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Quality by name, Quality by nature

In line with our business name we only supply quality products from the World’s leading suppliers in our industry. We have long and extremely well-established agreements with the best-known names in engineering and manufacturing.

We realise the importance of quality and therefore will only ever supply fully guaranteed product, so you know when you buy from us you will never be let down.

Our suppliers include but are not limited to :-

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Can't find your bearings?

We pride ourselves on being a world leader in customer service, our multi award winning team are fully trained to be able to meet your needs.

Whether we are fulfilling your stock orders or helping you with a breakdown we will ensure that each order is treated with the total care and attention it deserves. You will receive it as quickly as possible. Working with our delivery partners we ensure our quality service is evident from initial enquiry through to it arriving with you.

Contact one of our team to see how we can help you.

Contact Us

Phone: +44 113 323 7793

Email: sales@qualitybearingsonline.com

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Standard International Delivery

The vast majority of our products are despatch the Same Day internationally, through DHL and with a delivery time of between 3 and 5 working days.

DHL - 3-5 Day DeliveryDelivery Cost
Order Value up to £250£35.00
Order Value £250 - £500£30.00
Order Value over £500Free

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SKF Auto ML - Changing The Bearing Industry As A Whole

SKF Auto ML - Changing The Bearing Industry As A Whole

Machine learning-based predictive maintenance could change the game in the bearing industry and we here to give you latest insights and what we know. Not only do we think this will help businesses perform more efficiently, but it will also aid engineers with maintenance operating across many different industries. We also believe this is a huge technological advancement within the bearing industry itself, something worth sharing with our readers.

Did you know? There is a growing interest in using Machine Learning (ML) tools and applying them to industrial and commercial applications. A need for highly skilled ML in automated systems is becoming more and more common. ML is known to be rather challenging as it requires high levels of data science and disciplined expertise. Data scientists are required to make choices at each stage of the process which impacts the outcome or results. The more the system can learn through the data it is fed, the more it is able to predict and determine future behaviour.

Launched in October 2020 by SKF, Auto ML (Automated Machine Learning) is a software that uses Artificial Intelligence (AI) to accurately predict mechanical failures helping to optimise maintenance and production processes. The development of Auto ML is aimed towards significantly reducing, or stopping altogether, unplanned machine downtime. If successful, this could cut down costs substantially for businesses where machine downtime puts large production lines on hold. It can process data in real time and warn technicians of asset failures whilst continuing to streamline the production process. The unseen failures are detected using vibration data alone. By incorporating feedback data continuously, it can be used to provide warnings on an extended range of failures, either predicted or detected. The auto ML revolution is still relatively new and hasn’t yet been widely applied however, we expect to see more of Auto ML being utilised in an array of different industries enhancing machine efficiency.


The Benefits of SKF AI:

  • Support and serve rotating equipment performance.
  • Automates the work that has to be done today.
  • Optimise efficiency of operations on manufacturing floor.
  • Increase quality assurance, eventually shorten lead times.
  • Optimises efficiency of own manufacturing.

So, when will your company start to implement Auto Machine Learning, or have you begun already?


Sources

SKF: https://industrial-ai.skf.com/the-automl-revolution-is-here/

Bearing News: https://www.bearing-news.com/wp-content/uploads/2020/12/BearingNEWS-DecJan2020-digital.pdf

25th Feb 2021 Hao Phan

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