What is predictive maintenance?

As the name implies, predictive maintenance anticipates equipment problems rather than reacting to them. The aim is to predict when equipment failure might occur, and then to prevent that failure by addressing the problem immediately.

Conditions in machinery can be carefully monitored in order to identify a significant change which is indicative of a developing fault. These conditions can include temperature, lubricant conditions, vibration readings, ultrasonic sound detection, liquid or gas pressure and more.

Real-time data is gathered from machinery to notify workers when something is starting to go wrong. It enables technicians to get ahead of problems before they cause any costly downtime.

The most comprehensive predictive maintenance systems use sensors mounted on machinery which feed data directly into a system which can alert workers of a developing problem. But it is possible to gather data using hand-held multimeters, or simply record the readings from meters built into the asset. The software needed to analyse the data collected is now more affordable than ever, meaning predictive maintenance is no longer the preserve of the largest corporations.

Practical examples of using condition monitoring and predictive maintenance:

  • Using infrared cameras to monitor wear on bearings or motor heat
  • Using vibration analysis to monitor internal components – machinery problems occur at specific frequencies, so vibration analysis can pinpoint problems.

In each case, identifying potential failures ahead of time, and replacing the part in question before you get to breakdown situation can contribute to the significant potential benefits of a predictive maintenance approach.

The benefits of predictive maintenance

  • Dramatic reduction in scheduled and unscheduled downtime – maintenance can be scheduled during non-working hours and the machine is repaired before it fails.
  • Reduced maintenance costs – work is performed only when it’s needed based on actual conditions and data.
  • Reduced spare parts inventory – when maintenance activities are predicted, the components needed to support those activities can also be predicted, allowing parts to be ordered only when needed.
  • Cost savings – less down time, a reduction in equipment cost, reduced labour costs involved in maintenance work and fewer emergency call outs all add up to significant savings.
  • Extended lifecycle of monitored equipment – by preventing critical failure key equipment should last longer, avoiding the cost and disruption of installing a replacement.
  • Less guess work – unlike preventative maintenance which relies on average life expectancy statistics, maintenance tasks can now be based around the actual usage of the asset.
  • Increased productivity – precise repair tasks are identified, as well as parts, tools and support needed to correct the problem, resulting in much more efficient use of time.
  • Improved quality – predictive maintenance can detect and correct product quality problems, leading to an overall improvement in output quality.
  • ISO certification – part of the certification process for ISO 9000 includes criteria that seek to ensure equipment reliability and consistent production of first-quality products. Predictive maintenance helps maintain consistent quality performance levels.
  • Feeling of reliability and safety for staff – predictive maintenance reduces the likelihood of a machine experiencing a catastrophic failure, and this results in an improvement in worker safety. There have been cases of bodily injury and even death due to sudden machine failures.
  • Verification of new equipment condition – using predictive maintenance tools and techniques, it’s possible to verify the purchased condition of new equipment before acceptance. If any problems are identified, the vendor has to correct before the invoice has been paid.

The cumulative effect of all of these benefits can result in a significant improvement in overall profitability. Many industries report between 2-10% productivity increases due to predictive maintenance practices.

What to do now

The overwhelming outcome from research into the effectiveness of predictive maintenance is that the benefits outweigh the costs of implementation in the vast majority of cases. As such, predictive maintenance should form an important part of running a successful maintenance management operation for most manufacturing businesses.

The software and technology associated with predictive maintenance has become affordable for almost any size company that wants to be as proactive as possible with maintenance work. If you have lots of machinery that is critical to operations, there is probably a very good case for predictive maintenance. For a predictive maintenance programme to truly succeed, it’s important to focus the programme on total-plant optimisation, and proper training for technicians and analysts.

To help you decide, determine the cost of machine downtime and thenweigh that against the cost of implementing predictive maintenance practices. If the figures stack up, the next step is to ensure the critical data you need is, or can be, available for analysis. You need to understand what conditions you want to monitor for continuous analysis, and then put the measures in place to facilitate this.

If you need any help or are considering this approach, feel free to get in touch and we can advise you on whether this approach could work for you and/or form part of your overall maintenance approach.