Predictive Maintenance Market

Predictive Maintenance Market Outlook for 2023 to 2033

The valuation of the global predictive maintenance market is US$ 9.15 billion in 2023. The market is expected to progress at a CAGR of 24.2% and reach US$ 79.9 billion by 2033.

Using software packages, predictive maintenance technology can be incorporated into existing maintenance management systems. Machine learning, artificial intelligence, and big data analytics can be combined with predictive maintenance to produce timely, accurate, and detailed predictions.

Key Market Highlights

• Predictive maintenance technology is expected to become cost-effective as its usage is increasing and improving. As a result, companies are likely to spend less on maintenance. In the future, it will become common for equipment to get monitored and diagnosed remotely. This remote setup is anticipated to make maintenance operations efficient in the long run.
• Innovation continues to advance the performance, safety, and sustainability of the oil and gas industry. As digital technologies have become prevalent, they play an increasingly important role in achieving these goals. In the digital age, artificial intelligence (AI), cloud computing, the Internet of Things, and robotics are some examples.
• Companies are preparing to launch outcome-based services to upgrade legacy systems. Reducing human judgment by diagnosing errors using monitoring tools like image analytics and sensors has become easy for organizations with predictive maintenance.

The use of artificial intelligence (AI)-driven analysis for the optimization of assets can reduce maintenance costs for manufacturers. As a result of Industry 4.0 technology, predictive maintenance is now a reality, helping companies save time and money. Maintenance-driven production scheduling and remote monitoring can benefit from a technological upgrade with digital anomaly detection using artificial intelligence.

Historical Demand Analysis Vs Demand Outlook

The predictive maintenance market is anticipated to expand at a 24.2% CAGR from 2023 to 2033, up from the 18.4% CAGR recorded from 2018 to 2022.

The historical timeframe of the market was driven by the pandemic as the health infrastructure systems were undergoing different challenges. Some of the challenges included higher demand for masks, sanitary materials, and ventilators. In such a situation, it becomes easy for health systems and hospitals to get useful insights regarding disease outcomes and risks by leveraging predictive models.

Demand for predictive maintenance systems is increasing due to the rising need to reduce equipment failure and maintenance pricing. It becomes easy for enterprises to make fast operation predictions accurately compared to traditional methods.

Market Dynamics

• Rising need to reduce maintenance costs and increase equipment uptime is expected to impact market growth.
• Growing adoption of the latest technologies, including Machine Learning, the Internet of Things, and Cloud Computing is expected to drive market growth.
• Department managers can avoid virtual downtime using predictive maintenance systems when the equipment is not operating to its maximum potential. These systems can leverage a range of data, including equipment run time, energy usage, temperature, output, etc. All these benefits of predictive maintenance systems contribute toward market growth.
• The rising demand for maintenance solutions to reduce downtime and costs across different industries is expected to propel the market’s growth.

Sudip Saha

Principal Consultant

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Growth Drivers of the Market

Technological Advancements Facilitating Adoption of Predictive Maintenance Systems

Recent technological advancements have made predictive maintenance solutions affordable and easily available for manufacturers. IoT connects manufacturing, transportation and logistics, automotive, and utility industries. Consequently, many organizations prefer predictive maintenance solutions to reduce downtime and maximize efficiency. Also, many key vendors are investing in the market for service innovation. For instance,

In 2019, PTC announced the latest version of its award-winning ThingWorx Industrial IoT solution platform. Further, the company offers new capabilities, including those designed to improve the productivity of industry workers. It is done by clarifying how important operational information is delivered, collected, and synthesized.

Maintenance activities have become efficient and effective as automation and robotics are advancing. Predictive maintenance allows companies to see how their equipment performs comprehensively. As a result, this will help them make informed decisions about how and when to upgrade or replace their equipment as needed.

Businesses Improving their Efficiency Using Preventive Maintenance Systems

Businesses can reduce waste and improve efficiency by leveraging predictive maintenance technology. A positive impact on the region's economy can be achieved by creating new jobs, increased productivity, and overall economic development.

Businesses are improving their energy efficiency and environmental performance with predictive maintenance systems, resulting in a sustainable economy. Also, this system can help companies to maximize profits by predicting consumer demand and allocating resources effectively.

A predictive maintenance system could boost regional development and revolutionize business operations. Further, developing smart cities and autonomous vehicles could also be facilitated through this system. Traffic congestion can be reduced, and public transportation can be improved using this system.

Predictive Maintenance Useful in Effectively Reducing Emissions

Predictive maintenance technology can send alerts to authorities before potential threats, improving public health and safety. This technology increases environmental sustainability through improved energy efficiency, resulting in reduced emissions and energy consumption.

Predictive maintenance systems have advanced in recent years by improving data collection, using sophisticated algorithms, and automating the implementation. For example, these technologies analyze various parameters. These parameters include temperature and vibration based on data collected from IoT sensors and other sources using machine learning algorithms to detect anomalies.

Predictive maintenance is a method to analyze the future breakdown point of in-service equipment to estimate when maintenance is required so that the components/parts can be replaced before failure. This method can also be used in many ways depending on available data.

Predictive maintenance technologies carry out vibration analysis, infrared testing, sound level measurements, oil analysis, ultrasonic leak detection, and thermography testing. These are carried out to improve plant operations and safety and regulatory compliance through better asset utilization.

Challenges in the Predictive Maintenance Market

The lack of a skilled workforce is a vital factor restraining the growth of the market, as there is an increasing demand for a highly skilled workforce for handling the recent software systems. Additionally, there might be a growing requirement for a professional team to take a large amount of data generated from IoT devices.

Comparative View of Adjacent Predictive Maintenance Markets

The table below compares the predictive maintenance market, predictive touch market, and predictive disease analytics market. Based on the analysis, predictive technology is found to make splashes across different industries. The technology has been catering to the rising demand for predictive disease analytics in the healthcare sector or predictive maintenance in the manufacturing sector. Though the adoption rate of predictive touch is relatively higher, predictive maintenance market valuation is expected to remain significant over the forecast period.

Predictive Maintenance Market:

Predictive Touch Market:

Predictive Disease Analytics Market:

Category-wise Insights

Software over Other Solutions

Easy accessibility makes software a key solution for predictive maintenance. Given its popularity, software holds a market share of 20.1% in 2023.

As per the predictive maintenance market report, preference for software-based predictive maintenance solutions remains high as they offer data advantage to organizations. For instance, TIBCO Software’s TIBCO Data Virtualization as well as TIBCO EBX help end users to understand data and take the next best steps. Besides this, end users also prefer software-based predictive maintenance to see the bypass status and reduce the risk.

Automotive Generates Significant Demand for Predictive Maintenance

Due to the increasing need for manufacturing equipment maintenance, the automotive segment held a significant share of 18.2% of the global predictive maintenance market.

The emerging Industry 4.0 is projected to fuel growth in the market over the coming decade.

Followed by the automotive industry, the energy and utilities segment is also predicted to record a notable CAGR rate during the forecast period because of the increasing requirement for monitoring assets.

A Glance at the Country-wise Overview

The United States is the leading market in the predictive maintenance landscape, globally. The United Kingdom holds a significant share of the global market in the European region. The presence of key companies in India is facilitating the development of predictive maintenance technologies, contributing to the growth of the market.

Investments in Advancing Technologies in the United States

The United States is expected to be the leading country holding a share of 17.2% of the global market for predictive maintenance technologies. The market is projected to grow rapidly over the projected period. There are a few factors that contribute to the growth of the United States market during the forecast period, including:

• Increasing investments in developing technologies such as IoT, artificial intelligence, and machine learning for process manufacturing industries
• Growing presence of predictive maintenance vendors in the country

As a result, the United States captures a significant share of the North America market due to the presence of leading market players.

Industrial Automation in the United Kingdom Fueling Market Growth

The United Kingdom is predicted to expand at a significant rate over the forecast period. Growing awareness about the significance of predictive maintenance technology and rising investments by organizations are propelling the demand for predictive maintenance services in the United Kingdom.

Rising industrial automation is also creating massive opportunities for various players in the United Kingdom market that contributes a share of 9.1% to the global revenue.

Presence of Several Companies in India Contributing to Market Development

The South Asia Pacific region increasingly focuses on new solutions to optimize the output for the maintenance of assets, which facilitates the region's market growth.

India is expected to witness significant growth due to the availability of several companies contributing to market development. Furthermore, machine learning and real-time condition monitoring, as part of predictive maintenance, are anticipated to drive the market during the forecast period. India holds a share of 6.5% of the global market.

Competitive Landscape of Predictive Maintenance Market

The presence of key players in the market makes it highly competitive. Moreover, these market players follow key strategies such as mergers and acquisitions, partnerships, and novel product launches to reinforce their position in the market.

• TIBCO Software introduced its TIBCO EBX and Data Virtualization in May 2021. Both solutions greatly reinforce an organization's data fabric, allowing customers to influence the immense prospective of data.
• SAS Institute released its platform called SAS VIya in May 2021 by integrating new data management solutions into its potent SAS VIya platform. The purpose of this launch is to strengthen the foundation for data analytics.

Prominent Players

• Microsoft
• IBM
• GE
• SAP
• Schneider Electric
• PTC
• Software AG

Predictive Maintenance Market Segmentation

By Solution:

• Software
• Services
• Consulting
• Implementation and Integration
• Training
• Support & Maintenance

By Development:

• Cloud
• On-premise

By End-use Industry:

• Automotive
• Healthcare
• Manufacturing
• Transportation
• Energy & Utility
• Others

By Region:

• North America (The United States, Canada)
• Europe (Germany, Italy, The United Kingdom, Spain, France, BENELUX, Russia)
• Latin America (Mexico, Brazil, & Rest of Latin America)
• East Asia (China, South Korea, and Japan)
• South Asia & Pacific (India, ASIAN, and Australia & New Zealand)
• The Middle East and Africa (GCC Countries, Türkiye & South Africa)