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Evidence shows that components obsolescence is increasing rapidly. According to recent research by IHS Technology, in the year 2000 alone, component manufacturers issued 1,164 end-of-life (EOL) or product discontinuance notices, and the figure spiked to 5,506 by 2014. Though IHS forecasts that the number of such notices is going to decline, it’s always best to be prepared.

In the film Minority Report, the foreknowledge of three psychics is used to predict crimes and apprehend the future offenders, stopping the crimes before they occur. Predictive maintenance strategies are not too dissimilar to this, in that they stop problems before they arise, saving both time and money for the company.

In the classic film series Back to the Future, the risks and rewards of acting based on the knowledge of future events are explored through the adventures of Michael J. Fox’s Marty McFly.  Manufacturers can reap the rewards of predicting the future by using machine learning to implement a predictive maintenance strategy and save substantial amounts of time and money.

Unplanned machine downtime costs the world’s manufacturers over $50 billion a year, with a major cause of this being unexpected equipment failure. How can modern sensor networks reduce unplanned machine downtime in the manufacturing industry?

According to the 2019 Official Annual Cybercrime Report, a business falls victim to a ransomware attack every 14 seconds. As manufacturers connect more equipment to the Internet of Things, ransomware and other security breaches pose a more serious threat to productivity.