Overall Equipment Effectiveness-Helping Manufacturers Tackle the UK Productivity Problem.

Author:Coussins, Andy
 
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A recent lull in growth for UK productivity has highlighted the need for manufacturing firms to think and act more strategically when it comes to boosting both their performance and productivity. While the concept of overall equipment effectiveness (OEE) is nothing new, recent advances in Industry 4.0 technologies mean that process evaluation--to identify and eliminate inefficiencies--has once again become a key consideration for organisations striving for future business growth.

In today's manufacturing landscape, the value-driven insights leveraged from technologies like artificial intelligence (AI) can be used to evaluate real-time data generated by connected machines. This is proving pivotal for driving operational productivity--from the factory to the shop floor.

Anticipating and minimising machine downtime.

The fast-paced adoption of advanced digital technologies by manufacturers around the globe means that, to stay fit to compete, UK firms need to ensure they have a robust and agile IT infrastructure in place. Those manufacturers able to embrace today's readily available Industry 4.0 technologies will be best positioned to drive up efficiencies and reposition themselves competitively in the global manufacturing market.

By deploying sophisticated sensors to harvest production data on the shop floor, and tools to extract and process this data in real-time, firms will be able to optimise machinery and reduce operational downtime and costs. Indeed, a recent 2018 survey on machine downtime revealed how the broken machines and faulty parts that hamper productivity were costing Britain's manufacturers more than 180bn [pounds sterling] a year.

Although production challenges such as machine breakdowns may seem inevitable, having the right systems in place can help manufacturers retain a degree of control over unforeseen circumstances. The use of monitoring software, for example, gives firms the visibility needed to anticipate and solve production problems before these happen. Similarly, by harnessing insights generated from real-time production data, manufacturers can improve equipment reliability, boost longevity, and reduce waste. As well as informing future planning efforts, these insights can also enable manufactures to discover hidden opportunities --to increase business performance, quality, and yield.

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