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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Our CTO, Robert Russell, features in August’s edition of Processing Magazine where he highlights the operational challenges of scaling predictive maintenance & how automating analytic tasks allows organizations to expand the coverage of its assets without significantly increasing costs.

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Our CEO, Simon Kampa, recently wrote an article for Smart Industry which explores the challenges of deploying traditional predictive maintenance at scale, and how artificial intelligence is enabling wider and faster deployment.

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2017 was an exciting year for Industry 4.0, with it starting to gain some mainstream press attention. The Senseye founders give their outlook for 2018.

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Senseye has joined forces with PTC to offer easy to use predictive maintenance to users of the leading ThingWorx® industrial innovation platform

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Maintenance practises have changed significant in a fairly short time. No planning has given way to scheduled planning, giving way to predictive maintenance.

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To date, the manufacturing sector has benefited minimally from predictive maintenance due to difficulties with the scalability of manual analysis. Senseye changes this - cloud based predictive maintenance solution, with a clear, concise user interface.

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It's crucial to get the data correct for a predictive maintenance project in order to be able to accurately detect machine failure. 6 tips on getting good data.

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Reducing machine downtime can come through condition monitoring (current health) and prognostics (remaining useful life), key for predictive maintenance

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