New Report Indicates US$11 Billion Predictive Maintenance Market By 2022, Driven By IoT Technology And New Services

PRESS RELEASE: Hamburg, Germany – 21 March 2017 //

IoT Analytics, a leading provider of market insights for the Internet of Things (IoT), today published a comprehensive Market Report, focusing on sizing the opportunity of the Predictive Maintenance market for the period 2017 to 2022.

predictive maintenance report release

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.

predictive maintenance report press release

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.”

The Predictive Maintenance report is available to download HERE.

 

Predictive Maintenance Report Structure

Executive Summary
PREFACE
1. Introduction to Predictive Maintenance (PdM)

1.1 Definition & Disambiguation
1.2 Role in IoT & I4.0
1.3 Benefits of employing PdM
1.4 PdM application areas
1.5 PdM process
1.6 Technology stack

2. Market Size & Outlook

2.1 Total Market
2.2 General Market
2.3 Market by Technology
2.4 Market by Industry
2.5 Market by Region

3. Competitive Landscape

3.1 Overview
3.2 List of Vendors
3.3 Company Profiles
3.4 M&A Patterns
3.5 M&A Activity Log
3.6 M&A Examples

4. Business Models & Use Cases

4.1 Business model observations
4.2 Selected market strategies
4.3 Use Case deep-dive
4.4 Further use cases

5. Trends

5.1 Trending Topics
5.2 The Future of Service
5.3 Challenges & Barriers
5.4 PdM Research

6. Methodology
About IoT Analytics
Appendix

Companies Mentioned (selection from the Predictive maintenance report)

Accenture, Alexander Thamm, Bosch, Brüel&Kjaer, C3 IoT, Cassantec, Caterpillar, Cisco, DataRPM, Dell, General Electric, Helium, Huawei, Hitachi, IBM, Keysight Technologies, Konux, Meggitt, Microsoft, National Instruments, OSIsoft, PTC, Rockwell Automation, Samsara, SAP, SAS, Schneider Electric, Senseye, Siemens, Sight Machine, SKF, Software AG, Spectris plc, Splunk, Tachyus, thyssenkrupp, Uptake + 65 more.

Target Audience

The focus of this Predictive Maintenance report is on industrial equipment and machinery but the lessons learned can be leveraged by any organization looking to implement PdM. The Predictive Maintenance report may be most beneficial to OEMs looking into PdM as a new business model, technology vendors in the IoT & PdM space. Also relevant for companies looking into M&A targets in the PdM area, as many Startups mentioned.

About IoT Analytics

IoT Analytics is the leading provider of market insights & competitive intelligence for the Internet of Things (IoT), M2M, and Industry 4.0. The specialized data-driven research firm helps more than 40,000 Internet of Things decision-makers understand IoT markets every month. IoT Analytics tracks important data around the IoT ecosystem such as M&A activity, Startup funding, company projects, use cases and latest developments. Product offerings include in-depth market reports, technical whitepapers, sponsored research, regular newsletter, as well as Go2Market and consulting services. As a research pioneer, IoT Analytics combines traditional methods of market research such as interviews and surveys with state-of-the art web-mining tools to generate high-caliber insights.

IoT Analytics is headquartered in Hamburg, Germany.

For more information, visit www.iot-analytics.com

Contact

For further comments or more information on this press release or the Predictive Maintenance report, please contact Stephanie Baumann, Public Relations Manager at IoT Analytics by emailing: press@iot-analytics.com