The global predictive maintenance market size was valued at USD 3.18 billion in 2018 and is expected to register a CAGR of 37.9% over the forecast period. Equipment manufacturers, plant owners, and operators in the energy industry face the common challenge to keep their machinery and other assets working efficiently. Reducing the cost of maintenance, equipment/plant downtime, time-sensitive repairs are the key challenges that are highly faced by the plant owners during the operation. These solutions help the plant owners to schedule a maintenance program prior to any likelihood of failures.
Considering the aggressive time constraints for various industrial products and services, it is important to identify the causes of failures or potential faults before they have a chance to occur. Evolving technologies such as Internet of Things (IoT), cloud storage, and big data analytics are enabling more industrial equipment and assembly robots to provide condition-based data, making fault detection easier and practical. Information collected from this equipment can be turned into actionable and meaningful insights by using these solutions. This is expected to accelerate the demand for these solutions across the globe.
Companies are deploying their maintenance services more effectively and are improving equipment up-time by proactively detecting potential issues by using the available data within the plant. The faults or failures of the equipment or plant can be detected easily by effectively using the available structural data. The structural data pointers include year of production, model, make, working hours, warranty details along with unstructured data mainly repair logs and maintenance history. This information enables organizations to predict if or when the equipment will fail so that the repair works can be carried out before the failure occurs.
Predictive maintenance can be applied to all industry verticals where machines produce significant amounts of data and require maintenance. Industries namely automotive, aerospace, healthcare, manufacturing, process industries like chemicals, food and beverage, oil and gas can be transformed with the help of these solutions. Additionally, apart from the advantages such as reducing downtime, eliminating the causes of failure and controlling repair costs, these solutions also employ non-intrusive testing techniques for evaluating and computing asset performance trends.
However, lack of availability of skilled workforce with adequate knowledge of operating the predictive maintenance solution is a major challenge faced by the organizations. Moreover, for proper functioning and understanding of the tool, a trained person is required. The person must be capable enough to analyze the situation and take the corresponding action based on the outcomes. In order to overcome these challenges training and consulting services are also becoming popular and are witnessing significant demand.
Based on solution, the predictive maintenance market is segmented into integrated and standalone solutions. The integrated solutions segment is anticipated to hold the dominant market share over the forecast period. High demand for integrated solutions can be attributed to the growing need for customized solutions. Moreover, with the growing popularity and awareness about these solutions, the demand for application specific solutions from various industry verticals have increased significantly.
Integrated solutions are tailor-made while standalone solutions are standard/readymade solutions offered by the market players. Standalone solutions are devoid of the option for customization. However, standalone solutions are highly deployed by small and medium size enterprises owing to its low cost. The increasing need for a single solution with multiple capabilities is making integrated solutions more popular compared to standalone solutions.
Based on service, the market is segmented into deployment/installation, support and maintenance, and training and consulting services. The deployment/installation services segment is anticipated to dominate the market in the forthcoming years. The demand for cloud-based deployment of the solutions from various industry verticals such as aerospace and defense, automotive and transportation, and energy and utilities is likely to increase over the forecast period. This is expected to further contribute to the segment growth.
Since equipment and types of machinery require regular and timely maintenance for effective functioning, support and maintenance services are gaining traction. Once the deployment/installation of these solutions is done, the support and maintenance services play a crucial role throughout the lifetime of the solution. These services are helping organizations to enhance their overall efficiency and revenue generation. The growth of the segment is also driven by the higher rate of deployment of predictive maintenance solutions and the expected continuation in the trend.
Large enterprises segment accounted for a major market share in 2018. These enterprises are optimizing and automating their operational maintenance process by using these solutions. Moreover, the cost associated with downtime and assets in large enterprises is very high. To overcome these challenges predictive maintenance solutions are increasingly being deployed in large enterprises across the globe.
Small and medium enterprises segment is projected to register the fastest CAGR from 2019 and 2025. Growing investments for establishment and growth of small and medium-size enterprises across the globe is also contributing significantly to the overall growth. There is a rise in adoption of predictive maintenance solutions by small and medium enterprises operating in the manufacturing sector since it helps them keep low repair and operational costs for new operations.
The manufacturing segment is estimated to dominate the global market in 2018. The growing need for maintenance of manufacturing equipment such as industrial robots, machinery, elevators, and pumps for reducing the overall downtime is driving the adoption of predictive maintenance solutions and services in the manufacturing segment. Moreover, the rising automation in the manufacturing sector coupled with Industry 4.0 is also anticipated to drive the demand for these solutions to protect the high-end equipment from damages.
Energy and utilities segment is also a major contributor to global market growth. The growth of the segment can be attributed to the rising need for enhancing equipment up-time by predicting potential issues prior to their occurrence. Moreover, the increasing need to predict the likelihood of failure of aged components in the energy and utility infrastructure is supporting the segment growth. Additionally, increasing penetration of power consumption analytics applications is also contributing significantly in making the energy and utilities one of the leading segments.
On-premise segment is estimated to hold a major market share over the forecast period, attributed to data privacy concerns associated with cloud infrastructure. Moreover, deployment and operations of predictive maintenance solution over the on-premise platform has been the traditional method opted by many organizations across the globe. Since most of the companies have servers and data centers for running their internal and external software solutions effectively, the on-premise mode is preferred significantly.
Cloud-based solutions segment is projected to exhibit the fastest CAGR over the forecast period. The growth can be attributed to faster data processing, efficient resource utilization, direct IT control, and cost-effectiveness offered by cloud models. Moreover, remote maintenance feature can also be utilized by the deployment of the solutions on the cloud platform. Additionally, leading vendors operating in the global market are offering cloud-based solutions for effectively automating the equipment maintenance process and gain maximum profits associated to it.
Asia Pacific is expected witness the fastest CAGR during the forecast period. The higher growth of the market in region is primarily attributed to massive investments done by public and private sectors for the enhancement of asset maintenance solutions. Therefore, augmenting the demand for predictive maintenance solutions deployed for automating the maintenance process of the plant. Moreover, the higher availability of cheap labor in the region has led to the establishment of huge number of manufacturing units in the region. Furthermore, rising concerns for reducing overall downtime and operation costs in manufacturing plants is forcing the plant owners to deploy these solutions.
North America is anticipated to hold a major market share during the forecast period. The region is the leader in the development and adoption of advance predictive maintenance solutions. This can be attributed to the presence of a large number of leading solution and service providers. Moreover, higher investments made on emerging technologies such as artificial intelligence, IoT, and machine learning are anticipated to help the region to maintain its dominant position in the near future. Furthermore, higher awareness regarding predictive maintenance measures and its importance is also creating significant demand for these solutions.
Some of the key players operating in the market are IBM Corporation; Microsoft Corporation; SAP ERP; General Electric Company; Siemens AG; Schneider Electric SE; Software AG; Accenture plc; Honeywell International Inc.; and Cisco Systems, Inc. These players have implemented various organic and inorganic growth strategies, such as product launches, collaborations, partnerships, mergers and acquisitions to expand their market presence.
IBM Corporation has been an innovative developer of predictive maintenance solution for various industry verticals. The company offers solutions for maintaining, monitoring, and optimizing the assets for better utilization and performance. It helps the organizations enhance maintenance programs by developing a set of instructions to carry out when changes in asset performance are identified. It also helps the customers enhance the life of their assets with the help of these solutions.
Base year for estimation
Actual estimates/Historical data
2014 - 2017
2019 - 2025
Revenue in USD Million and CAGR from 2019 to 2025
North America, Europe, Asia Pacific, Latin America, and Middle East & Africa
U.S., Canada, Germany, U.K., China, India, Japan, and Brazil
Revenue forecast, company ranking, competitive landscape, growth factors, and trends
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This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2014 to 2025. For the purpose of this study, Grand View Research has segmented the global predictive maintenance market report based on solution, service, deployment, enterprise size, end-use, and region:
Solution Outlook (Revenue, USD Million, 2014 - 2025)
Service Outlook (Revenue, USD Million, 2014 - 2025)
Support & Maintenance
Training & Consulting
Deployment Outlook (Revenue, USD Million, 2014 - 2025)
Enterprise Size Outlook (Revenue, USD Million, 2014 - 2025)
Small & Medium Enterprises
End-Use Outlook (Revenue, USD Million, 2014 - 2025)
Aerospace & Defense
Automotive & Transportation
Energy & Utilities
IT & Telecommunication
Oil & Gas
Regional Outlook (Revenue, USD Million, 2014 - 2025)
Middle East & Africa
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