As factories become smarter and organizations embrace the benefits of digital transformation, it brings with it many new opportunities and new positive ways of working.

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As the investment in digital transformation projects continues to grow, so does the number of failed initiatives. How can companies maximize their chances of success?

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Senseye has started Senseye Hack Life Days, making available to all employees the same chance to grow and contribute to our communities. See what they did!

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Senseye announces a strategic partnership with Malone Group to support the deployment of its predictive maintenance software in the UK, Ireland and Canada.

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The world of data science is full of models that struggle to deliver results in real-world environments. So, what is the best approach?

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Running an Initial Deployment (ID) is a critical exercise. We have put together five steps to assist in planning for an ID

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Challenge drives innovation. For offshore oil & gas, the challenge is to achieve the right balance between uptime and output without delaying maintenance.

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Our top five predictions for the manufacturing sector in 2020 will provide some useful indication for what to expect

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Senseye is working with Ultimo Software Solutions to integrate Senseye’s predictive maintenance (PdM) with Ultimo’s Enterprise Asset Management System

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Senseye today announced that its suite of technologies and methodologies are being rolled out in automotive manufacturing facilities in the U.S.

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Senseye today announced that its Senseye PdM technology suite will be made available through FANUC’s ‘FIELD system’ Industrial IoT (IIoT) platform.

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Senseye today announced that it has opened a new regional office in North America to support its customers and partners throughout the Americas.

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Senseye today announced that it has appointed industry specialist Barry Stott to lead its activities in the oil and gas sector globally.

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Senseye, the industrial software company & member of the OSIsoft Partner EcoSphere, will be a sponsor at the PI World Conference in Gothenburg, Sweden.

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Senseye, which is experiencing booming demand across Europe, has bolstered its team of commercial and industrial experts and opened a new office in Germany earlier this year to boost its support for clients in German speaking countries.

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Chosen by top UK-based entrepreneurs, the Startups 100 Judges’ Picks have been selected to reflect some of the top trends in this year’s list.

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Condition monitoring has evolved over the past 30 years.

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Senseye announced today that it has recruited Wakako Yamaguchi to expand its business activities in Japan. Wakako will lead Senseye’s sales activities in Japan and provide account management support to its customers in the country.

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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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Senseye, a provider of predictive maintenance software, today announced that it has appointed Peter Livaudais to lead its operations in France, Belgium, Netherlands, Luxembourg and the French-speaking areas of Switzerland.

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Digital twins are virtual models of real life assets or production operations. They can be powerful weapons in the emerging armory of the Industry 4.0 but face a major hurdle in terms of scalability...

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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, which was made a MindSphere Gold partner in August 2018, first provided its software to MindSphere users in June 2018, when it was made available as a complementary service that could be connected to the operating system. This new version of Senseye’s application was developed specifically for MindSphere and is hosted within the operating environment itself.

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Senseye, which uses machine learning to automate condition monitoring and prognostics analysis, has translated its industrial operations software tool into five additional languages. Previously available in English only, Senseye can now be used on the shop-floor by maintenance and operations people that speak French, German, Japanese, Russian and Spanish to cater to existing customers, with additional languages being added.

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What do your manufacturing customers really want? It’s certainly nice for them to have the most nimble robots or the fastest machines, but such assets are only a means to an end. What all organizations really want is a guarantee that they can keep their operations working at optimum efficiency to support their key business objectives. That's where servitization comes in.

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What is the next step in the world of predictive maintenance? The answer: prognostics. Prognostics is the science of forecasting when your assets will stop being able to perform their intended functions. With prognostics in place you can properly perform PdM which is undoubtedly the future of condition monitoring.

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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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Experienced sales leader joins Senseye as Managing Director for DACH region.

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Senseye, a provider of predictive maintenance analytics, and Iconsys, the manufacturing systems integrator, today announced a new alliance to help industrial companies boost operational efficiency and profitability using Industry 4.0 technologies.

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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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Servitization is becoming an increasingly common term for manufacturers around the world. However, a clear understanding of what servitization is & how it affects manufacturers is much harder to come by. We’ve produced a white paper to demystify the subject. For those on the go, here’s the TL;DR.

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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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In a competitive marketplace enhancing machine reliability by implementing a condition monitoring program can make all the difference. But realizing your ambitions takes planning, commitment & continuous improvement. We look at the common pitfalls & provide ways you can realize its potential.

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Digitalization is the topic of the moment, and Industry 4.0 is at the heart of this for more efficient, cost effective factories. We're seeing an increase in the number of times this job title is cropping up and it shows a general increase in interest in businesses adapting for servitization.

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Making the decision to transition to automated condition monitoring shouldn’t be taken lightly. Far from a standalone maintenance project, automatic condition monitoring requires a shift in the entire organizational culture to support dramatic process, attitude and skillset changes.

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Senseye, a leading provider of predictive maintenance analytics, today announced a new partnership with Siemens to make Senseye’s award-winning condition monitoring and prognostic software available to manufacturers through the MindSphere Industrial Internet of Things operating system.

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Reducing unplanned downtime in factories is crucial to reducing overall maintenance spend and the total cost of asset ownership. Achieving this at scale however is a significant challenge and can only be achieved through the intelligent use of machine learning driven predictive maintenance solutions

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There are subtle but crucial differences between detection, diagnostics and prognostics when discussing machine health. Whilst you don't need to know the details, it's important to understand the differences to apply to your own industrial condition monitoring project for maximum benefit and ROI.

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The Internet of Things has a lot of promises associated with it, relating to how much it will improve our lives. Manufacturing will see the the best improvements.

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Industry 4.0 has often been critisized from a security point of view but is this really fair? Often the security issues such as Meltdown and Spectre are within.

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For 2018, Senseye is unveiling several exciting upgrades to its award-winning predictive maintenance software, further automating machine prognostics analysis.

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Is Industry 4.0 secure?

November 14, 2017

The security of the IoT / Industry 4.0 is a HUGE topic. Here we distil the really important things that you need to consider when exploring this topic.

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Prognostics is particularly exciting as it means understanding the Remaining Useful Life of your machinery however it's easy to get wrong and be unsuccessful.

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Analysing condition monitoring data manually is beneficial but this method limits scalability whilst coming with great expense. Automated is best but how / when

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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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Investing the correct amount in condition monitoring can be a challenge as it's easy to spend too much and be disappointed with the results.

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

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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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The hype around Predictive Analytics seems never ending. Yet it has some serious limitations when it comes to predicting machine failure and avoiding downtime.

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Senseye, the Uptime-as-a-Service leader today announced the launch of the next generation of predictive maintenance software to include remaining useful life

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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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Different techniques come under the label 'condition monitoring'. In this overview we explore where it came from, what is done and how effective it is.

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Prognostics is a relatively new term in industry and it's key to predictive maintenance. It all comes down to calculating the remaining useful life of machines.

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Prognostics is the future of condition monitoring, telling you when your machine will fail AND what condition it is now in. Download our FREE white paper!

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Implementing Industry 4.0 can be costly and distracting but it doesn't have to be. We've listed 4 things to help you keep on top of your Industrial IoT project

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It's easy to go wrong in deploying an IoT solution. We've put together three principles to help in building an effective solution to avoiding machine failure.

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A number of prognostics tools are turning up but how effectively can they help you with your predictive maintenance? We've put together a checklist to help!

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Industry 4.0 promises many things around security and interoperability but the most interesting thing is predictive maintenance, enabled by prognostics.

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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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It can be difficult to measure how much money predictive maintenance can save in manufacturing. Thankfully we;ve found a great and impartial case study

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6 key things to look for when evaluating prognostic products to forecast machine failure

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Condition Monitoring (CM) is the process of monitoring data (vibration, acoustic emissions, temperature, etc) from machinery in order to identify changes which may indicate faults.

Condition monitoring project life cycles tend to follow a consistent traditional engineering roadmap from specifying the system through implementation, rollout, training and support.....

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IoT meets Industry – Part 3

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IoT meets Industry – Part 2

November 30, 2015

IoT meets Industry – Part 2

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IoT meets Industry – Part 1

November 18, 2015

IoT meets Industry – Part 1

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Not Horizontal, Cross Vertical!

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Using Senseye with Thingspeak

September 14, 2015

Using Senseye with Thingspeak

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