A few weeks ago, I met with an investor to offer an assessment and guidance concerning a potential investment in a software company developing a predictive maintenance software: a system designed to use sensor data to assess the condition of a piece of equipment, detect an impending failure, and prescribe a remedial action.
As is often the case, there was a profound difference between the ideal world as described by the technologists and the harsh reality of equipment maintenance as experienced by field-service personnel.
Writing the Complete Guide to Predictive Maintenance Technology is obviously a grand goal for a short blog post. But now that I have got your attention, I’d like to focus on just one aspect: while diagnostic algorithms can be extremely powerful, implementing an application that can tackle complex, real-world maintenance problems requires much more than the ability to detect an anomaly in a time-series data stream. Read More