Today around two-thirds of manufacturers are gathering data from their production environments, yet relatively few are using it to improve processes or boost productivity and yield, argues Dr Simon Kampa.

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For manufacturers, leveraging data and analytics can deliver substantial returns. We’ve helped large scale manufacturers halve their levels of unplanned downtime and cut their maintenance costs by around 40%. The reduction in unplanned downtime tends to be the most significant saving here. Every minute that critical machinery is offline can cost big factories tens of thousands of pounds, so the returns that can be achieved by preventing this are substantial.

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Senseye, a provider of predictive maintenance analytics, today announced that it has partnered with the North East Automotive Alliance (NEAA), to provide its predictive maintenance software to the automotive sector in the North East of England.

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Whether you are new or already familiar with Predictive Maintenance (PdM) the Senseye team have put together a handy A to Z guide of some of the commonly used words and phrases associated with the maintenance practice.

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Factories are no longer simply a mass of machinery operating as a series of siloed production lines. Instead, manufacturing executives and engineers manage interconnected networks of moving parts, something more akin to a living organism, that can be trained and fine-tuned to optimise performance.

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The idea of predictive maintenance can be daunting for some manufacturers as it represents a significant cultural shift in how they plan, prioritize and perform maintenance activities. The benefits of doing so can be huge but if this shift isn’t properly managed, there can be serious consequences.

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Smart factories are rapidly becoming the future of manufacturing, offering a new level of efficiency and productivity to those investing in them. Industry 4.0, combined with increasingly sophisticated analytics, is playing a huge role in driving the smart factory movement.

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2019 marks an inflection point in the maturity of Industry 4.0 and the application of real-world predictive maintenance. As a provider of industrial predictive maintenance analytics to Fortune 500 companies, it is very much our area of expertise. Read our predictions for 2019.

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Our CEO, Simon Kampa, recently featured in IMPO magazine where he provides a five-point plan outlining how manufacturing environments of all shapes and sizes can achieve substantial improvements in productivity and efficiency by implementing predictive maintenance at scale.

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Our CEO, Simon Kampa, recently featured in IMPO magazine where he explains how artificial intelligence has helped increase the adoption of predictive maintenance by manufacturers and helped to fill maintenance skills gaps and boost productivity.

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