Description
Predictive Maintenance Market Report 2021 – 2026
The Predictive Maintenance Market Report 2021-2026 constitutes the third update of IoT Analytics’ ongoing coverage of the Predictive Maintenance space. Along with the latest market assessment, the report provides business and technical insights collected through two end-user surveys. The reports’ offering is further enhanced with an extensive summary of recent market developments, trends, and challenges, along with an updated market forecast for the market in 2021-2026 by technology, segment, and region.
Analyst take on Predictive Maintenance:
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Find out:
- What is Predictive Maintenance?
- How big is the Predictive Maintenance market today and how fast is it growing?
- Which types of technologies are used for Predictive Maintenance?
- What are examples of Predictive Maintenance vendors and their strategies to achieve zero downtime?
- What are the economics of unplanned downtime?
- What is the current Predictive Maintenance penetration rate, planned investments and implementation best-practices?
- What are the KPIs of today’s Predictive Maintenance models?
- What are the most used Predictive Maintenance analytics methods?
- Which benefits customers see from their Predictive Maintenance investments?
- What trends are characterizing the market currently?
- What challenges are holding the market back?
Available pricing plans:
See Terms & Conditions for license details.
Single User License
183 page PDF- 1 named user (in your organization within the country of purchase)
- Complete market report in PDF
- Market model data in EXCEL
- List of predictive maintenance companies in EXCEL
- Complete market report in PPT
- 1h discussion with the analyst team
Team User License
183 page PDF, 2x EXCELs- 1-5 named users (in your organization within the country of purchase)
- Complete market report in PDF
- Market model data in EXCEL
- List of predictive maintenance companies in EXCEL
- Complete market report in PPT
- 1h discussion with the analyst team
Enterprise Premium License
183 page PDF, PPT, 2x EXCELs- Report may be distributed to all employees of the enterprise
- Complete market report in PDF
- Market model data in EXCEL
- List of predictive maintenance companies in EXCEL
- Complete market report in PPT
- 1h discussion with the analyst team
At a glance:
Definition of Predictive Maintenance:
Predictive maintenance describes a set of techniques to:
accurately monitor the current condition of machines or any type of industrial equipment, using either on-premises or cloud analytics solutions, with the goal of predicting upcoming machine failure by using automated (near) real-time analytics and supervised or unsupervised ML. (Note: Many PdM implementations use “near real-time” analytics, i.e., with several minutes of delay.)
>> Among other benefits, this approach promises cost savings over routine or time-based preventive maintenance because tasks are performed only when warranted.
Predictive Maintenance is defined and further differentiated from other maintenance approaches.
The report presents a complete picture of the technology stack of IoT PdM solutions, along with deep dives on 4 PdM sensing techniques and 7 key analytics considerations (e.g., types of data sources).
The market is defined as annual PdM technology-spend by companies implementing PdM Solutions, and an analyst opinion on market development provided.
The market is further broken down into technology stack elements, segments, and regions.
The report provides a company landscape with ~280 firms, grouped into four main categories based on their main PdM offering: Hardware, Connectivity, Storage and Platform, and Analytics. In the same chapter, PdM startups founding information, and M&A activities are also presented.
10 cases studies are presented with detailed information on technology, challenges addressed, PdM approach taken, and solution implications.
The report provides results from two surveys on the Predictive Maintenance end-user perspective, with business- (e.g., economics of unplanned downtime), and technical-related (e.g., precision of models) information on PdM implementations.
7 trends and 2 challenges are described in detail, backed up with interview quotes and examples.
Table of contents:
Selected companies from the report:
ABB, Amazon Web Services, Aspen Technologies, Augury, AVEVA, Cisco, GE, Google, HPE, IBM, LeanBI, MachineMetrics, Microsoft, Nanoprecise SC, PARC, PTC, Reliability Solutions, SAP, Seeq, SKF, Senseye, Siemens and many more.
Related Reading:
IoT Analytics published a blog post on “Predictive Maintenance Market: The Evolution from Niche Topic to High ROI Application” which is derived from the report.
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