Maintenance is often one of the first things to get reduced during a financially challenging time - but has many obvious and hidden costs that need to be understood.

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Senseye answers the question of 'what is the Return on Investment (ROI) of Predictive Maintenance?' by announcing ROI Lock - Guaranteed PdM ROI.

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Safer with Senseye PdM

May 12, 2020

It is tempting when looking at the benefits of introducing predictive maintenance (PdM) technologies to focus on the financial improvements achievable.

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In an industry where the end product does not provide a large profit margin and demand is ever increasing, incremental gain must be made through efficient distribution plants. Over the last decade, heavy investment into automation has sought to alleviate these pressures.

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Predictive Maintenance and other connected technologies associated with the smart factory revolution offer huge opportunities for production efficiency and visibility, but they also bring an additional operational risk – security.

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By going beyond the machine builder’s recommended operating model they are taking further operational risks which leads to unplanned downtime and quality issues.

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The costs of binning faulty products or reworking them can be huge. Senseye can help manufacturers make substantial gains by optimizing both your machinery & your products.

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How can firms running older machines keep up with Industry 4.0 and the smart factories movement? It might be much easier and cheaper than you think, writes Senseye’s Chief Technology Officer, Robert Russell

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In a recent article by The Telegraph and sponsored by Microsoft, our Co-Founder and CEO Dr Simon Kampa, provided his insights and knowledge on how AI-based technologies such as predictive maintenance

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Reducing downtime may be at the top of your wish-list when opting for a Predictive Maintenance regime, but there are other big rewards on offer. Don’t overlook the potential benefit of eliminating over-maintenance.

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Verdantix investigates how Senseye uses machine learning to prevent unplanned downtime & extend asset life & how Senseye helps industrial firms & equipment manufacturers deliver on their maintenance goals.

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Mining has significantly benefited from the use of modern machinery and data analysis. The future for the sector presents some critical challenges that need to be anticipated and managed to maintain profitably.

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Organizations can only reap the huge rewards of Industry 4.0 by allowing data to flow freely to whichever systems can make the most of it.

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Manufacturing today is a world away from where it was ten years ago. IT is strongly represented at board level, enabling innovation and creating digitization strategies to support and enhance businesses.

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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.

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Being entirely data driven, quick to set up & relatively few people required, it brings insights & the benefits of scale to manufacturing operations

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Senseye, the industrial software company, today announced that it has entered into a new partnership with ATS Global to accelerate smart factory strategies

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When changes have threatened the automotive industry, it has always been able to innovate and respond. Predictive Maintenance is the next step.

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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 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 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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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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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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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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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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IoT meets Industry

November 18, 2015

IoT meets Industry – Part 1

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Using Senseye with Thingspeak

September 14, 2015

Using Senseye with Thingspeak

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