Monitor your asset health

⇨ Human-collected maintenance data, often overlooked, can provide valuable insights into asset health if combined effectively with modern condition monitoring tools.

⇨ Automation through machine learning and AI can enhance predictive insights for asset management when fed with comprehensive condition monitoring data.

⇨ Investing in proper data management and leveraging technician-collected information can lead to better context and accuracy in monitoring asset health, potentially unlocking greater operational benefits.

With all the options available for monitoring your asset health, are you forgetting an important one you are already paying for right now?

Condition monitoring such as oil sample analysis, vehicle information systems, IOT (internet of things) sensors and others are all great tools to indicate asset health.

Personally, I enjoy using and have always embraced technology. It’s great to see that the reality in 2023 is that machine learning and AI solutions, if given access to the right amount of condition monitoring data, over time are able to automate predictive insights that can improve asset management outcomes.

For many years valuable information has been collected by humans every day on maintenance work orders and inspections (that would be via your technicians). In contrast to condition monitoring data sources, it is typically only utilised as a “one point of time” insight to your equipment health.

For example:

A typical service will have approximately 15-20 readings recorded on it by a technician.

Only one or two readings,typically the engine hours or other will be available as measurement points within the CMMS.

The small number is often due to the need to set up these measuring points in the CMMS for each asset class and the administration to double enter these back into the CMMS after the work order is complete.

These readings have already been identified as key indicators to asset health. That is why they are on the service sheets to check!

They can include for example:

• Exhaust gas and back pressure tests
• Fire suppression pressure
• Gearbox temperatures
• Brake thickness
• Brake accumulator pressure test
• Tyre pressure and depth
• Mag plugs test results
• Gap Clearances
• Engine hours

Every site, is already paying for this data to be collected on paper-based sheets and then simply scans the completed work order and files most of it it away.

Speaking with a vendor recently that provides a really good solution like this, I posed the question:

“How do you utilise in your solution the history of the human collected information that is captured every day on maintenance work orders, inspections and equipment prestarts?”

It is not something they had considered, however together, we are now looking at opportunities to combine it with their other data sources, to further enhance the results.

During the conversation it was suggested that human collected information is often inaccurate and as such not valid.

As a former maintenance technician (albeit many years ago), I would suggest that a trained technician given the right tools and process, (hint: this is not a paper sheet and pen) will not only record the reading correctly, they will also be able to provide real life context that automating that reading does not achieve.

What benefits could you gain today by unlocking insights from what you have?

Some ideas our clients have helped form are below

At Obzervr, after 5 years of working in mining maintenance, heavy industry, and rail, we understand the constant balancing of priorities, the working environment and challenges that presents.

If you are considering a better way of working, we would be happy to spend 30 minutes with you and share some real-life examples, of how leveraging digital technology has helped similar businesses, make substantial improvements.

Feel free to reach out at anytime