Maintenance strategy for Industry 4.0

For years, Asset intensive organisations such as Manufacturing, Oil & Gas, Energy & Infrastructure, have all been seeking the holy grail of maintenance.

However through time maintenance strategies have evolved due to necessities from Coorective Maintenance such as Run to failure, Fix on Break to Preventative maintenance, Time base to Condition Monitoring and Predictive Maintenance.

In a recent market study conducted only 18% of equipment has failed due to its age, while 82% of failures occur randomly. It proves that a time-based approach is not cost-effective – a piece of equipment gets maintained irrespective of the actual need.

Now with the proliferation of sensors & IoT, organisations can have access to vast amount of data only with access to be simplified through cloud. Predictive maintenance as we know is evolving with prescriptive analytics at a fast pace. What has become evident is there is not one size fit all, each strategy will be entirely be dependent on the business & process needs.

An example of Oil and Gas company who facing an unplanned breakdown could costs millions in lost production per day and additional cost to business while fixing the problem. Predictive Analytics would be used predict the event ahead of time and Prescriptive Maintenace to state what would be next course action as a result of prediction.

On the contrary, changing a lightbulb based on Building Management systems data in a non critical area requires no prediction algorithm to validate the ROI, However the lightbulb asset in a critical health and safety zone could change the priority of the maintenance strategy deployed.

Establishing the right maintenance strategy and aligning your IIoT & analytics strategy early on will pave quick dividend on the ROI on Industry4.0.

According to the McKinsey report, IoT-based predictive maintenance extends equipment’s life, helps to eliminate as much as 30 percent of the time-based maintenance routine, and reduces equipment downtime by 50 percent. For a mature and reliable predictive maintenance solution, however, a thought-out architecture with the focus on machine learning is crucial.

It is vital understanding the right maintenance strategy to align with your organisation.

Contact us to find out how we can help at Prognostic.

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