세계의 운영 예지보전 시장 보고서(2025년)
Operational Predictive Maintenance Global Market Report 2025
상품코드 : 1694672
리서치사 : The Business Research Company
발행일 : On Demand Report
페이지 정보 : 영문 200 Pages
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한글목차

운영 예지보전 시장 규모는 향후 몇 년 동안 26.4%의 연평균 성장률(CAGR)을 기록하며 2029년에는 235억 7,000만 달러 규모로 성장할 것으로 예상됩니다. 예측 기간 동안의 성장은 새로운 산업 및 응용 분야로의 확장, 사전 예방적 유지보수 솔루션에 대한 수요, 신흥국 시장 침투, 예지보전 채택, 지속가능성 및 에너지 효율에 대한 관심 증가 등에 기인합니다. 예측 기간 동안 주요 동향으로는 IoT 센서와 데이터 분석의 통합, 머신러닝 알고리즘 채택, 산업 간 애플리케이션 확대, 클라우드 기반 플랫폼 개발, 기업 자산 관리 시스템과의 통합 등이 있습니다.

운영 예지보전 시장은 센서, 액추에이터, 가전제품 등 무선으로 네트워크에 연결하여 데이터를 전송하는 사물인터넷(IoT) 기기의 증가로 인해 성장할 것으로 예상됩니다. 이러한 성장은 인터넷 연결성 향상, 산업 자동화 확대, 공급망 관리 강화, 데이터 분석의 발전 등의 요인으로 인해 IoT 디바이스는 실시간 모니터링, 데이터 분석, 문제 조기 발견, 상태 기반 유지보수를 가능케 하기 때문에 운영 예지보전에 매우 중요한 역할을 합니다. 이러한 기능을 통해 기업은 자산 성능을 최적화하고, 비용을 절감하며, 운영 효율성을 향상시킬 수 있습니다. 예를 들어, 영국에 본사를 둔 업계 단체인 GSM Association은 전 세계 IoT 연결 수가 2021년 151억 개에서 2025년 233억 개로 증가할 것으로 예측하고 있습니다. 이처럼 IoT 기기의 증가는 운영 예지보전 시장의 주요 촉진요인으로 작용하고 있습니다.

운영 예지보전 시장의 주요 업체들은 장비의 신뢰성과 효율성을 향상시키기 위해 AI 기반 분석 및 실시간 모니터링과 같은 기술 혁신을 우선순위에 두고 있습니다. 이러한 발전을 통해 기업은 유지보수의 필요성을 사전에 관리하고 운영 중단을 줄일 수 있습니다. 기계 학습은 센서 데이터를 분석하여 잠재적인 문제를 알려주는 패턴을 식별하여 성능을 최적화하고 고장을 예방하기 위한 예방적 유지보수를 실행하는 데 도움이 됩니다. 예를 들어, 일본의 산업 장비 전문 기업인 Hitachi Industrial Equipment Systems는 2024년 6월 에어 컴프레서의 '예지 진단 서비스'를 도입했습니다. 이 서비스는 머신러닝과 원격 모니터링을 통해 잠재적인 문제를 감지하고 예방하며, 실시간 데이터와 유지보수 전문지식을 결합하여 운영 효율을 높이고, 가동 중단 시간을 최소화하며, 환경에 미치는 영향을 줄입니다.

목차

제1장 주요 요약

제2장 시장 특징

제3장 시장 동향과 전략

제4장 시장 - 금리, 인플레이션, 지정학, 코로나, 회복이 시장에 미치는 영향을 포함한 거시경제 시나리오

제5장 세계의 성장 분석과 전략 분석 프레임워크

제6장 시장 세분화

제7장 지역별·국가별 분석

제8장 아시아태평양 시장

제9장 중국 시장

제10장 인도 시장

제11장 일본 시장

제12장 호주 시장

제13장 인도네시아 시장

제14장 한국 시장

제15장 서유럽 시장

제16장 영국 시장

제17장 독일 시장

제18장 프랑스 시장

제19장 이탈리아 시장

제20장 스페인 시장

제21장 동유럽 시장

제22장 러시아 시장

제23장 북미 시장

제24장 미국 시장

제25장 캐나다 시장

제26장 남미 시장

제27장 브라질 시장

제28장 중동 시장

제29장 아프리카 시장

제30장 경쟁 구도와 기업 개요

제31장 기타 주요 기업과 혁신적 기업

제32장 세계의 시장 경쟁 벤치마킹과 대시보드

제33장 주요 인수합병

제34장 최근의 시장 동향

제35장 시장 잠재력이 높은 국가, 부문, 전략

제36장 부록

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영문 목차

영문목차

Operational Predictive Maintenance (OPM) is a proactive maintenance strategy that leverages data analytics, machine learning, and predictive modeling techniques to forecast equipment failures or maintenance requirements before they occur. The objective of OPM is to minimize downtime, reduce maintenance costs, and optimize the efficiency and reliability of equipment and processes.

The primary types of Operational Predictive Maintenance include software and services. Software encompasses a collection of programs, instructions, and data that enable computers and other electronic devices to perform specific tasks, functions, or operations. It can be deployed in the cloud or on-premise and utilizes various technologies such as machine learning, deep learning, big data, and analytics. It is utilized by various end-users, including the public sector, automotive, manufacturing, healthcare, energy and utilities, transportation, and others.

The operational predictive maintenance market research report is one of a series of new reports from The Business Research Company that provides operational predictive maintenance market statistics, including operational predictive maintenance industry global market size, regional shares, competitors with an operational predictive maintenance market share, detailed operational predictive maintenance market segments, market trends and opportunities, and any further data you may need to thrive in the operational predictive maintenance industry. This operational predictive maintenance market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The operational predictive maintenance market size has grown exponentially in recent years. It will grow from $7.31 billion in 2024 to $9.24 billion in 2025 at a compound annual growth rate (CAGR) of 26.4%. The growth in the historic period can be attributed to cost savings from reduced downtime and maintenance costs, improved asset reliability and performance, enhanced safety and risk mitigation, regulatory compliance requirements, growing awareness of predictive maintenance benefits.

The operational predictive maintenance market size is expected to see exponential growth in the next few years. It will grow to $23.57 billion in 2029 at a compound annual growth rate (CAGR) of 26.4%. The growth in the forecast period can be attributed to expansion into new industries and applications, demand for proactive maintenance solutions, market penetration in emerging economies, predictive maintenance adoption, increased focus on sustainability and energy efficiency initiatives. Major trends in the forecast period include integration of IoT sensors and data analytics, adoption of machine learning algorithms, expansion of applications across industries, development of cloud-based platforms, integration with enterprise asset management systems.

The operational predictive maintenance market is anticipated to grow due to the rising number of IoT (Internet of Things) devices. IoT devices, which include sensors, actuators, and appliances, connect wirelessly to networks and transmit data. This growth is driven by factors such as improved internet connectivity, greater industrial automation, enhanced supply chain management, and advancements in data analytics. IoT devices are crucial for operational predictive maintenance as they enable real-time monitoring, data analysis, early problem detection, and condition-based maintenance. These capabilities help organizations optimize asset performance, reduce costs, and improve operational efficiency. For example, the GSM Association, a UK-based industry group, forecasts that global IoT connections will grow to 23.3 billion by 2025, up from 15.1 billion in 2021. Thus, the increasing number of IoT devices is a key driver of the operational predictive maintenance market.

Key players in the operational predictive maintenance market are prioritizing technological innovations, such as AI-driven analytics and real-time monitoring, to improve equipment reliability and efficiency. These advancements enable businesses to proactively manage maintenance needs and reduce operational disruptions. Machine learning is employed to analyze sensor data, identifying patterns that signal potential issues, which helps in performing proactive maintenance to optimize performance and prevent failures. For example, in June 2024, Hitachi Industrial Equipment Systems Co., Ltd., a Japan-based company specializing in industrial equipment, introduced the "Predictive Diagnosis Service" for air compressors. This service uses machine learning and remote monitoring to detect and prevent potential issues, combining real-time data with maintenance expertise to improve operational efficiency, minimize downtime, and lessen environmental impact.

In March 2023, Schaeffler Group, a German automotive industry company, acquired ECO-Adapt SAS to bolster its presence in the growing predictive maintenance market. This strategic move aims to expand Schaeffler's service offerings, strengthen its market position, and contribute to its customers' sustainable future. ECO-Adapt SAS, based in France, specializes in energy monitoring and predictive maintenance services.

Major companies operating in the operational predictive maintenance market are Google LLC, Microsoft Corporation, Robert Bosch GmbH, Hitachi Ltd., Amazon Web Services Inc., The International Business Machines Corporation, General Electric Company, Schneider Electric SE, SAP SE, Svenska Kullagerfabriken AB, Rockwell Automation Inc., SAS Institute Inc., Micro Focus, Splunk Inc., PTC Inc., Software AG, TIBCO Software Inc., C3.ai Inc., Softweb Solutions Inc., Fiix Software, Uptake Technologies Inc., eMaint Enterprises LLC, Seebo Interactive Ltd., Asystom, Ecolibrium Energy

North America was the largest region in the operational predictive maintenance market in 2024. The regions covered in the operational predictive maintenance market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the operational predictive maintenance market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The operational predictive maintenance market includes revenues earned by entities by providing services such as data analytics and modeling, predictive maintenance modeling, condition monitoring, failure prediction and diagnostics, performance monitoring and optimization, and training and support. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Operational Predictive Maintenance Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on operational predictive maintenance market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

Where is the largest and fastest growing market for operational predictive maintenance ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The operational predictive maintenance market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.

Scope

Table of Contents

1. Executive Summary

2. Operational Predictive Maintenance Market Characteristics

3. Operational Predictive Maintenance Market Trends And Strategies

4. Operational Predictive Maintenance Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Covid And Recovery On The Market

5. Global Operational Predictive Maintenance Growth Analysis And Strategic Analysis Framework

6. Operational Predictive Maintenance Market Segmentation

7. Operational Predictive Maintenance Market Regional And Country Analysis

8. Asia-Pacific Operational Predictive Maintenance Market

9. China Operational Predictive Maintenance Market

10. India Operational Predictive Maintenance Market

11. Japan Operational Predictive Maintenance Market

12. Australia Operational Predictive Maintenance Market

13. Indonesia Operational Predictive Maintenance Market

14. South Korea Operational Predictive Maintenance Market

15. Western Europe Operational Predictive Maintenance Market

16. UK Operational Predictive Maintenance Market

17. Germany Operational Predictive Maintenance Market

18. France Operational Predictive Maintenance Market

19. Italy Operational Predictive Maintenance Market

20. Spain Operational Predictive Maintenance Market

21. Eastern Europe Operational Predictive Maintenance Market

22. Russia Operational Predictive Maintenance Market

23. North America Operational Predictive Maintenance Market

24. USA Operational Predictive Maintenance Market

25. Canada Operational Predictive Maintenance Market

26. South America Operational Predictive Maintenance Market

27. Brazil Operational Predictive Maintenance Market

28. Middle East Operational Predictive Maintenance Market

29. Africa Operational Predictive Maintenance Market

30. Operational Predictive Maintenance Market Competitive Landscape And Company Profiles

31. Operational Predictive Maintenance Market Other Major And Innovative Companies

32. Global Operational Predictive Maintenance Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Operational Predictive Maintenance Market

34. Recent Developments In The Operational Predictive Maintenance Market

35. Operational Predictive Maintenance Market High Potential Countries, Segments and Strategies

36. Appendix

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