Entry to Industry 4.0

1 min read

The majority of machine shops operate mixed machine tool fleets and many are in need of low-cost easy to use vendor-neutral machine monitoring technology to assess productivity. Sheffield-based FourJaw Manufacturing Analytics has come up with the answer.

A low-cost technology solution that can monitor the performance of different machine tools and boosts productivity can be a game-changer for machining shops operating mixed fleets, as while many OEMs offer multi-machine networks and management functions, it does not do the job if you run a range of different brands.

Step forward FourJaw Manufacturing Analytics, a tech start-up that rose out of the University of Sheffield Advanced Manufacturing Research Centre (AMRC), which has developed a plug-and-play cloud-based data capture and analysis smart device that can be fitted to machines on a shop-floor – of any make and age.

The upfront costs of the technology are as little as £200, which includes £180 for the hardware and a subscription covering future software upgrades that are instantly installed and supported.

FourJaw says the MachineLink device and app enables precision engineering firms in high value manufacturing sectors, to access Industry 4.0 levels of data analytics and claims it will help unlock five-fold increases in shop-floor productivity.

Founders CEO Chris Iveson and CTO Robin Hartley, were research engineers at the AMRC, part of the High Value Manufacturing (HVM) Catapult, when they unearthed the idea to harness production data to empower manufacturers to understand their machining operations, enabling them to increase productivity levels and save costs.

“Robin was a researcher (at the AMRC) and came up with a piece of software that extracted data from CNC machine control systems and using that data to inform the research engineers at the AMRC to monitor the many different machine tools on site,” explains Iveson.

These machines included DMG Mori, WFL, Starrag and Makino brands and everything from mills, turning machines, lathes, grinding machines and machining centres and the data helped researchers optimise speeds and feeds, and monitor tool loads.

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