How predictive analytics can support manufacturing maintenance teams

Manufacturing has long been an industry that places peak performance, operational efficiency and quality targets at the top of their agenda. Leveraging data and the industrial Internet of Things (IIoT) can support these objectives.

Another digital opportunity, faster to execute might be closer than you think, as manufacturers now take advantage of predictive analytics to accelerate their digital transformation journeys.

At Senseye, we see the rise of smart factories happening first hand. Manufacturers are making ever greater use of data with predictive analytics solutions, like Senseye PdM. They combine data from different existing sources, directly from machines, maintenance systems or the IIoT to make production processes more efficient, agile, and responsive.

Predictive analytics supports another corporate objective: enabling predictive maintenance. This practice relies on gathering and analysing data coming from different sources to spot signals of upcoming asset failures, while providing all the insight needed for engineers to investigate and determine the best actions to take.

Predictive maintenance was once a time-consuming, costly exercise. It couldn’t scale. It was an exhausting manual exercise, customised for each monitored machine, which relied on condition monitoring experts to take readings from each asset; and review the information they gathered, to spot the failure signals. It was applied for critical assets where regulations demanded it.

Now, through greater use of specialised solutions like Senseye PdM, we see the democratisation of predictive maintenance, which is accelerating its global adoption.

For many large-scale manufacturers, moving to predictive analytics simply means getting the most from their data while enabling predictive maintenance. Around two-thirds of manufacturers today are already gathering massive amounts of information from their production environments. All too often, this data remains in its silos and is not used to its fullest potential.

This makes predictive analytics, the natural next step, enabling predictive maintenance to drive efficiency and improving the bottom line, for any manufacturer's digital transformation journey.

Since 2014, Senseye has supported Fortune 500 companies around the world with predictive analytics, delivering predictive maintenance at scale.

The author, Rob Russell, is Chief Technology Officer at Senseye.

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