Europe Predictive Maintenance Market – Industry Trends and Forecast to 2029

Market Analysis and Size

Predictive maintenance is known to lead a huge increase in ROI. It can decline maintenance costs up to 25%-30%, decrease breakdowns to 70%-75%, and reduce downtime to 35%-45%. These services are being highly deployed as they save overall cost for enterprises.

Europe Predictive Maintenance Market was valued at USD 490.88 million in 2021 and is expected to reach USD 34823.24 million by 2029, registering a CAGR of 40.10% during the forecast period of 2022-2029. Manufacturing accounts for the largest vertical segment in the respective market owing to the rise in the vertical segment in the respective market due to the automation in the manufacturing sector. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team also includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.

Market Definition

Predictive maintenance is a technique that utilizes data analysis techniques and tools to detect anomalies in business operations. These also detect possible defects in equipment and processes so that they can be fixed before they result in failure.

Report Scope and Market Segmentation

Europe Predictive Maintenance Market Dynamics

This section deals with understanding the market drivers, advantages, opportunities, restraints and challenges. All of this is discussed in detail as below:

Drivers

• Need to Obtain New Insights

The increase in the need to aggregate and explore textual data to obtain new insights is one of the major factors driving the predictive maintenance market. The incorporation of industry technology, knowledge, and practices to drive business outcomes has a positive impact on the market.

• Emergence of Big Data Analytics

The rise in the emergence of big data analytics across the region accelerate the market growth. Numerous enterprises are focusing on combining disparate internal data and external data sources for acquiring new efficiencies to assist in expanding the market.

• Prevent Unplanned Reactive Maintenance

The increased adoption of predictive maintenance programs to prevent unplanned reactive maintenance further influences the market. These services allow the maintenance frequency to be as low as possible to prevent unplanned reactive maintenance without incurring costs.

Additionally, rapid urbanization, change in lifestyle, surge in investments and increased consumer spending positively impact the predictive maintenance market.

Opportunities

Furthermore, need for real-time condition monitoring to assist in taking prompt actions and rise in internet proliferation extend profitable opportunities to the market players in the forecast period of 2022 to 2029. The increase in the usage of connected and integrated technologies will further expand the market.

Restraints/Challenges

On the other hand, factors such as data security concerns along with the requirement of frequent maintenance and up gradation to keep the systems updated are expected to obstruct market growth. Also, the lack of skilled workforce and complications with ownership and privacy of collected data are projected to challenge the predictive maintenance market in the forecast period of 2022-2029.

This predictive maintenance market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on predictive maintenance market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

COVID-19 Impact on Europe Predictive Maintenance Market

The COVID-19 pandemic had a positive impact on the predictive maintenance market. It helped millions of people globally in leveraging advanced tools for various applications. The surge in investments by various SMEs and large enterprises in technologies such as AI and machine learning for improving business operations. These services were highly useful during the pandemic due to the high need for remote monitoring and management of assets and business processes. The predictive maintenance is expected to witness high growth Post-COVID-19 due to the adoption of smart manufacturing processes using AI, and IoT technologies.

Recent Developments

• In June 2020, PTC launched an advanced ThingWorx 9. Industrial IoT platform to enhance scalability, simplify solution development and expand OPC UA support for enterprise deployments. This will help the company to enhance their product portfolio and better meet consumers changing demand.

Europe Predictive Maintenance Market Scope and Market Size

The predictive maintenance market is segmented on the basis of components, deployment mode, organisation size and vertical. The growth amongst these segments will help you analyze meager growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Components

• Solution
• Services

Deployment Mode

• Cloud
• On-Premise

Organisation Size

• Large Enterprises
• Small and Medium-Sized Enterprises

Vertical

• Manufacturing
• Energy and Utilities
• Transportation
• Government
• Healthcare
• Aerospace and Defense
• Others

Europe Predictive Maintenance Market Regional Analysis/Insights

The predictive maintenance market is analysed and market size insights and trends are provided by country, components, deployment mode, organisation size and vertical as referred above.

The countries covered in the predictive maintenance market report are Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, and Rest of Europe in Europe.

Germany has been accounted for the largest market share in Europe predictive maintenance market due to growing expansion of manufacturing plants to fulfil the growing demand, this factor tends to increase the growth of predictive maintenance in the country.

The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.   

Competitive Landscape and Europe Predictive Maintenance Market

The predictive maintenance market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to predictive maintenance market.

Some of the major players operating in predictive maintenance market are

• IBM (US)
• SAP SE (Germany)
• Microsoft (US)
• Siemens (Germany)
• GENERAL ELECTRIC (US)
• Schneider Electric (France)
• Software AG (Germany)
• C3.ai, Inc. (US)
• DINGO Software Pty. Ltd. (Australia)
• Splunk Inc. (US)
• Oracle (US)
• Amazon Web Services, Inc. (US)
• Hitachi, Ltd. (Japan)
• ABB (Sweden)
• Huawei Technologies Co., Ltd. (China)
• Intel Corporation (US)
• SKF (Sweden)

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