A new study from Vanson Bourne, sponsored by ServiceMax, from GE Digital, the provider of field service management solutions, has found that 75% of IT and field service leaders believe that machines will receive better, preventative healthcare than human beings by 2020.
IT and field service leaders surveyed believe advancements in machines having the ability to predict failure, and take preventative measures or self-healing actions are widely viewed as beneficial to a company’s bottom line. For example:
● 46% of respondents say machines requesting help themselves will help their company better manage their equipment assets.
● 39% of respondents say predictive maintenance would help better manage asset equipment.
● 44% of respondents say digital twin with predictive maintenance and artificial intelligence would help prevent major failures.
● 69% of respondents say they would like their own personal digital twin to help themselves and medical professionals regulate their health in non-invasive ways by taking early action and preventative measures.
The study, “After The Fall: Cost, Causes and Consequences of Unplanned Downtime,” surveyed 450 field service and IT decision makers in the UK, US, France and Germany across the manufacturing, medical, oil and gas, energy and utilities, telecoms, distribution, logistics and transport sectors, among others. According to Gartner, by 2020, 10% of emergency field service work will be both triggered and scheduled by artificial intelligence. The new study highlights the impact of new technology like artificial intelligence, analytics, and use of a digital twin on how we monitor industrial machines to predict when a piece of equipment will fail and what preventative service maintenance is required.
“In the same way that organisations want zero unplanned downtime with their equipment assets to avoid expensive loss of production or service, we want to mitigate our own human ‘outages’,” said Mark Homer, Vice President Global Customer Transformation for ServiceMax, from GE Digital. “This holistic view of how something is operating – whether it’s a person, an equipment plant or an individual component in a machine – has historically been disjointed and only visible when something goes wrong.
“Today, organisations are now acutely aware of the value of a real-time view on the health and performance of their critical assets, as well as predictive analytics on when preventative maintenance or intervention is required, and access to time series data, service history and optimisation demands.
“The research found that more than half of companies are planning to invest in a digital twin in the next three years. The value of these digital insights in an industrial context is starting to generate interest in preventative maintenance in a human context.”