The emerging market for Predictive Maintenance shows increasing growth as maintenance strategies move from what has been known as Condition-based Maintenance to Analytics- and IoT-enabled Predictive Maintenance. New IoT platforms, low-cost secure cloud storage as well as analytics vendors that offer dynamic data models play an increasing role in the technology transition.
The Predictive Maintenance report forecasts a compound annual growth rate (CAGR) for Predictive Maintenance of 39% over the time frame of 2016-2022, with annual technology spending reaching US$10.96 Billion by 2022. These numbers are based on the Predictive Maintenance related revenue of leading technology companies in the field, across 13 industries and 7 technology areas.
In developing the 139-page report, the analyst team at IoT Analytics studied over 110 companies that offer Predictive Maintenance technology elements and reviewed 47 implemented Predictive Maintenance projects. Ten of the leading companies and eleven of the use cases are presented in depth, alongside an analysis of current business models and M&A activities. The Predictive Maintenance report also calls out 6 major industry trends as well as various challenges, both for technology providers as well as technology users.
Commenting on the findings, IoT Analytics Managing Director Knud Lasse Lueth said: “Predictive Maintenance is one of the few real ‘killer’ use cases for the industrial Internet of Things. It is easy to understand how it works and the benefits are real. Inside factories, predictive maintenance is increasingly used to optimize internal operations typically resulting in 20-30% efficiency gains. But the real revolution is happening outside the factory. Several equipment OEMs have started to introduce new Predictive Maintenance services that are so compelling that they will likely change the industry dynamics forever. During our analysis, we found the elevator industry to be one of the segments at the forefront of this development. However, when we looked deeper into individual projects, we found that even advanced implementations in this industry are still to unlock the majority of its value.”
Source: Padraig Scully / IoT Analytics Press Release, Hamburg Germany
21 March 201
