide a more reliable scheduling tool for routine preventive maintenance tasks.

The premise of predictive maintenance is that regular monitoring of the actual mechanical conditions of equipment and the operating performance of process systems will provide the maximum interval between repairs. It will also minimize the frequency and cost of unscheduled downtimes resulting from equipment failure and will improve the overall availability of equipment in operating plants. In fact, predictive maintenance should be seen as a preventive maintenance program triggered by a condition.

But first let’s look at the benefits and explain them a little better. All of them are the result of proven improvements after implementations and studies in various companies.

Reduction in maintenance costs

The real costs normally associated with maintenance operations can be reduced by more than 50%. Comparison of maintenance costs include actual labor and maintenance department overhead, as well as the actual cost of replacement parts, tools and other equipment required to maintain the equipment.

Reduction in machine failures

Regular monitoring of the actual conditions of the equipment and process systems can reduce the number of unexpected and catastrophic equipment failures by approximately 55%. The comparison uses the frequency of unexpected equipment failure prior to the implementation of the predictive maintenance program and the failure rate during a two-year period following the inclusion of condition monitoring in the program. Projections indicate that reductions of as much as 90% can be achieved!

Reduced downtime for repairs

Predictive maintenance reduces the actual time required to repair or recondition plant equipment. You can reduce the mean time to repair (MTTR) by 60%. To determine the average improvement, the actual repair times before the predictive maintenance program are compared to the actual repair time after one year of operation using predictive maintenance management techniques. Regular monitoring and analysis of machine conditions identify the specific faulty components on each machine and enables maintenance personnel to plan each repair.

Reduced stock of spare parts

The ability to pre-determine defective parts needing repair, tools and required labor skills ensure a reduction in both repair time and costs. The costs involved in stocking spare parts can be reduced by more than 30%. Rather than purchasing all the spare parts for stock, industrial plants have enough time to order the spare or replacement parts as needed.

Increased service life of parts

Preventing catastrophic failures and early detection of machine and system problems increase the service life of industrial plant machinery by an average of 30%. The increase in machine service life is a projection based on five years of operation after implementation of a predictive maintenance program. The calculation includes: frequency of repairs, severity of machine damage and the actual condition of the machinery after repairs. A condition-based predictive maintenance program avoids serious damage to equipment, as well as other plant systems. This reduction in the severity of damages increases the service life of plant equipment, in addition to preventing the propagation of defects.

A side benefit of predictive maintenance is the automatic ability to estimate the mean time between failures (MTBF). This statistic provides the means to determine the most cost-effective time to replace machinery, rather than continually absorbing the high maintenance costs. The MTBF of plant equipment is reduced every time a major repair or reconditioning occurs. Predictive maintenance will automatically reduce the MTBF over the service life of the machine. When the MTBF reaches the point where maintenance and continuing operation costs exceed replacement costs, the machine should be replaced.

Increased production

The availability of process systems increases after the implementation of a condition-based predictive maintenance program. The increase can be as much as 30%. The improvement is based strictly on machine availability and does not include improved process returns. However, a complete predictive program, which includes process parameter monitoring, can also improve the operating efficiency and, therefore, the productivity of manufacturing and processing plants.

Improved operator safety

Early warning of machine and system problems reduces the risk of destructive failures, which can lead to personal injury or death. This benefit has been supported by several insurance companies, which have offered benefit reductions for factories that have a condition-based predictive maintenance program.

Verification of repairs

Vibration analysis can be used to determine whether repairs to existing machinery have corrected the identified problems and/or led to additional abnormal behavior before the system starts up again. This eliminates the need for a second shutdown, which is often necessary to correct inadequate or incomplete repairs. Data obtained in a predictive maintenance program can be used to schedule plant shutdowns. Many industries try to fix major problems or schedule preventive maintenance servicing during annual maintenance shutdowns. Predictive data can provide the information necessary to plan for specific repairs, as well as other activities during the shutdown.

Overall profits

The benefits of predictive maintenance management substantially improve the overall operation of manufacturing and processing plants. Benefits derived from the use of condition-based management offset the capital cost of the equipment required to implement the program within the first three months. The use of predictive maintenance techniques, based on data collection, further reduces the annual operating costs of predictive maintenance methods. In this way, any factory can obtain effective implementation in costs by adopting this type of maintenance management program.

Although predictive maintenance is a proven philosophy, with many success stories, some implementations do fail as well. The main reason for this is the lack of planning and management support, which is critical to any successful program.

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Tobias Schroeder

Author

Tobias Schroeder

MBA in Strategic Management from UFPR. Business and market analyst at SoftExpert, a software provider for enterprise-wide business processes automation, improvement, compliance management and corporate governance.

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