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시장보고서
상품코드
1872049
예지보전 솔루션 : 세계 시장 점유율과 순위, 총판매량 및 수요 예측(2025-2031년)Predictive Maintenance Solution - Global Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031 |
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QYResearch
세계의 예측 보전 솔루션 시장 규모는 2024년에 111억 3,800만 달러로 추정되며, 2025-2031년의 예측 기간에 CAGR 17.6%로 성장하며, 2031년까지 351억 4,100만 달러로 확대할 것으로 예측되고 있습니다.
예지보전 솔루션은 실시간 센서 데이터, 머신러닝, AI 기술을 활용하여 설비 상태를 모니터링하고 고장이 발생하기 전에 그 가능성을 예측하는 시스템입니다. 최적의 유지보수 시기를 파악하여 예기치 못한 다운타임을 줄이고, 유지보수 비용을 절감하며, 장비 수명을 연장하고, 전반적인 운영 효율을 향상시키는 데 기여합니다. 이 솔루션은 제조업, 에너지 산업, 운송업, 의료 산업 등 다양한 산업 분야에서 폭넓게 활용되고 있습니다.
세계 주요 예측보전 솔루션 업체로는 IBM, Microsoft, SAP 등이 있습니다. 상위 5개사가 약 70%의 점유율을 차지하고 있습니다. 북미가 가장 큰 시장으로 약 35%, 유럽과 아시아태평양이 각각 약 30%, 28%의 점유율을 차지하고 있습니다. 제품별로는 클라우드 기반이 가장 큰 부문으로 75% 이상의 점유율을 차지하고 있습니다. 또한 용도별로는 산업-제조업이 가장 큰 용도이며, 그 다음으로 운송-물류가 그 뒤를 잇고 있습니다.
시장 성장 촉진요인
다운타임 및 유지보수 비용 절감에 대한 수요 증가: 산업 분야에서는 예기치 못한 설비 고장 방지, 수리 비용 절감, 생산 중단 최소화를 위해 예지보전 도입이 확대되고 있습니다.
IoT, AI, 머신러닝의 발전: 사물인터넷(IoT) 기기, 인공지능(AI), 머신러닝의 통합으로 실시간 모니터링, 고장 감지, 예측 분석이 가능해져 시장 성장을 가속하고 있습니다.
인더스트리 4.0 및 스마트 제조의 도입: 디지털화 및 자동화 제조 공정으로의 전환은 스마트 팩토리 생태계의 핵심 요소로서 예지보전의 도입을 촉진하고 있습니다.
자산의 최적화와 효율성에 대한 관심이 높아짐에 따라 예지보전은 조직이 중요 자산의 성능, 수명, 신뢰성을 극대화할 수 있도록 도와주며, 자본 집약적 산업에서 매력적인 솔루션이 되고 있습니다.
클라우드 및 엣지 컴퓨팅의 성장: 클라우드 기반 플랫폼과 엣지 컴퓨팅은 데이터 저장, 처리, 확장성을 향상시키고, 예측 솔루션의 접근성과 비용 효율성을 높이고 있습니다.
엄격한 규제와 안전 기준: 항공우주, 의료, 석유 및 가스 등의 분야는 엄격한 안전 규제가 적용되고 있으며, 이를 준수하기 위한 첨단 유지보수 전략의 필요성이 높아지고 있습니다.
시장이 해결해야 할 과제
높은 초기 투자 및 도입 비용: 센서, 데이터 인프라, AI 알고리즘 도입에 많은 비용이 소요될 수 있으며, 특히 중소기업(SME)에게는 큰 부담이 될 수 있습니다.
레거시 시스템과의 통합: 많은 조직은 여전히 구식 장비와 시스템에 의존하고 있으며, 대규모 업그레이드 없이 최신 예지보전 기술을 도입하기 어렵습니다.
데이터 품질 및 관리 과제: 예지보전은 고품질의 일관성 있는 데이터에 크게 의존합니다. 불완전한 데이터나 노이즈가 많은 데이터는 예측의 정확도를 떨어뜨리고 시스템의 신뢰성을 떨어뜨릴 수 있습니다.
숙련된 인력 부족: 데이터 사이언스, AI, 산업 시스템에 정통한 전문가가 부족하여 예지보전의 효과적인 도입과 확장을 가로막고 있습니다.
사이버 보안 문제: 예지보전 솔루션은 클라우드 연결 및 데이터 공유를 수반하는 경우가 많기 때문에 사이버 위협의 영향을 받기 쉬우므로 강력한 보안 대책이 필요합니다.
이 보고서는 세계의 예측 유지보수 솔루션 시장에 대해 총매출액, 주요 기업의 시장 점유율 및 순위를 중심으로 지역별, 국가별, 유형별, 용도별 분석을 종합적으로 제시하는 것을 목적으로 합니다.
예측 유지보수 솔루션 시장 규모 추정 및 예측은 2024년을 기준 연도로 하여 2020-2031년의 과거 데이터와 예측 데이터를 기반으로 한 매출액으로 제시되었습니다. 정량적 분석과 정성적 분석을 통해 독자들이 예측보전 솔루션에 대한 사업/성장 전략 수립, 시장 경쟁 구도 평가, 현재 시장에서의 자사 포지셔닝 분석, 정보에 입각한 사업적 판단을 내릴 수 있도록 돕습니다.
시장 세분화
기업별
- IBM
- Microsoft
- SAP
- GE Digital
- Schneider
- Hitachi
- Siemens
- Intel
- RapidMiner
- Rockwell Automation
- Software AG
- Cisco
- Oracle
- Fujitsu
- Dassault Systemes
- Augury Systems
- TIBCO Software
- Uptake
- Honeywell
- PTC
- Huawei
- ABB
- AVEVA
- SAS
- SKF
- Emerson
- Mpulse
- Maintenance Connection
- Dingo
- Particle
- Bosch
- C3.ai
- Dell
- Sigma Industrial Precision
유형별 부문
- 클라우드 기반
- 온프레미스
용도별 부문
- 산업·제조업
- 운송·물류
- 에너지·유틸리티
- 의료·생명과학
- 항공우주·방위
- 기타
지역별
- 북미
- 미국
- 캐나다
- 아시아태평양
- 중국
- 일본
- 한국
- 동남아시아
- 인도
- 호주
- 기타 아시아태평양
- 유럽
- 독일
- 프랑스
- 영국
- 이탈리아
- 네덜란드
- 북유럽 국가
- 기타 유럽
- 라틴아메리카
- 멕시코
- 브라질
- 기타 라틴아메리카
- 중동 및 아프리카
- 튀르키예
- 사우디아라비아
- 아랍에미리트
- 기타 중동 및 아프리카
자주 묻는 질문
The global market for Predictive Maintenance Solution was estimated to be worth US$ 11138 million in 2024 and is forecast to a readjusted size of US$ 35141 million by 2031 with a CAGR of 17.6% during the forecast period 2025-2031.
Predictive Maintenance Solution is a system that uses real-time sensor data, machine learning, and AI technologies to monitor equipment conditions and predict potential failures before they occur. By identifying the optimal time for maintenance, it helps reduce unplanned downtime, lower maintenance costs, extend equipment lifespan, and improve overall operational efficiency. This solution is widely applied across industries such as manufacturing, energy, transportation, and healthcare.
Global core predictive maintenance solution manufacturers include IBM, Microsoft, SAP etc.The top 5 companies hold a share about 70%.North America is the largest market, with a share about 35%, followed by Europe and Asia Pacific with the share about 30% and 28%.In terms of product, cloud based is the largest segment, with a share over 75%. And in terms of application, the largest application is industrial and manufacturing, followed by transportation and logistics.
Market Drivers
Rising Demand to Reduce Downtime and Maintenance Costs: Industries are increasingly adopting predictive maintenance to prevent unexpected equipment failures, lower repair costs, and minimize production disruptions.
Advancement in IoT, AI, and Machine Learning: The integration of Internet of Things (IoT) devices, artificial intelligence (AI), and machine learning enables real-time monitoring, fault detection, and predictive analytics, driving market growth.
Adoption of Industry 4.0 and Smart Manufacturing: The shift toward digital and automated manufacturing processes encourages the implementation of predictive maintenance as a core component of smart factory ecosystems.
Increased Focus on Asset Optimization and Efficiency: Predictive maintenance helps organizations maximize the performance, lifespan, and reliability of critical assets, making it attractive in capital-intensive industries.
Growth in Cloud and Edge Computing: Cloud-based platforms and edge computing improve data storage, processing, and scalability, making predictive solutions more accessible and cost-effective.
Stringent Regulatory and Safety Standards: Sectors such as aerospace, healthcare, and oil & gas are under strict safety regulations, fueling the need for advanced maintenance strategies to ensure compliance.
Market Challenges
High Initial Investment and Implementation Costs: Deploying sensors, data infrastructure, and AI algorithms can be expensive, especially for small and mid-sized enterprises (SMEs).
Integration with Legacy Systems: Many organizations still rely on outdated equipment or systems, making it difficult to implement modern predictive maintenance technologies without extensive upgrades.
Data Quality and Management Issues: Predictive maintenance relies heavily on high-quality, consistent data. Incomplete or noisy data can lead to inaccurate predictions and reduced system reliability.
Lack of Skilled Workforce: There is a shortage of professionals skilled in data science, AI, and industrial systems, which hinders the effective deployment and scaling of predictive maintenance.
Cybersecurity Concerns: As predictive maintenance solutions often involve cloud connectivity and data sharing, they are susceptible to cyber threats, requiring robust security measures.
This report aims to provide a comprehensive presentation of the global market for Predictive Maintenance Solution, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Predictive Maintenance Solution by region & country, by Type, and by Application.
The Predictive Maintenance Solution market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Predictive Maintenance Solution.
Market Segmentation
By Company
- IBM
- Microsoft
- SAP
- GE Digital
- Schneider
- Hitachi
- Siemens
- Intel
- RapidMiner
- Rockwell Automation
- Software AG
- Cisco
- Oracle
- Fujitsu
- Dassault Systemes
- Augury Systems
- TIBCO Software
- Uptake
- Honeywell
- PTC
- Huawei
- ABB
- AVEVA
- SAS
- SKF
- Emerson
- Mpulse
- Maintenance Connection
- Dingo
- Particle
- Bosch
- C3.ai
- Dell
- Sigma Industrial Precision
Segment by Type
- Cloud Based
- On-premises
Segment by Application
- Industrial and Manufacturing
- Transportation and Logistics
- Energy and Utilities
- Healthcare and Life Sciences
- Aerospace and Defense
- Others
By Region
- North America
- United States
- Canada
- Asia-Pacific
- China
- Japan
- South Korea
- Southeast Asia
- India
- Australia
- Rest of Asia-Pacific
- Europe
- Germany
- France
- U.K.
- Italy
- Netherlands
- Nordic Countries
- Rest of Europe
- Latin America
- Mexico
- Brazil
- Rest of Latin America
- Middle East & Africa
- Turkey
- Saudi Arabia
- UAE
- Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Predictive Maintenance Solution company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of Predictive Maintenance Solution in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Predictive Maintenance Solution in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.
Table of Contents
1 Market Overview
- 1.1 Predictive Maintenance Solution Product Introduction
- 1.2 Global Predictive Maintenance Solution Market Size Forecast (2020-2031)
- 1.3 Predictive Maintenance Solution Market Trends & Drivers
- 1.3.1 Predictive Maintenance Solution Industry Trends
- 1.3.2 Predictive Maintenance Solution Market Drivers & Opportunity
- 1.3.3 Predictive Maintenance Solution Market Challenges
- 1.3.4 Predictive Maintenance Solution Market Restraints
- 1.4 Assumptions and Limitations
- 1.5 Study Objectives
- 1.6 Years Considered
2 Competitive Analysis by Company
- 2.1 Global Predictive Maintenance Solution Players Revenue Ranking (2024)
- 2.2 Global Predictive Maintenance Solution Revenue by Company (2020-2025)
- 2.3 Key Companies Predictive Maintenance Solution Manufacturing Base Distribution and Headquarters
- 2.4 Key Companies Predictive Maintenance Solution Product Offered
- 2.5 Key Companies Time to Begin Mass Production of Predictive Maintenance Solution
- 2.6 Predictive Maintenance Solution Market Competitive Analysis
- 2.6.1 Predictive Maintenance Solution Market Concentration Rate (2020-2025)
- 2.6.2 Global 5 and 10 Largest Companies by Predictive Maintenance Solution Revenue in 2024
- 2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Predictive Maintenance Solution as of 2024)
- 2.7 Mergers & Acquisitions, Expansion
3 Segmentation by Type
- 3.1 Introduction by Type
- 3.1.1 Cloud Based
- 3.1.2 On-premises
- 3.2 Global Predictive Maintenance Solution Sales Value by Type
- 3.2.1 Global Predictive Maintenance Solution Sales Value by Type (2020 VS 2024 VS 2031)
- 3.2.2 Global Predictive Maintenance Solution Sales Value, by Type (2020-2031)
- 3.2.3 Global Predictive Maintenance Solution Sales Value, by Type (%) (2020-2031)
4 Segmentation by Application
- 4.1 Introduction by Application
- 4.1.1 Industrial and Manufacturing
- 4.1.2 Transportation and Logistics
- 4.1.3 Energy and Utilities
- 4.1.4 Healthcare and Life Sciences
- 4.1.5 Aerospace and Defense
- 4.1.6 Others
- 4.2 Global Predictive Maintenance Solution Sales Value by Application
- 4.2.1 Global Predictive Maintenance Solution Sales Value by Application (2020 VS 2024 VS 2031)
- 4.2.2 Global Predictive Maintenance Solution Sales Value, by Application (2020-2031)
- 4.2.3 Global Predictive Maintenance Solution Sales Value, by Application (%) (2020-2031)
5 Segmentation by Region
- 5.1 Global Predictive Maintenance Solution Sales Value by Region
- 5.1.1 Global Predictive Maintenance Solution Sales Value by Region: 2020 VS 2024 VS 2031
- 5.1.2 Global Predictive Maintenance Solution Sales Value by Region (2020-2025)
- 5.1.3 Global Predictive Maintenance Solution Sales Value by Region (2026-2031)
- 5.1.4 Global Predictive Maintenance Solution Sales Value by Region (%), (2020-2031)
- 5.2 North America
- 5.2.1 North America Predictive Maintenance Solution Sales Value, 2020-2031
- 5.2.2 North America Predictive Maintenance Solution Sales Value by Country (%), 2024 VS 2031
- 5.3 Europe
- 5.3.1 Europe Predictive Maintenance Solution Sales Value, 2020-2031
- 5.3.2 Europe Predictive Maintenance Solution Sales Value by Country (%), 2024 VS 2031
- 5.4 Asia Pacific
- 5.4.1 Asia Pacific Predictive Maintenance Solution Sales Value, 2020-2031
- 5.4.2 Asia Pacific Predictive Maintenance Solution Sales Value by Region (%), 2024 VS 2031
- 5.5 South America
- 5.5.1 South America Predictive Maintenance Solution Sales Value, 2020-2031
- 5.5.2 South America Predictive Maintenance Solution Sales Value by Country (%), 2024 VS 2031
- 5.6 Middle East & Africa
- 5.6.1 Middle East & Africa Predictive Maintenance Solution Sales Value, 2020-2031
- 5.6.2 Middle East & Africa Predictive Maintenance Solution Sales Value by Country (%), 2024 VS 2031
6 Segmentation by Key Countries/Regions
- 6.1 Key Countries/Regions Predictive Maintenance Solution Sales Value Growth Trends, 2020 VS 2024 VS 2031
- 6.2 Key Countries/Regions Predictive Maintenance Solution Sales Value, 2020-2031
- 6.3 United States
- 6.3.1 United States Predictive Maintenance Solution Sales Value, 2020-2031
- 6.3.2 United States Predictive Maintenance Solution Sales Value by Type (%), 2024 VS 2031
- 6.3.3 United States Predictive Maintenance Solution Sales Value by Application, 2024 VS 2031
- 6.4 Europe
- 6.4.1 Europe Predictive Maintenance Solution Sales Value, 2020-2031
- 6.4.2 Europe Predictive Maintenance Solution Sales Value by Type (%), 2024 VS 2031
- 6.4.3 Europe Predictive Maintenance Solution Sales Value by Application, 2024 VS 2031
- 6.5 China
- 6.5.1 China Predictive Maintenance Solution Sales Value, 2020-2031
- 6.5.2 China Predictive Maintenance Solution Sales Value by Type (%), 2024 VS 2031
- 6.5.3 China Predictive Maintenance Solution Sales Value by Application, 2024 VS 2031
- 6.6 Japan
- 6.6.1 Japan Predictive Maintenance Solution Sales Value, 2020-2031
- 6.6.2 Japan Predictive Maintenance Solution Sales Value by Type (%), 2024 VS 2031
- 6.6.3 Japan Predictive Maintenance Solution Sales Value by Application, 2024 VS 2031
- 6.7 South Korea
- 6.7.1 South Korea Predictive Maintenance Solution Sales Value, 2020-2031
- 6.7.2 South Korea Predictive Maintenance Solution Sales Value by Type (%), 2024 VS 2031
- 6.7.3 South Korea Predictive Maintenance Solution Sales Value by Application, 2024 VS 2031
- 6.8 Southeast Asia
- 6.8.1 Southeast Asia Predictive Maintenance Solution Sales Value, 2020-2031
- 6.8.2 Southeast Asia Predictive Maintenance Solution Sales Value by Type (%), 2024 VS 2031
- 6.8.3 Southeast Asia Predictive Maintenance Solution Sales Value by Application, 2024 VS 2031
- 6.9 India
- 6.9.1 India Predictive Maintenance Solution Sales Value, 2020-2031
- 6.9.2 India Predictive Maintenance Solution Sales Value by Type (%), 2024 VS 2031
- 6.9.3 India Predictive Maintenance Solution Sales Value by Application, 2024 VS 2031
7 Company Profiles
- 7.1 IBM
- 7.1.1 IBM Profile
- 7.1.2 IBM Main Business
- 7.1.3 IBM Predictive Maintenance Solution Products, Services and Solutions
- 7.1.4 IBM Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.1.5 IBM Recent Developments
- 7.2 Microsoft
- 7.2.1 Microsoft Profile
- 7.2.2 Microsoft Main Business
- 7.2.3 Microsoft Predictive Maintenance Solution Products, Services and Solutions
- 7.2.4 Microsoft Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.2.5 Microsoft Recent Developments
- 7.3 SAP
- 7.3.1 SAP Profile
- 7.3.2 SAP Main Business
- 7.3.3 SAP Predictive Maintenance Solution Products, Services and Solutions
- 7.3.4 SAP Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.3.5 SAP Recent Developments
- 7.4 GE Digital
- 7.4.1 GE Digital Profile
- 7.4.2 GE Digital Main Business
- 7.4.3 GE Digital Predictive Maintenance Solution Products, Services and Solutions
- 7.4.4 GE Digital Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.4.5 GE Digital Recent Developments
- 7.5 Schneider
- 7.5.1 Schneider Profile
- 7.5.2 Schneider Main Business
- 7.5.3 Schneider Predictive Maintenance Solution Products, Services and Solutions
- 7.5.4 Schneider Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.5.5 Schneider Recent Developments
- 7.6 Hitachi
- 7.6.1 Hitachi Profile
- 7.6.2 Hitachi Main Business
- 7.6.3 Hitachi Predictive Maintenance Solution Products, Services and Solutions
- 7.6.4 Hitachi Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.6.5 Hitachi Recent Developments
- 7.7 Siemens
- 7.7.1 Siemens Profile
- 7.7.2 Siemens Main Business
- 7.7.3 Siemens Predictive Maintenance Solution Products, Services and Solutions
- 7.7.4 Siemens Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.7.5 Siemens Recent Developments
- 7.8 Intel
- 7.8.1 Intel Profile
- 7.8.2 Intel Main Business
- 7.8.3 Intel Predictive Maintenance Solution Products, Services and Solutions
- 7.8.4 Intel Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.8.5 Intel Recent Developments
- 7.9 RapidMiner
- 7.9.1 RapidMiner Profile
- 7.9.2 RapidMiner Main Business
- 7.9.3 RapidMiner Predictive Maintenance Solution Products, Services and Solutions
- 7.9.4 RapidMiner Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.9.5 RapidMiner Recent Developments
- 7.10 Rockwell Automation
- 7.10.1 Rockwell Automation Profile
- 7.10.2 Rockwell Automation Main Business
- 7.10.3 Rockwell Automation Predictive Maintenance Solution Products, Services and Solutions
- 7.10.4 Rockwell Automation Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.10.5 Rockwell Automation Recent Developments
- 7.11 Software AG
- 7.11.1 Software AG Profile
- 7.11.2 Software AG Main Business
- 7.11.3 Software AG Predictive Maintenance Solution Products, Services and Solutions
- 7.11.4 Software AG Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.11.5 Software AG Recent Developments
- 7.12 Cisco
- 7.12.1 Cisco Profile
- 7.12.2 Cisco Main Business
- 7.12.3 Cisco Predictive Maintenance Solution Products, Services and Solutions
- 7.12.4 Cisco Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.12.5 Cisco Recent Developments
- 7.13 Oracle
- 7.13.1 Oracle Profile
- 7.13.2 Oracle Main Business
- 7.13.3 Oracle Predictive Maintenance Solution Products, Services and Solutions
- 7.13.4 Oracle Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.13.5 Oracle Recent Developments
- 7.14 Fujitsu
- 7.14.1 Fujitsu Profile
- 7.14.2 Fujitsu Main Business
- 7.14.3 Fujitsu Predictive Maintenance Solution Products, Services and Solutions
- 7.14.4 Fujitsu Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.14.5 Fujitsu Recent Developments
- 7.15 Dassault Systemes
- 7.15.1 Dassault Systemes Profile
- 7.15.2 Dassault Systemes Main Business
- 7.15.3 Dassault Systemes Predictive Maintenance Solution Products, Services and Solutions
- 7.15.4 Dassault Systemes Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.15.5 Dassault Systemes Recent Developments
- 7.16 Augury Systems
- 7.16.1 Augury Systems Profile
- 7.16.2 Augury Systems Main Business
- 7.16.3 Augury Systems Predictive Maintenance Solution Products, Services and Solutions
- 7.16.4 Augury Systems Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.16.5 Augury Systems Recent Developments
- 7.17 TIBCO Software
- 7.17.1 TIBCO Software Profile
- 7.17.2 TIBCO Software Main Business
- 7.17.3 TIBCO Software Predictive Maintenance Solution Products, Services and Solutions
- 7.17.4 TIBCO Software Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.17.5 TIBCO Software Recent Developments
- 7.18 Uptake
- 7.18.1 Uptake Profile
- 7.18.2 Uptake Main Business
- 7.18.3 Uptake Predictive Maintenance Solution Products, Services and Solutions
- 7.18.4 Uptake Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.18.5 Uptake Recent Developments
- 7.19 Honeywell
- 7.19.1 Honeywell Profile
- 7.19.2 Honeywell Main Business
- 7.19.3 Honeywell Predictive Maintenance Solution Products, Services and Solutions
- 7.19.4 Honeywell Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.19.5 Honeywell Recent Developments
- 7.20 PTC
- 7.20.1 PTC Profile
- 7.20.2 PTC Main Business
- 7.20.3 PTC Predictive Maintenance Solution Products, Services and Solutions
- 7.20.4 PTC Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.20.5 PTC Recent Developments
- 7.21 Huawei
- 7.21.1 Huawei Profile
- 7.21.2 Huawei Main Business
- 7.21.3 Huawei Predictive Maintenance Solution Products, Services and Solutions
- 7.21.4 Huawei Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.21.5 Huawei Recent Developments
- 7.22 ABB
- 7.22.1 ABB Profile
- 7.22.2 ABB Main Business
- 7.22.3 ABB Predictive Maintenance Solution Products, Services and Solutions
- 7.22.4 ABB Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.22.5 ABB Recent Developments
- 7.23 AVEVA
- 7.23.1 AVEVA Profile
- 7.23.2 AVEVA Main Business
- 7.23.3 AVEVA Predictive Maintenance Solution Products, Services and Solutions
- 7.23.4 AVEVA Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.23.5 AVEVA Recent Developments
- 7.24 SAS
- 7.24.1 SAS Profile
- 7.24.2 SAS Main Business
- 7.24.3 SAS Predictive Maintenance Solution Products, Services and Solutions
- 7.24.4 SAS Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.24.5 SAS Recent Developments
- 7.25 SKF
- 7.25.1 SKF Profile
- 7.25.2 SKF Main Business
- 7.25.3 SKF Predictive Maintenance Solution Products, Services and Solutions
- 7.25.4 SKF Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.25.5 SKF Recent Developments
- 7.26 Emerson
- 7.26.1 Emerson Profile
- 7.26.2 Emerson Main Business
- 7.26.3 Emerson Predictive Maintenance Solution Products, Services and Solutions
- 7.26.4 Emerson Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.26.5 Emerson Recent Developments
- 7.27 Mpulse
- 7.27.1 Mpulse Profile
- 7.27.2 Mpulse Main Business
- 7.27.3 Mpulse Predictive Maintenance Solution Products, Services and Solutions
- 7.27.4 Mpulse Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.27.5 Mpulse Recent Developments
- 7.28 Maintenance Connection
- 7.28.1 Maintenance Connection Profile
- 7.28.2 Maintenance Connection Main Business
- 7.28.3 Maintenance Connection Predictive Maintenance Solution Products, Services and Solutions
- 7.28.4 Maintenance Connection Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.28.5 Maintenance Connection Recent Developments
- 7.29 Dingo
- 7.29.1 Dingo Profile
- 7.29.2 Dingo Main Business
- 7.29.3 Dingo Predictive Maintenance Solution Products, Services and Solutions
- 7.29.4 Dingo Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.29.5 Dingo Recent Developments
- 7.30 Particle
- 7.30.1 Particle Profile
- 7.30.2 Particle Main Business
- 7.30.3 Particle Predictive Maintenance Solution Products, Services and Solutions
- 7.30.4 Particle Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.30.5 Particle Recent Developments
- 7.31 Bosch
- 7.31.1 Bosch Profile
- 7.31.2 Bosch Main Business
- 7.31.3 Bosch Predictive Maintenance Solution Products, Services and Solutions
- 7.31.4 Bosch Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.31.5 Bosch Recent Developments
- 7.32 C3.ai
- 7.32.1 C3.ai Profile
- 7.32.2 C3.ai Main Business
- 7.32.3 C3.ai Predictive Maintenance Solution Products, Services and Solutions
- 7.32.4 C3.ai Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.32.5 C3.ai Recent Developments
- 7.33 Dell
- 7.33.1 Dell Profile
- 7.33.2 Dell Main Business
- 7.33.3 Dell Predictive Maintenance Solution Products, Services and Solutions
- 7.33.4 Dell Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.33.5 Dell Recent Developments
- 7.34 Sigma Industrial Precision
- 7.34.1 Sigma Industrial Precision Profile
- 7.34.2 Sigma Industrial Precision Main Business
- 7.34.3 Sigma Industrial Precision Predictive Maintenance Solution Products, Services and Solutions
- 7.34.4 Sigma Industrial Precision Predictive Maintenance Solution Revenue (US$ Million) & (2020-2025)
- 7.34.5 Sigma Industrial Precision Recent Developments
8 Industry Chain Analysis
- 8.1 Predictive Maintenance Solution Industrial Chain
- 8.2 Predictive Maintenance Solution Upstream Analysis
- 8.2.1 Key Raw Materials
- 8.2.2 Raw Materials Key Suppliers
- 8.2.3 Manufacturing Cost Structure
- 8.3 Midstream Analysis
- 8.4 Downstream Analysis (Customers Analysis)
- 8.5 Sales Model and Sales Channels
- 8.5.1 Predictive Maintenance Solution Sales Model
- 8.5.2 Sales Channel
- 8.5.3 Predictive Maintenance Solution Distributors
9 Research Findings and Conclusion
10 Appendix
- 10.1 Research Methodology
- 10.1.1 Methodology/Research Approach
- 10.1.1.1 Research Programs/Design
- 10.1.1.2 Market Size Estimation
- 10.1.1.3 Market Breakdown and Data Triangulation
- 10.1.2 Data Source
- 10.1.2.1 Secondary Sources
- 10.1.2.2 Primary Sources
- 10.1.1 Methodology/Research Approach
- 10.2 Author Details
- 10.3 Disclaimer
