2020 brought with it an unexpected and unwelcome new reason to maintain a ‘low-touch’ environment across industry. However, infection control is only one reason why a low-touch approach to asset management and maintenance makes sense. More generally, there are three good reasons why maintenance teams should be embracing a hands-off maintenance regime. What’s more, all three will still apply long after we’ve seen the last of the pandemic.
First, a low-touch environment minimizes the risk to workers. If they can use smart systems to monitor assets remotely, they can maintain a safe distance until they really need to get their hands dirty. This reduces their potential exposure to moving machinery, dangerous emissions, heat, cold or whatever other hazards may be lurking on the factory or plant floor.
Second, it also minimizes the risk to assets. If smart monitoring systems can encourage the idea that maintainers should only touch assets when a problem is detected, rather than as a matter of routine, people will be far less likely to inadvertently introduce any extra problems. No bolts will be over-tightened when they didn’t need adjusting, for instance, and no debris will be introduced into sealed systems that were opened up and inspected ‘just in case’. This nips a lot of future trouble in the bud.
Third, deploying smart monitoring systems equipped with machine learning capabilities makes better use of increasingly limited human resources. The pandemic may have created a jobs' crisis in the short term, but industry faces a demographic time bomb that will make recruitment increasingly difficult in the medium term. The impending retirement of a cohort of older, experienced manufacturing workers will create a shortage of new recruits and a workforce of people of younger technicians who lack the same level of experience as their more mature predecessors. For instance, The Manufacturing Institute projects a talent gap of 2.4 million in US manufacturing alone by 2028.
Technology could be the key to plugging that gap. It can take over much of the heavy lifting when organizations need to monitor the deluge of machine data coming in from the increasingly connected plant floor. This effectively compensates for a smaller workforce. Better still, Predictive Maintenance solutions can also interpret data and flag up when maintenance teams should be directing their attention towards a particular asset, thereby compensating for a lack of experience or expertise among recent recruits.
Happily, solutions such as Senseye PdM can help that hard-pressed maintenance teams keep performing as well as ever, even as they look to switch to a low-touch approach and work remotely where possible. In fact, Senseye PdM goes beyond the status quo and helps users make the leap from traditional preventive maintenance towards predictive maintenance.
Instead of the familiar approach of carrying out planned maintenance at fixed intervals, Senseye PdM uses proprietary algorithms to spot subtle patterns in the behavior of industrial machinery and can often see a failure developing weeks, if not months, before it can impact on production. Users are then alerted when they need to fix something – ideally before it has an opportunity to cause a breakdown or otherwise impact on production.
Existing Senseye customers include a range of leading global industrial organizations, who typically find that their deployments can cut downtime in half, deliver a 55% increase in productivity and boost maintenance accuracy by 85%.
They also make far better use of their precious human resources. For example, one of Senseye’s customers previously had one condition monitoring analyst to monitor 50 assets. Thanks to Senseye, that specialist-to-asset ratio is now 1:1000.
What's more, Senseye has launched ROI Lock™ in partnership with a leading Tier One global re-insurer, to significantly reduce the perceived risk of investing in predictive maintenance solutions. If deploying Senseye PdM fails to reduce unplanned downtime as agreed upfront, customers can claim a refund on their entire subscription fee.