Senseye announced today that it has joined the Partner EcoSphere at OSIsoft to deliver its automated condition monitoring product to help PI System customers on their digital transformation journey.

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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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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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Servitization allows you to get closer with your customers by providing your product as a service. Predictive maintenance helps ensure that you can deliver it.

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Predictive maintenance can result in avoiding between 30-50% of downtime that occurs during preventative maintenance but not many companies have adopted it.

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The crucial differences between Preventative and Predictive Maintenance and how you can save downtime and increase productivity when you forecast machine failure

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How does the IIoT (Industrial Internet of Things) help Predictive Maintenance? It can be used for prognostics to help avoid downtime and save money - simple!

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Forecasting machine failure sounds great but there can be some prerequisites. Here's our top three for you to check off to simplify things.

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