Predictive Maintenance & Asset Performance Market Report 2023–2028

The Predictive Maintenance Market Report 2023-2028 constitutes the 4th update of IoT Analytics’ ongoing coverage of predictive maintenance and is part of IoT Analytics’ ongoing coverage of industrial and software/analytics topics. The content presented in this report is based on a compilation of primary research, including surveys and interviews with 35+ industry experts from predictive maintenance vendors and end users conducted between March and October 2023.

The report encompasses a holistic overview of the current state of the predictive maintenance market and adjacent markets such as condition-based maintenance and asset performance management, including market projections, factors driving adoption, competitive landscape, technology and process implementation overview, notable trends and challenges, and insightful case studies.

The primary objective of this document is to provide our readers with a comprehensive understanding of the current predictive maintenance market landscape, offering in-depth analysis, market sizing, and valuable insights to facilitate informed decision-making and strategic planning.

What is predictive maintenance (PdM)?

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 statistical methods and supervised/unsupervised ML.
>> Among other benefits, this approach promises cost savings over routine or time-based preventive maintenance because tasks are performed only when warranted.

What is asset performance management (APM)?

A strategic equipment management approach that helps optimize the performance and maintenance efficiency of individual assets and of entire plants or fleets.
>> APM aims to improve the efficiency, availability, reliability, maintainability, and overall life cycle value of assets. This concept includes elements of CbM and PdM but goes beyond them.

What is condition-based maintenance (CbM)?

A maintenance approach that monitors the actual condition of an asset to determine what maintenance needs to be done.
>> It does not involve further analytics, such as predicting the remaining useful life (RUL) or the overall health of the machine.

The Predictive Maintenance Market Report 2023–2028 analyzes the predictive maintenance (PdM), condition-based maintenance (CbM), and asset performance management (APM)* market from 2021 to 2028. It provides detailed data and forecasts for the market size:

• by tech stack (connectivity, hardware, services, software)
• by hosting type (Private cloud/on-premises, public cloud)
• by segment (primary sector, health care, transportation, contruction & real estate, other, hybrid manufacturing, process manufacturing, discrete manufacturing)
• by industry (discrete manufacturing, hybrid manufacturing, process manufacturing)
• by region (Sub-Saharan Africa, Middle East & North Africa, South Asia, Latin America & Caribbean, North America, East Asia & Pacific, Europe & Central Asia)
• by country (East Asia & Pacific: Singapore, Australia, South Korea, Japan, China, Other; Europe and Central Asia: Belgium, Poland, Netherlands, Switzerland, Spain, Italy, France, United Kingdom, Germany; North America: Canada, United States)

*no breakdowns included for APM

In 2022, the predictive maintenance market achieved a value of $5.5 billion. Uncertain economic conditions and other manufacturing priorities over the past two years, lead to an 11% growth rate between 2021 and 2022. As businesses refocus on enhancing efficiency, safety, and operational performance, we project an annual growth rate of 17% for the predictive maintenance market through to 2028.

Our research reveals that industries with heavy assets and high downtime costs, such as oil & gas, chemicals, mining & metals, are spearheading the adoption of predictive maintenance solutions.

• What is predictive maintenance, condition-based maintenance, and asset performance management?
• What role does predictive maintenance play in the overall maintenance space?
• What are the key features, functionalities, and components of predictive maintenance solutions? What are the key components of asset performance management solutions?
• What is the current market size and projected growth of the predictive maintenance market?
• How does the predictive maintenance market split by tech stack, segment, hosting type, asset type, sensor type and region?
• What does the competitive landscape for predictive maintenance look like, who are the key players, and what is their market share?
• What are the emerging predictive maintenance trends and challenges?
• What are some successful case studies demonstrating the benefits of predictive maintenance in various applications?

ABB

AVEVA

AWS

Arundo

AspenTech

Augury

Baker Hughes

Cognite

Falkonry

GE

I-care

IBM

MachineMetrics

MathWorks

Microsoft

Novity

Rockwell Automation

SKF

Siemens

Telit Cinterion