The Predictive Maintenance (PdM) market is significantly influenced by a variety of market factors that play a crucial role in shaping its growth trajectory. One key factor is the increasing adoption of advanced technologies such as Internet of Things (IoT) and Artificial Intelligence (AI) across industries. These technologies empower predictive maintenance solutions to gather and analyze vast amounts of data from equipment and machinery, enabling proactive identification of potential failures before they occur. This preventive approach not only minimizes downtime but also extends the lifespan of assets, making it an attractive proposition for businesses.
Another market factor driving the growth of predictive maintenance is the escalating demand for cost-effective solutions. Companies are increasingly recognizing the economic benefits of implementing PdM systems, as they help in reducing unplanned downtime and maintenance costs. By shifting from reactive to proactive maintenance strategies, organizations can optimize their operational efficiency and allocate resources more effectively. This cost-effectiveness has become a pivotal factor in the decision-making process for businesses looking to enhance their maintenance practices.
Moreover, the rise of Industry 4.0 has been a significant catalyst for the predictive maintenance market. Industry 4.0 emphasizes the integration of digital technologies into manufacturing processes, fostering the development of smart factories. Predictive maintenance aligns seamlessly with the goals of Industry 4.0 by providing real-time insights into equipment health, enabling data-driven decision-making, and supporting the overall evolution towards intelligent and connected manufacturing environments.
The increasing complexity of industrial machinery is also a notable market factor influencing the growth of predictive maintenance solutions. As equipment becomes more sophisticated, the need for advanced monitoring and diagnostic tools becomes imperative. Predictive maintenance addresses this complexity by utilizing machine learning algorithms to analyze diverse sets of data, ranging from temperature and vibration to fluid levels and energy consumption. This enables the early detection of anomalies and potential failures, ensuring optimal performance of intricate machinery.
Furthermore, regulatory requirements and industry standards contribute to the expansion of the predictive maintenance market. Various industries, such as aerospace, healthcare, and energy, are subject to strict regulations regarding equipment safety and reliability. Compliance with these regulations often necessitates the implementation of predictive maintenance practices to ensure that equipment meets the required standards. As a result, industries are increasingly turning to predictive maintenance solutions as a means of achieving and maintaining regulatory compliance.
The growth of the Internet of Things (IoT) ecosystem also plays a pivotal role in shaping the predictive maintenance market. The proliferation of connected devices and sensors embedded in equipment facilitates the continuous monitoring of machine health. This interconnectedness enables seamless communication between devices, allowing for the real-time transmission of data and prompt decision-making. The integration of IoT with predictive maintenance not only enhances the accuracy of failure predictions but also facilitates the efficient management of assets across diverse industries.
Report Attribute/Metric | Details |
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Segment Outlook | Component, Testing Type, Deployment Mode, Technique, Vertical, and Region |
Businesses are utilising AI and ML technology to evaluate loT data with extraordinary precision, accuracy, and speed compared to traditional business intelligence solutions. PdM proactive maintenance strategies offer solutions to minimise time and money spent on repairs and maintenance while reducing unplanned downtime of equipment that is essential for production. PdM solutions also guarantee that assets are always available and in top functioning condition.
Further, One of the best alternatives for asset-heavy firms that offers lower expenses and a higher ROI is predictive maintenance tactics. Solution providers skilled in AI and ML can gather a sizable amount of customer-related data and turn it into insightful information. due to loT's massive data production from linked devices. Real-time condition monitoring is made possible by the ongoing improvements in big data and cloud testing. A wealth of data is made available by the widespread use of loT devices with industrial equipment.
Additionally, Machine learning and artificial intelligence are now more frequently combined. A growing number of clients are embracing these AI-powered solutions to assist in the transition from a reactive to a proactive strategy. New AI-enabled solutions are being aggressively introduced by market participants.has enhanced the Predictive Maintenance (PdM) market CAGRacross the globe in the recent years.
However the expanding utilization of predictive maintenance in the logistics and transportation industries is another factor driving the growth of the Predictive Maintenance (PdM) marketrevenue.
The Predictive Maintenance (PdM) market segmentation,based on component, includes Hardware, Solution, Services. The market was dominated by the solution sector. In order to predict an anomaly in the operation of the essential equipment, the solution makes use of the data accumulated by various IoT sensors and does an in-depth data analysis. Hence, is a great contributor in Predictive Maintenance (PdM) market revenue. In some circumstances, businesses directly prefer to adopt managed services for their operations in accordance with their needs. Additionally, the increasing demand for employee training, efficient application of these solutions, and help with integration & implementation are anticipated to boost the expansion of the services sector.
On June 2022: Siemens Digital Industries announced the acquisition of Senseye, a Southampton-based provider of machine data, to broaden its range of cutting-edge predictive maintenance and asset intelligence.
The Predictive Maintenance (PdM) market segmentation,based on testing type, includes Vibration Monitoring, Electrical Insulation, Infrared Detector Thermography, Temperature Monitoring, and others. Among these, the vibration monitoring segment accounts for the largest market share. Additionally, Regular motor testing, or testing at the first hint of trouble, allows for accurate problem prediction, prevention, and resolution with the least amount of service interruption. It is possible to do this motor winding test without actually attaching the test apparatus to the motor. The test apparatus is typically linked to the motor starter's load side. A voltage pulse is applied to the other two windings while one of the three windings is grounded during the test. The segment is anticipated to have the greatest CAGR throughout the assessment period. positively impacts the market growth.
Theglobal Predictive Maintenance (PdM) market data based on deployment includes Cloud, and On-premise. The on-premises market category represents the biggest market share of these. Additionally, the segment is anticipated to have the greatest CAGR throughout the assessment period. Its modular sensors and simpler deployments in existing equipment are credited with this. However, due to direct IT control, remote accessibility, internal data delivery & handling, faster data processing using advanced predictive analytics, efficient resource utilisation, and cost-effectiveness, cloud-based predictive maintenance solutions are expected to exhibit the highest growth rate during the forecast period.
Figure 2: Predictive Maintenance (PdM) Market, by Deployment, 2021 & 2030 (USD Billion)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Based on Techniques, the Predictive Maintenance (PdM) industry has been segmented into Traditional Technique, Advanced Technique. The market share that belongs to traditional procedures is the largest. Additionally, the segment is anticipated to have the greatest CAGR throughout the assessment period. Traditional maintenance techniques are simple. They include planned maintenance on a regular basis and emergency maintenance. This means that equipment is taken out of the manufacturing cycle until the broken or worn-out components are fixed.
Based on Vertical, the Predictive Maintenance (PdM) industry has been segmented into Manufacturing, Healthcare, Energy & Utility, Automotive, Aerospace & Defense, Transportation, and Others. The manufacturing sector holds the biggest market share of these. Additionally, the segment is anticipated to have the greatest CAGR throughout the assessment period. Companies are concentrating on increasing their financial performance by thoroughly examining the manufacturing reliability of their operations as competition in the manufacturing business grows and the obstacles for successful survival become more significant. In this context, effective asset performance management is a must-have.
By Region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. North AmericaPredictive Maintenance (PdM) market accounted for USD 7.47 billion in 2021 and is expected to exhibit a significant CAGR growth during the study period. Key developments in technology are among the main drivers of the predictive maintenance industry in this region.
Further, the major countries studiedin the market reportare: The U.S, Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.
Figure 3: PREDICTIVE MAINTENANCE (PDM) MARKET SHARE BY REGION 2021 (%)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Europe Predictive Maintenance (PdM) market accounts for the second-largest market share due to the increase in awareness towards the benefits of predictive maintenance in all sectors. Further, the Germany Predictive Maintenance (PdM) marketheld the largest market share, and the UK Predictive Maintenance (PdM) market was the fastest growing market in the European region
The Asia-Pacific Predictive Maintenance (PdM) Market is expected to grow at the fastest CAGR from 2022 to 2030. A number of businesses are currently introducing next-generation, complete cloud-based solutions. Industry expansion has been assisted by the rising use of new and developing technologies to get insightful knowledge into decision-making. Various vertical end-users are looking for downtime and cost savings more and more. Moreover, China Predictive Maintenance (PdM) market held the largest market share, and the India Predictive Maintenance (PdM) market was the fastest growing market in the Asia-Pacific region
Major market players are spending a lot of money on R&D to increase their product lines, which will help the Predictive Maintenance (PdM) market grow even more. Market participants are also taking a range of strategic initiatives to grow their worldwide footprint, with key market developments such as new product launches, contractual agreements, mergers and acquisitions, increased investments, and collaboration with other organizations. Competitors in the Predictive Maintenance (PdM) industry must offer cost-effective items to expand and survive in an increasingly competitive and rising market environment.
One of the primary business strategies adopted by manufacturers in the Predictive Maintenance (PdM) industry to benefit clients and expand the market sector is to manufacture locally to reduce operating costs. In recent years, Predictive Maintenance (PdM) industry has provided efficiency in terms of providing many solutions ahead of time. The Predictive Maintenance (PdM) market major player such as Axiomtek Co. Ltd (Taiwan), Oracle Corporation (US), Microsoft Corporation (US), XMPro (US) and others are working to expand the market demand by investing in research and development activities.
Axiomtek is a well-known industry pioneer who is steadfastly committed to the research, development, and production of a variety of cutting-edge, dependable, and industrial computer products with high efficiency. Over the past 30 years, Axiomtek has grown dramatically. Software, hardware, firmware, and application engineers are all part of Axiomtek's expanding team of engineers. In December 2022: Axiomtek, a company with experience in both software and hardware integration, recently introduced the AMR Builder Package. The package comes with DigiHub for AMR, sensor kits, a controller, and development support services.
Senseye is a industrial analytics software company providing outcome-oriented predictive maintenance solutions for manufacturing and industrial companies. Its predictive maintenance technology offers a significant decrease in unplanned machine downtimes and greater productivity of maintenance personnel. Through extended asset lifetimes and waste reduction, Senseye products help businesses enhance their sustainability. On June 2022 Siemens Digital Industries announced the acquisition of Senseye, a Southampton-based provider of machine data, to broaden its range of cutting-edge predictive maintenance and asset intelligence.
Axiomtek Co. Ltd (Taiwan)
Oracle Corporation (US)
Microsoft Corporation (US)
XMPro (US)
IBM Corporation (US)
RapidMiner (US)
Hitachi Ltd (Japan) among others
The purpose of the partnership between Optibus and Stratio, which will begin in March 2023, is to advance and enhance predictive maintenance solutions through the application of artificial intelligence.
In order to provide predictive maintenance solutions that forecast vehicle needs with greater precision and notify users in advance of when a vehicle may break down or require repair, the Optibus-Stratio partnership will quicken the integration of historical data, artificial intelligence, and vehicle health monitoring. The agreement represents the first time a predictive maintenance company and a planning and operations platform have worked together.
To improve occupant comfort and raise building value, Schneider Electric, the world leader in the digital revolution of energy management and automation, today announced the launch of EcoStruxureTM Building Operation for the Indian market in March 2023. Buildings in India use 30% of the total electricity produced there, which has resulted in an increase in demand for energy.
November 2022: Persistent and Software AG will work on go-to-market initiatives, including as the creation of industry solutions and accelerators for the banking, financial services, and insurance, telecommunications, and healthcare and life sciences sectors. The recently established Professional Services Center of Excellence will bring the domain and technical capabilities required to deliver these solutions to meet client business goals. It will be supported by a strong talent base of Persistent-trained engineers.
June 2022: GlobalLogic Japan, Ltd. ("GlobalLogic Japan") is a Japanese affiliate of GlobalLogic Inc., which will be bought by Hitachi, Ltd. (TSE:6501, "Hitachi") in July 2021. Today, Nojima Corporation (TSE:7419, "Nojima") announced their alliance. The collaboration aims to hasten Nojima's Digital Transformation ("DX") strategy's creation and application.
Hardware
Solution
Services
Vibration Monitoring
Electrical Insulation
Infrared Thermography
Temperature Monitoring
Ultrasonic Leak Detector
Oil Analysis
Cloud
On-premise
Traditional Technique
Advanced Technique
Manufacturing
Healthcare
Energy & Utility
Automotive
Aerospace & Defense
Transportation
Others
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