세계 예지보전 시장 규모는 2025-2032년의 예측 기간 동안 31.95%의 연평균 복합 성장률(CAGR)로 확대되어 2024년 109억 달러에서 2032년 1,001억 6,000만 달러로 성장할 것으로 예상됩니다.
IoT 기기의 보급과 함께 IoT 기술의 통합은 예지보전 시장을 크게 변화시키고 있으며, 에릭슨 AB에 따르면 2022년에는 4G 및 5G 네트워크를 통한 광대역 IoT가 13억 개의 연결에 도달하여 셀룰러 IoT 기기의 최대 점유율을 연결하는 주요 기술로 자리매김할 것으로 예상됩니다. 주요 기술로 자리 잡을 것으로 예상됩니다. 이러한 광범위한 연결성을 통해 기업은 방대한 양의 데이터를 실시간으로 수집하고 분석할 수 있으며, 장비와 기계의 정확한 모니터링이 용이해집니다. 따라서 기업은 IoT를 통합하여 잠재적인 고장을 예방하기 위해 적시에 개입할 수 있어 단순한 데이터 수집 이상의 이점을 얻을 수 있습니다. IoT가 제공하는 기능을 통해 기업은 유지보수 일정을 최적화하고, 다운타임을 줄이며, 가능한 한 낮은 운영 비용으로 시스템을 운영할 수 있습니다. 시간 기반의 유지보수 스케줄을 따르지 않고, 필요할 때 필요한 유지보수를 수행하는 조건 기반 유지보수를 할 수 있습니다. 즉, 운영 효율성을 높이고 중요한 자산의 수명을 연장할 수 있습니다.
또한, IoT 장비의 실시간 데이터는 유지보수 팀이 장비의 정확한 상태를 분석하고 적절한 유지보수 시기를 판단할 수 있도록 도와 의사결정 프로세스를 개선하는 데 도움이 됩니다. 이러한 사전 예방적 조치는 막대한 비용과 프로세스 마비를 초래할 수 있는 갑작스러운 고장을 방지할 수 있습니다. 광대역 IoT의 도입이 가속화됨에 따라 예지보전 시장은 크게 성장할 것입니다. 고도의 연결성과 데이터 분석의 결합으로 조직은 보다 지능적인 유지보수 전략을 채택할 수 있습니다. 또한, IoT의 통합은 유지 보수 관행을 개선하고 비즈니스 운영에 혁명을 일으켜 생산성을 높이고 서비스 제공을 개선할 수 있습니다.
이 보고서는 세계 예지보전 시장을 조사했으며, 시장 개요와 함께 구성요소별, 방법론별, 기업 규모별, 최종 사용자 산업별, 지역별 동향, 시장 진출기업 프로파일 등의 정보를 제공합니다.
Global predictive maintenance market is projected to witness a CAGR of 31.95% during the forecast period 2025-2032, growing from USD 10.90 billion in 2024 to USD 100.16 billion in 2032.
The integration of IoT technology is profoundly reshaping the predictive maintenance market owing to the proliferation of IoT devices. According to Ericsson AB, in 2022, broadband IoT, particularly through 4G and 5G networks, reached an impressive 1.3 billion connections establishing itself as the primary technology linking the largest share of cellular IoT devices. This extensive connectivity empowers businesses to collect and analyze vast amounts of data in real time, facilitating accurate monitoring of equipment and machinery. Thus, organizations can make timely interventions to prevent potential failures with the integration of IoT, which offers benefits more than simple data collection. The company can optimize its maintenance schedules, reduce downtimes, and operate the system at the lowest operational costs possible with the capabilities offered by IoT. It can be condition-based only to maintain, when necessary, rather than following a time-based maintenance schedule. This means it enhances operational efficiency but prolongs the life of critical assets.
Real-time data from IoT devices also helps improve the decision-making process as the maintenance team can analyze the exact health of equipment and determine the proper time for maintenance. Such proactive actions avoid sudden breakdowns that can significantly cost money and even paralyze the process. The predictive maintenance market is set for significant growth as the adoption of broadband IoT continues to accelerate. The combination of advanced connectivity and data analytics enables organizations to adopt more intelligent maintenance strategies. Additionally, the integration of IoT is improving maintenance practices and revolutionizing business operations, resulting in increased productivity and better service delivery.
For example, in August 2024, Asahi Kasei Engineering Co., Ltd. introduced V-MO, developed with joint efforts by Mitsui O.S.K. Lines (MOL), a cloud-based predictive maintenance service for ocean vessel motors that enhances operational efficiency through timely repairs before vessels reach port.
Increased Demand for Operational Efficiency Drives Growth in the Market
The growing demand for operational efficiency has significantly driven the growth of predictive maintenance. The need to achieve higher productivity with lower cost enables organizations to make a significant realization about the switch from a reactive to a proactive approach for maintenance. Predictive maintenance utilizes advanced technologies, like IoT sensors and data analytics, that enable real-time monitoring of equipment health. Hence, businesses can predict failures before they happen, minimizing unplanned downtime, which can be costly and disruptive to operations.
The flexibility of optimizing maintenance schedules according to actual equipment conditions instead of fixed intervals allows resources to be better allocated. Companies can focus on maintenance activities that are directly linked to productivity and, thus, improve asset utilization. Therefore, increasing awareness of these advantages is fueling more investment in predictive maintenance solutions as organizations can save costs, resulting in improved operational performance and further accelerating predictive maintenance market growth as companies drive for an increasingly competitive edge in a demanding marketplace.
For example, in June 2024, Hitachi Industrial Equipment Systems Co., Ltd. launched a predictive diagnosis service for air compressors that utilizes machine learning and maintenance expertise to enhance efficiency, prevent equipment stoppages, and reduce environmental impact on factory operations.
Shift Towards Condition-Based Maintenance Boosting the Predictive Maintenance Market
The shift toward condition-based maintenance models significantly fuels the growth of the predictive maintenance market. Condition-based maintenance focuses on the actual condition of equipment and is performed only when necessary, unlike traditional time-based maintenance. Predictive maintenance offers these benefits through the integration of advanced technologies such as IoT sensors, machine learning, and data analytics for continuous monitoring of equipment performance and health, fueling the predictive maintenance market growth in the forecasted period.
Organizations are becoming aware of the inadequacies of time-based strategies, resulting in organizations applying condition-based maintenance to raise efficiency and minimize unnecessary maintenance expenses. Companies also aim to minimize their unplanned downtime by the predictive approach while implementing maintenance, thereby enabling them to prolong their lifetime assets. This condition-based maintenance makes possible optimal resource deployment, ensuring that efforts go where maintenance is most urgently required. This transition optimizes operational performance and aligns with the growing emphasis on sustainability and resource efficiency. Thus, the demand for predictive maintenance market is witnessing the rise in the adoption of these solutions as businesses seek more effective maintenance strategies.
For example, in August 2024, Equinor ASA enhanced asset performance by implementing condition-based maintenance through SAP Asset Performance Management, transitioning from manual processes to a data-driven approach that optimizes asset health and performance, enabling more efficient resource allocation and decision-making.
Government Initiatives Fueling Predictive Maintenance Market Growth
Government initiatives are significant in the predictive maintenance market as they further push for advanced technologies and channel innovation in this field. There are programs like Manufacturing USA promoted by the Advanced Manufacturing National Program Office (AMNPO) in the United States. The AMNPO gives funding and resources for such research and development to go into the integration of manufacturers using IoT and data analytics. This improves efficiency while cutting operational costs, which makes companies competitive in a predictive maintenance market, creating a huge demand for these solutions. Similarly, the European Union's Horizon Europe pushes for digital transformation and sustainable transition across industries such as the manufacturing and transportation sectors, thereby supporting predictive maintenance technology as part of funding projects in developed advanced analytics and machine learning applications. This encourages enterprises to invest in predictive maintenance practices, enhancing operational effectiveness and reducing environmental impacts. This creates a strong market climate that fosters revenue growth for solution providers as these government programs energize innovation and adoption of predictive maintenance practices, thereby beneficially impacting industries that desire improved performance and sustainability.
For example, in November 2024, Manufacturing USA unveiled its 2024 Strategic Plan, which outlines its vision, mission, and goals to enhance the United States' manufacturing competitiveness. The plan emphasizes technology investment, workforce development, and collaboration to foster innovative, scalable manufacturing capabilities across the nation.
IT and Telecommunications Industry Dominates in Predictive Maintenance Market
The manufacturing industry is dominating the lead in predictive maintenance, using advanced technologies to boost efficiency and cut down operational costs. Predictive maintenance becomes critical in anticipation of equipment failures before they occur as manufacturers rely on more complex machinery. Companies can optimize maintenance schedules, thereby minimizing unplanned downtime and extending asset lifespan, by using IoT, data analytics, and machine learning. Predictive maintenance helps manufacturers to make data-driven decisions and enhance overall operational strategies. It is a proactive approach that enhances productivity and offers a competitive edge in the rapidly evolving predictive maintenance market. The manufacturing sector's adoption of such innovative solutions drives significant growth in the predictive maintenance market and makes it a key player in technological advancement and operational excellence.
North America Leads Predictive Maintenance Market Share
North America is leading the predictive maintenance market with specific government actions and key industry players. Implementing various initiatives in the United States government, such as the Advanced Manufacturing Partnership and the National Institute of Standards and Technology's Smart Manufacturing Program, aimed to promote advanced manufacturing technologies. Furthermore, the federal and state governments' huge investments in the infrastructure have focused on upgrading obsolete assets, which has resulted in a significant increase in the demand for predictive maintenance solutions. Industry majors in North America are emphasizing the building of complex analytics platforms and IoT sensors capable of real-time monitoring equipment. Furthermore, collaborations between companies and research institutions boost innovation and lead to sector-specific tailored predictive maintenance solutions in aerospace, automotive, energy, etc. North America has taken the lead position through supportive policies and an innovation ecosystem that will drive widespread adoption and technological advancements in the predictive maintenance market.
For instance, in June 2024, C3 AI, Inc. and Holcim Group AG deployed C3 AI Reliability for predictive maintenance across Holcim's global network that enhances operational efficiency and sustainability in cement manufacturing as part of Holcim's Plants of Tomorrow digital transformation initiative.
Future Market Scenario (2025-2032F)
Advanced artificial intelligence and machine learning algorithms may offer more accurate predictions of equipment failures, optimizing maintenance schedules and minimizing downtime.
The widespread adoption of digital twin technology will enable organizations to develop asset real-time virtual replicas, thereby enabling sophisticated monitoring and proactive maintenance strategies.
Predictive maintenance will grow beyond manufacturing and energy, penetrating sectors such as agriculture, healthcare, and transportation with continuous innovation to save on costs and improve safety.
The proliferation of IoT devices will drive edge computing, enabling real-time data processing and quicker decision-making, further enhancing the effectiveness of predictive maintenance solutions.
Key Players Landscape and Outlook
The predictive maintenance market exhibits a diverse landscape of key players consisting of technology providers, software developers, and companies focused on IoT solutions, where these entities are in continuous collaboration to integrate advanced analytics, machine learning, and IoT capabilities into their services. The predictive maintenance market is expanding and is maintained by the growing demand for operational efficiency and cost reduction across industries. Organizations are recognizing the importance of data-based decision-making and will further invest in predictive maintenance technology. Integration with artificial intelligence and edge computing for predictive maintenance is a major trend, thereby providing real-time analytics and quicker responses. It will enable easy connectivity among devices and facilitate a good effect of predictive maintenance strategy as 5G networks become widespread. Hence, the predictive maintenance market is forecasted to grow strongly, with immense technology and application advancements across different sectors.
In October 2024, Cognizant Technology Solutions Corporation entered into a strategic collaboration agreement with Amazon Web Services, Inc. to enhance smart manufacturing capabilities, leveraging generative AI and IoT solutions for global enterprises in automotive, life sciences, and consumer goods.
In June 2024, Hitachi Ltd. and Microsoft Corp. partnered on a multibillion-dollar project to integrate Microsoft cloud services and generative AI into Hitachi's Lumada Solutions, enhancing productivity and innovation across industries over three years.
All segments will be provided for all regions and countries covered
Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.