Start benefiting from predictive maintenance straight away

Getting started with predictive maintenance is straightforward – it involves understanding your organization’s maintenance mix.

We’ve outlined the standard maintenance approaches and methodologies below: corrective, preventative, condition-based, and predictive to help you understand key industry considerations for the methods your organization’s currently using to achieve efficient maintenance.

Every organization will have a unique blend, using multiple maintenance methodologies at the same time, each to a greater or lesser degree. No matter where you are in the mix, no matter which methods you use more than others, the benefits of achieving scalable predictive maintenance are clear and can be achieved quickly from any starting point.

What is it?

Corrective maintenance (often referred to as reactive maintenance) is carried out after a failure has been detected. Usually this is a reactive approach for when your machinery has already failed, you will carry out corrective maintenance to repair, restore or replace your machine back to its operational state.

When is it used?

This reactive action is performed when a problem has already occurred, during an emergency repair, or during a routine maintenance period. It is the most basic form of maintenance strategy, requiring little to no advance planning or management overhead.

Key considerations

Whilst corrective maintenance means minimal planning and lower immediate operational costs, it does expose organizations to extensive downtime, unpredictable fluctuations in output, as well as higher long-term running costs.

Discover more

What is it?

Preventative maintenance aims to maintain the machine in accordance with a prescribed time schedule to reduce the probability of failure. Machinery manufacturers will often provide specific Mean Time Between Failure (MTBF) information, identifying the average length of time between failures of a machine and its components. Alternately a suitable maintenance schedule, using a locally generated MTBF, may be derived by analyzing historic maintenance events and records.

When is it used?

Planned maintenance activities are scheduled for when the MTBF number is approaching or has been exceeded. At this point, machinery is inspected, serviced, repaired, restored, or has components replaced on a calendar basis or as inspection warrants.

Key considerations

The saying goes “over-maintenance is cheaper than failure”, in theory preventative maintenance can reduce the amount of unplanned downtime and reduce operational risk since components should always be in good condition. However, it does not consider actual usage of the machine and cannot indicate potential failure points, often causing more downtime due to both planned and unplanned maintenance.

Discover more

What is it?

Condition-based maintenance (CBM) relies on using sensing equipment to monitor physical parameters that relate to the actual condition of a machine. These are the vital signs of machine health, like vibration, current and acoustic signature. This data can be offline (handheld device inspections) or online (real-time data collection) and once collected is interpreted by expert human operators, often assisted by data analytics systems, to help understand when to schedule maintenance time.

When is it used?

CBM allows organizations to have deeper information on the current condition of the machinery on which their business depends. This allows experienced maintainers to diagnose machinery issues more precisely and start to plan as to when the optimum time for maintenance may be.

Key considerations

Condition based maintenance comes with the human burden of data collection and analysis. It often requires a high level of knowledge and training and the number of machines that can be monitored can be limited by the availability of specialist resource.

Discover more

What is it?

Predictive Maintenance uses Artificial Intelligence (AI) to automatically interpret condition monitoring data to understand current machine condition and forecast future condition and timeframes. Some solutions can also prescribe relevant maintenance actions. This liberates maintenance and operations teams to plan much more effectively and monitor more machines.

When is it used?

The technology that drives predictive maintenance provides a safety-net regardless of other maintenance strategies and maturity. It provides advanced insights that are easily understood and actionable and does not require maintainers to spend their time analyzing raw condition information. It is particularly useful to reduce management overhead and allow efficient forward planning and resource use.

Key considerations

Predictive and prescriptive maintenance require suitable machine condition data which can come from investment in Industry 4.0 / Industrial IoT technologies. It’s a more efficient approach than other methodologies as maintenance can be planned to happen before any significant damage occurs and is based on the real condition of that machine, taking into account its usage cycle and not just its operating time.

Discover more

The cost of inefficient maintenance can be very high

$532,000

average cost of an hour’s unplanned downtime for large firms in the manufacturing and industrial sectors

27hrs

average total duration of monthly unplanned downtime per plant in those sectors - more than a full day in lost production

$172m

estimated annual cost to a large plant of unplanned downtime

$864bn

estimated annual cost of unplanned downtime in manufacturing and industrial plants for firms in the Fortune Global 500

New call-to-action

Ready to learn more?

Get downtime down, using Senseye PdM to power your predictive maintenance programme today.

Get in contact to share your requirements and discover how much Senseye PdM could improve your operations.

Join a free webinar

We run a regular Predictive Maintenance webinar, Q&A and live demo, on the last Thursday of every month. Register now to be sent information on joining the upcoming session or take a look at all our other resources.