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Analysis: Paving the path to a digital future

by Guest on Aug 9, 2017

Spherical roller bearing robot automated ring picking from SKF.
Spherical roller bearing robot automated ring picking from SKF.

Digitalisation is most apparent in the consumer market, where music downloads, online shopping and on-demand TV are hailed as marvels of the digital age. However, digitalisation is also having a huge effect on manufacturing – and SKF is at the forefront of using it to improve the company’s business in the service of its customers.

The ability to collect and manipulate vast amounts of digital information will catapult manufacturing into the future. By embracing digitalisation, SKF is enhancing its core offering – bearings technology, and related services – so that its customers can further boost the performance of their rotating equipment.

Furthermore, by focusing on industrial digitalisation, SKF aims to drive further optimisation of cost and efficiency of the full value chain, including world-class manufacturing and supply chain integration.

Growing expertise

Digitalisation will affect all parts of the value chain, from design and manufacturing through to purchasing and maintenance.

SKF has been monitoring equipment remotely for around fifteen years now, and the company now has around one million bearings connected to the Cloud. Data from them is gathered and interpreted daily, often with assistance from the company’s experts.

The ability to handle this data leads to enhanced analytics – allowing SKF to earlier detect potential failures in rotating equipment that affect overall equipment reliability and to get a better understanding of critical product and system design requirements.

SKF has already developed platforms to help customers gather and interpret data. For instance, its Enlight platform helps operators visualise data from a variety of sources, using a device such as a smartphone or tablet. This is a smart way of putting ‘Big Data’ into an operator’s pocket.

The ‘connectivity’ of the data runs in all directions, and can be used in many ways. At its simplest, it connects a sensor to a remote diagnostics centre. However, the data – on the health of a bearing, for instance – can be fed right back to the design stage, and used to help redesign a better product.

Increased digitalisation has also begun to allow more customised manufacturing. Because it can cut machine re-setting times close to zero, there are fewer restrictions to making customised products.

Recently, the owner of an aluminium mill required bearings that would allow increased output – through a higher rolling speed – as well as lower maintenance costs and the elimination of unplanned downtime. SKF was able to produce four-row cylindrical roller bearings – complete with optimised surface properties and customised coatings – to boost service life and robustness, as well as designing out product cost.

Paid for performance

A major shift in the future – aided by digitalisation – will be the way in which SKF serves its customers. While the usual ‘transactional’ model of providing hardware will remain important, it will start to be replaced by more performance-based contracts.

Here, SKF will be responsible for ensuring that the customer’s operations remain efficient. Supplying hardware like bearings will then support the services – from predictive maintenance to lubrication expertise – that deliver this extra efficiency.

Recently, SKF agreed a five-year ‘Rotation for Life’ contract with Zinkgruvan Mining of Sweden. SKF will carry out remote monitoring of four mills at a Zinkgruvan enrichment plant. The company will then pay SKF a fee – based on whether it meets its productivity targets.

This arrangement relies on digitalisation technologies working in synchronisation. In one element of the contract, monitoring data from a conveyor belt is gathered automatically – with no human intervention – and an SKF specialist analyses the deviations, if necessary, while a distributed lubrication system keeps the line running at optimum efficiency. The ability to correlate a wider variety of data can further improve performance. For instance, the condition monitoring data that SKF routinely collects can now be combined with ‘process’ data such as machine speed and control parameters, through a collaboration with Honeywell.


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