Prevent & Predict Next Steps

Some great advice to help you minimise downtime.

Prevent & Predict Next Steps

Choosing the best preventative and predictive maintenance methods for the application is key to an effective maintenance strategy.

In today’s climate there are increased output pressures on manufacturing to keep up with modern demand - exacerbated in the post-pandemic world. Therefore, creating efficiencies is the Holy Grail, while unplanned downtime is the arch enemy. Those maintenance teams still operating on a reactive basis will undoubtedly fall victim to unplanned downtime – and the varied frequency and unpredictability of this will cause hindrance and detriment to any manufacturing operation.

With preventative and predictive maintenance methods and equipment, and advanced technology in the Industrial Internet of Things (IIoT) sphere now widely available, it’s difficult to know where to start or how to implement this in an effective maintenance strategy. So whether you’re at the beginning of your proactive maintenance strategy journey, or have made the leap and want to understand more about how to make use of the many aids available, we’ve highlighted some of the key considerations.

Monitoring is key to effective maintenance

Preventative maintenance methods such as calendar or usage-based planned interventions are effective in helping to prolong the life of equipment and minimise risk of unplanned downtime. This can include activities such as applying lubrication at the right intervals, and replacing parts prone to failure. Additionally, upgrading components to more durable solutions can help avoid interventions. For example, replacing electromechanical relays with solid state versions, fitting anti-vibration mounts to reduce wear damage and fitting air pressure regulators to save energy and extend component life are all effective, relatively low cost and sensible measures to take.

Thermal imaging

Reactive activities can also be avoided to some extent, by monitoring the process and predicting when an intervention is necessary. For electrical maintenance, consider equipment such as handheld thermal imaging cameras, which can be used to help monitor temperatures, and identify hot spots that can denote issues such as faulty insulation and electrical switch gear issues, and near capacity fuses. Components including sensors, valves and even PLC I/O can degrade over time, causing problems including process accuracy and stability. Monitor performance using process calibrators.

Similarly, to get advance warning of mechanical failures, portable vibration analysis equipment can be used to make repeatable, severity-scaled readings of overall vibration and bearing condition.

Excessive wear can be a primary cause of failure for gearboxes. Oil and grease analysis can be performed to understand lubrication condition, including contamination and debris content, allowing appropriate action to avoid failures and downtime.

These are all great steps to hone your processes - but embracing the Industrial Internet of Things, (IIoT) will allow you to really step things up.

Sensor technology can be the start of the predictive maintenance journey

Before getting in a spin about Industry 4.0 and the complexities of IIoT, there’s no need to try and run before you can walk. Start small, and consider where to deploy the right pieces of technology to best mitigate negative impact on your operations. Sensor technology has become much more accessible from a product price and implementation perspective, and provides a good ‘toe in the water’ approach. Identify where your data sets might need enhancing to best avoid failures – whether that be in the areas of vibration, electrical energy, temperature or pressure – and look to strengthen existing data sets with the use of sensors to gather further information in real-time. Focus only on collecting the data you need – big data is a well-used term, but by sticking at first to small data, gleaning actionable insights will be more achievable, which is critical in the predictive maintenance mission.

Setting parameters of what falls into normal or abnormal operation means that abnormal can be quickly flagged and used as the trigger for deeper investigation into a potential issue. Many organisations already have more data than they think they have, and this can be enhanced with frequent real-time data that can be gathered using sensors and fed into a simple recording method such as Excel or a more sophisticated analysis tool.


Often organisations are concerned about implementing IIoT due to issues including cyber-security, and are reluctant to expand the use of it where integration with existing solutions seems complicated. There isn’t an ideal solution or a one-size-fits-all approach at the moment, so the best thing to do is to seek help from a variety of information resources, from online portals and platforms such as LinkedIn, through to knowledgeable organisations such as RS – we hold an array of technical expertise both within our business and in conjunction with key partners.

The move beyond reactive and preventative maintenance strategies to truly predictive using IIoT will reduce downtime and increase efficiencies - boosting the competitiveness of your organisation. While a daunting prospect, to freeze and do nothing isn’t an option.