Top 8 Reasons to Choose a Predictive Maintenance Strategy

Top 8 Reasons to choose a Predictive Maintenance Strategy

Predictive maintenance is a preventative maintenance program that is condition-driven, not relying solely on average-life statistics to schedule maintenance.
Using a number of indicators, such as direct monitoring of the mechanical condition and system efficiency, it aids in determining an accurate Mean Time Between Failure (MTBF), fixing only when something is requiring maintenance, or identifying areas of decreased efficiency across an entire plant.
In a paper titled “An Introduction to Predictive Maintenance” by Keith Mobley“, there was a survey conducted with 500 plants that have implemented predictive maintenance methods. From this survey, there is a clear and distinct return on investment through improvements in reliability, availability and operating costs. The plants in the survey include a broad cross- section of industries and the result is an indication of the types of improvements that can be expected

Based on the survey results, major improvements can be achieved in:

– Maintenance Costs

– Unscheduled machine failures

– Repair downtime

– Spare parts inventory

– Both direct and indirect overtime premiums

– Machine life

– Production

– Operator safety

– Product quality

– Overall profitability

1. Reduce Maintenance Costs by 50%

While every effort is made to assure the information in this document is accurate, I-care SPRL does not accept liability for any errors or mistakes that may arise.

A reduction in maintenance costs was significant for over 50% of the surveyed plants due to
a reduction in actual costs such as labor, material costs of repair, parts, tools and other
equipment required to maintain plant equipment.

2. Reduced Number of Catastrophic, Unexpected Machine Failures by 55%

In the study, machine failures before implementing a predictive maintenance program were
compared to machine failures for 2 years after implementation. There was a reduction of
55% in the number of catastrophic, unexpected machine failures, and it is projected that
over 90% reduction can be achieved if the study period were to extend for longer than 2
years.

3. Reduction in Mean Time to Repair (MTTR) by 60%

Regular monitoring and analysis of true machine condition using full spectrum condition
monitoring technology, identifies the specific failed component(s) in each machine, enabling
maintenance to more effectively plan repair. The capacity for accurately predetermining
specific repair requirements, provided a dramatic reduction in both repair time and costs.

4. Reduction in Spare Parts Inventory by over 30%

Knowing what spare parts are required and when, well ahead of time, provided the
surveyed plants with enough lead time to order spares and plan labor that they could
significantly reduce their level of spare parts inventory.

5. Increase in Useful Operating Life by 30%

Through implementation of predictive maintenance, the improvements in frequency of
repair, severity of machine damage and actual condition of machinery after repair were
substantial. These reductions then increase the operating life of plant equipment.

6. Determine the Condition of Installed Machinery during Commissioning

As well as predicting maintenance requirements of running equipment, predictive
maintenance technologies provide insights into potential future issues during
Commissioning. This provides an opportunity to quantify the purchased condition of new
equipment before acceptance and implement proactive maintenance actions to reduce
equipment infant mortality.

7. Powerful Operations Insight

Data obtained through the implementation of a Predictive Maintenance Program, provides
amazing insight for Operations to better plan plant outages. Even the reduction in the
number of days required for a plant shut can achieve significant cost savings.

8. High Quality Sensors – Lower Analysis Errors

Most hand-held data loggers and connected sensors provide time waveform high resolution
which enhances the vibration analyst’s capacity to make accurate determinations. However,
most often, wireless sensor systems are made as a commodity and sold at very cheap prices,
single axis, and with a lower resolution time waveform – therefore a lower capacity for
accurate fault determination.

CONCLUSION

The overall benefits achieved from implementing predictive maintenance have proven, in
many cases, to substantially improve the overall operation of manufacturing, processing,
mining and oil & gas plants. In all surveyed cases, the benefits achieved from using
predictive maintenance have offset the capital equipment costs required to implement the
program within the first three months.

Other benefits achieved through implementing Predictive Maintenance technology include:

– Excellent Reliability Improvement Tool
– Improved Product Quality – over 76% of surveyed plants reported improved quality as one of the reasons for implementation
– Asset Protection – more than 60% of plants surveyed included Asset Protection as one of the reasons for implementation
– ISO Certification – over 35% of plants surveyed included ISO Certification as one of the reasons for implementation
– Lower Insurance Rates – around 25% of plants surveyed indicated that Lower Insurance Rates were one of the reasons for implementation