Learning to anticipate problems and solve them before they happen is a practice that can pay dividends in all aspects of our lives. The consequences of not doing so can be costly, and this is especially true when it comes to manufacturing. A 2016 report by the Aberdeen Group found that, on average, the cost of unplanned downtime resulting from equipment failure is a staggering $260,000 per hour. A typical downtime lasts about four hours, leading to costs in excess of one million dollars per incident. These sorts of problems provide the motivation behind the Industry 4.0 movement, which seeks to integrate technologies such as machine learning into traditional industrial processes in order to diagnose issues and enhance automation.
This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/predicting-the-future-of-industry